Uncertainty estimation with bias-correction for flow series based on rating curve

Science.gov (United States)

Shao, Quanxi; Lerat, Julien; Podger, Geoff; Dutta, Dushmanta

2014-03-01

Streamflow discharge constitutes one of the fundamental data required to perform water balance studies and develop hydrological models. A rating curve, designed based on a series of concurrent stage and discharge measurements at a gauging location, provides a way to generate complete discharge time series with a reasonable quality if sufficient measurement points are available. However, the associated uncertainty is frequently not available even though it has a significant impact on hydrological modelling. In this paper, we identify the discrepancy of the hydrographers' rating curves used to derive the historical discharge data series and proposed a modification by bias correction which is also in the form of power function as the traditional rating curve. In order to obtain the uncertainty estimation, we propose a further both-side Box-Cox transformation to stabilize the regression residuals as close to the normal distribution as possible, so that a proper uncertainty can be attached for the whole discharge series in the ensemble generation. We demonstrate the proposed method by applying it to the gauging stations in the Flinders and Gilbert rivers in north-west Queensland, Australia.

Smuggling, non-fundamental uncertainty, and parallel market exchange rate volatility

OpenAIRE

Richard Clay Barnett

2003-01-01

We explore a model where smuggling and a parallel currency market arise, owing to government restrictions that prevent agents from legally holding foreign exchange. Despite such restrictions, agents are able to diversify their savings, holding both domestic and parallel foreign cash, basing their portfolio allocation on current and prospective parallel exchange rates. We attribute movements in parallel rates to non-fundamental uncertainty. The model generates equilibria with both positive and...

Exchange rate uncertainty and deviations from Purchasing\\ud Power Parity: evidence from the G7 area

OpenAIRE

Arghyrou, Michael; Gregoriou, Andros; Pourpourides, Panayiotis; Cardiff University

2009-01-01

Arghyrou, Gregoriou and Pourpourides (2009) argue that exchange rate uncertainty causes deviations from the law of one price. We test this hypothesis on aggregate data from the G7-area. We find that exchange rate uncertainty explains to a significant degree deviations from Purchasing Power Parity.

MERGERS IN ΛCDM: UNCERTAINTIES IN THEORETICAL PREDICTIONS AND INTERPRETATIONS OF THE MERGER RATE

International Nuclear Information System (INIS)

Hopkins, Philip F.; Bundy, Kevin; Wetzel, Andrew; Ma, Chung-Pei; Croton, Darren; Khochfar, Sadegh; Hernquist, Lars; Genel, Shy; Van den Bosch, Frank; Somerville, Rachel S.; Keres, Dusan; Stewart, Kyle; Younger, Joshua D.

2010-01-01

Different theoretical methodologies lead to order-of-magnitude variations in predicted galaxy-galaxy merger rates. We examine how this arises and quantify the dominant uncertainties. Modeling of dark matter and galaxy inspiral/merger times contribute factor of ∼2 uncertainties. Different estimates of the halo-halo merger rate, the subhalo 'destruction' rate, and the halo merger rate with some dynamical friction time delay for galaxy-galaxy mergers, agree to within this factor of ∼2, provided proper care is taken to define mergers consistently. There are some caveats: if halo/subhalo masses are not appropriately defined the major-merger rate can be dramatically suppressed, and in models with 'orphan' galaxies and under-resolved subhalos the merger timescale can be severely over-estimated. The dominant differences in galaxy-galaxy merger rates between models owe to the treatment of the baryonic physics. Cosmological hydrodynamic simulations without strong feedback and some older semi-analytic models (SAMs), with known discrepancies in mass functions, can be biased by large factors (∼5) in predicted merger rates. However, provided that models yield a reasonable match to the total galaxy mass function, the differences in properties of central galaxies are sufficiently small to alone contribute small (factor of ∼1.5) additional systematics to merger rate predictions. But variations in the baryonic physics of satellite galaxies in models can also have a dramatic effect on merger rates. The well-known problem of satellite 'over-quenching' in most current SAMs-whereby SAM satellite populations are too efficiently stripped of their gas-could lead to order-of-magnitude under-estimates of merger rates for low-mass, gas-rich galaxies. Models in which the masses of satellites are fixed by observations (or SAMs adjusted to resolve this 'over-quenching') tend to predict higher merger rates, but with factor of ∼2 uncertainties stemming from the uncertainty in those

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

Science.gov (United States)

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

2017-04-01

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

Diversity Dynamics in Nymphalidae Butterflies: Effect of Phylogenetic Uncertainty on Diversification Rate Shift Estimates

Science.gov (United States)

Peña, Carlos; Espeland, Marianne

2015-01-01

The species rich butterfly family Nymphalidae has been used to study evolutionary interactions between plants and insects. Theories of insect-hostplant dynamics predict accelerated diversification due to key innovations. In evolutionary biology, analysis of maximum credibility trees in the software MEDUSA (modelling evolutionary diversity using stepwise AIC) is a popular method for estimation of shifts in diversification rates. We investigated whether phylogenetic uncertainty can produce different results by extending the method across a random sample of trees from the posterior distribution of a Bayesian run. Using the MultiMEDUSA approach, we found that phylogenetic uncertainty greatly affects diversification rate estimates. Different trees produced diversification rates ranging from high values to almost zero for the same clade, and both significant rate increase and decrease in some clades. Only four out of 18 significant shifts found on the maximum clade credibility tree were consistent across most of the sampled trees. Among these, we found accelerated diversification for Ithomiini butterflies. We used the binary speciation and extinction model (BiSSE) and found that a hostplant shift to Solanaceae is correlated with increased net diversification rates in Ithomiini, congruent with the diffuse cospeciation hypothesis. Our results show that taking phylogenetic uncertainty into account when estimating net diversification rate shifts is of great importance, as very different results can be obtained when using the maximum clade credibility tree and other trees from the posterior distribution. PMID:25830910

Diversity dynamics in Nymphalidae butterflies: effect of phylogenetic uncertainty on diversification rate shift estimates.

Directory of Open Access Journals (Sweden)

Carlos Peña

Full Text Available The species rich butterfly family Nymphalidae has been used to study evolutionary interactions between plants and insects. Theories of insect-hostplant dynamics predict accelerated diversification due to key innovations. In evolutionary biology, analysis of maximum credibility trees in the software MEDUSA (modelling evolutionary diversity using stepwise AIC is a popular method for estimation of shifts in diversification rates. We investigated whether phylogenetic uncertainty can produce different results by extending the method across a random sample of trees from the posterior distribution of a Bayesian run. Using the MultiMEDUSA approach, we found that phylogenetic uncertainty greatly affects diversification rate estimates. Different trees produced diversification rates ranging from high values to almost zero for the same clade, and both significant rate increase and decrease in some clades. Only four out of 18 significant shifts found on the maximum clade credibility tree were consistent across most of the sampled trees. Among these, we found accelerated diversification for Ithomiini butterflies. We used the binary speciation and extinction model (BiSSE and found that a hostplant shift to Solanaceae is correlated with increased net diversification rates in Ithomiini, congruent with the diffuse cospeciation hypothesis. Our results show that taking phylogenetic uncertainty into account when estimating net diversification rate shifts is of great importance, as very different results can be obtained when using the maximum clade credibility tree and other trees from the posterior distribution.

Determination of the reference air kerma rate for 192Ir brachytherapy sources and the related uncertainty

International Nuclear Information System (INIS)

Dijk, Eduard van; Kolkman-Deurloo, Inger-Karine K.; Damen, Patricia M. G.

2004-01-01

Different methods exist to determine the air kerma calibration factor of an ionization chamber for the spectrum of a 192 Ir high-dose-rate (HDR) or pulsed-dose-rate (PDR) source. An analysis of two methods to obtain such a calibration factor was performed: (i) the method recommended by [Goetsch et al., Med. Phys. 18, 462-467 (1991)] and (ii) the method employed by the Dutch national standards institute NMi [Petersen et al., Report S-EI-94.01 (NMi, Delft, The Netherlands, 1994)]. This analysis showed a systematic difference on the order of 1% in the determination of the strength of 192 Ir HDR and PDR sources depending on the method used for determining the air kerma calibration factor. The definitive significance of the difference between these methods can only be addressed after performing an accurate analysis of the associated uncertainties. For an NE 2561 (or equivalent) ionization chamber and an in-air jig, a typical uncertainty budget of 0.94% was found with the NMi method. The largest contribution in the type-B uncertainty is the uncertainty in the air kerma calibration factor for isotope i, N k i , as determined by the primary or secondary standards laboratories. This uncertainty is dominated by the uncertainties in the physical constants for the average mass-energy absorption coefficient ratio and the stopping power ratios. This means that it is not foreseeable that the standards laboratories can decrease the uncertainty in the air kerma calibration factors for ionization chambers in the short term. When the results of the determination of the 192 Ir reference air kerma rates in, e.g., different institutes are compared, the uncertainties in the physical constants are the same. To compare the applied techniques, the ratio of the results can be judged by leaving out the uncertainties due to these physical constants. In that case an uncertainty budget of 0.40% (coverage factor=2) should be taken into account. Due to the differences in approach between the

Mass Spectrometric Calibration of Controlled Fluoroform Leak Rate Devices Technique and Uncertainty Analysis

CERN Document Server

Balsley, S D; Laduca, C A

2003-01-01

Controlled leak rate devices of fluoroform on the order of 10 sup - sup 8 atm centre dot cc sec sup - sup 1 at 25 C are used to calibrate QC-1 War Reserve neutron tube exhaust stations for leak detection sensitivity. Close-out calibration of these tritium-contaminated devices is provided by the Gas Dynamics and Mass Spectrometry Laboratory, Organization 14406, which is a tritium analytical facility. The mass spectrometric technique used for the measurement is discussed, as is the first principals calculation (pressure, volume, temperature and time). The uncertainty of the measurement is largely driven by contributing factors in the determination of P, V and T. The expanded uncertainty of the leak rate measurement is shown to be 4.42%, with a coverage factor of 3 (k=3).

Estimation of Uncertainty in Tracer Gas Measurement of Air Change Rates

Directory of Open Access Journals (Sweden)

Atsushi Iizuka

2010-12-01

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

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

Science.gov (United States)

Iizuka, Atsushi; Okuizumi, Yumiko; Yanagisawa, Yukio

2010-12-01

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

An estimation of reactor thermal power uncertainty using UFM-based feedwater flow rate in nuclear power plants

International Nuclear Information System (INIS)

Byung Ryul Jung; Ho Cheol Jang; Byung Jin Lee; Se Jin Baik; Woo Hyun Jang

2005-01-01

Most of Pressurized Water Reactors (PWRs) utilize the venturi meters (VMs) to measure the feedwater (FW) flow rate to the steam generator in the calorimetric measurement, which is used in the reactor thermal power (RTP) estimation. However, measurement drifts have been experienced due to some anomalies on the venturi meter (generally called the venturi meter fouling). The VM's fouling tends to increase the measured pressure drop across the meter, which results in indication of increased feedwater flow rate. Finally, the reactor thermal power is overestimated and the actual reactor power is to be reduced to remain within the regulatory limits. To overcome this VM's fouling problem, the Ultrasonic Flow Meter (UFM) has recently been gaining attention in the measurement of the feedwater flow rate. This paper presents the applicability of a UFM based feedwater flow rate in the estimation of reactor thermal power uncertainty. The FW and RTP uncertainties are compared in terms of sensitivities between the VM- and UFM-based feedwater flow rates. Data from typical Optimized Power Reactor 1000 (OPR1000) plants are used to estimate the uncertainty. (authors)

Proton capture in the nuclei 21Ne and 22Ne and its influence on the solar hydrogen burning in the neon-sodium cyclus

International Nuclear Information System (INIS)

Goerres, J.

1983-01-01

The aim of this thesis was to remove the uncertainties in the reaction rates of 21 Ne(p,γ) 22 Na and 22 Ne(p,γ) 23 Na in order to can make founded statements about the hydrogen burning in the NeNa cyclus. After the description of the experimental arrangement the search for resonances in the reaction 21 Ne(p,γ) 22 Na below Esub(p)=355 keV is reported. While the theory of the direct radiation capture is discussed the experimental results of the search for this transitions in 21 Ne(p,γ) 22 Na respectively 22 Ne(p,γ) 23 Na are presented. The astrophysical aspects of the results of this thesis are discussed and summarizingly presented. (orig./HSI) [de

Ionization balance for Ti and Cr ions: effects of uncertainty in dielectronic recombination rate

International Nuclear Information System (INIS)

Seon, Kwang-Il; Nam, Uk-Won; Park, Il H

2003-01-01

The available electron-impact ionization cross sections for Ti and Cr ions are reviewed, and calculations of the ionization balance for the ions under coronal equilibrium are presented. The calculated ionic abundance fractions are compared with those of previous works. The effects of modelling uncertainty in dielectronic recombination on isoelectronic line ratios, which are formed using the same spectral line from two elements of slightly different atomic numbers, are discussed concentrating on high temperature ranges. Also discussed are the effects of modelling uncertainty on inter-ionization stage line ratios formed from adjacent ionization stages. It is demonstrated that the modelling uncertainty in dielectronic recombination tends to cancel out only when the isoelectronic line ratio of He-like ions is considered, and that the sensitivity of the isoelectronic line ratios to the modelling uncertainty tends to increase for less ionized stages. It is also found that the interstage line ratios are less sensitive to the typical ∼20% uncertainties of dielectronic rates than the isoelectronic line ratios, and that the interstage line ratio of He-to Li-like ions in Ti and Cr plasmas is a better choice for a temperature diagnostic in the temperature ranges from ∼0.6 to ∼1.5 keV in which Li-like ions have maximum ionic abundances

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

Science.gov (United States)

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

2012-04-01

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

Deterministic 3D transport, sensitivity and uncertainty analysis of TPR and reaction rate measurements in HCPB Breeder Blanket mock-up benchmark

International Nuclear Information System (INIS)

Kodeli, I.

2006-01-01

The Helium-Cooled Pebble Bed (HCPB) Breeder Blanket mock-up benchmark experiment was analysed using the deterministic transport, sensitivity and uncertainty code system in order to determine the Tritium Production Rate (TPR) in the ceramic breeder and the neutron reaction rates in beryllium, both nominal values and the corresponding uncertainties. The experiment, performed in 2005 to validate the HCPB concept, consists of a metallic beryllium set-up with two double layers of breeder material (Li 2 CO 3 powder). The reaction rate measurements include the Li 2 CO 3 pellets for the tritium breeding monitoring and activation foils, inserted at several axial and lateral locations in the block. In addition to the well established and validated procedure based on the 2-dimensional (2D) code DORT, a new approach for the 3D modelling was validated based on the TORT/GRTUNCL3D transport codes. The SUSD3D code, also in 3D geometry, was used for the cross-section sensitivity and uncertainty calculations. These studies are useful for the interpretation of the experimental measurements, in particular to assess the uncertainties linked to the basic nuclear data. The TPR, the neutron activation rates and the associated uncertainties were determined using the EFF-3.0 9 Be nuclear cross section and covariance data, and compared with those from other evaluations, like FENDL-2.1. Sensitivity profiles and nuclear data uncertainties of the TPR and detector reaction rates with respect to the cross-sections of 9 Be, 6 Li, 7 Li, O and C were determined at different positions in the experimental block. (author)

Build to order and entry/exit strategies under exchange rate uncertainty

Directory of Open Access Journals (Sweden)

Lin Chin-Tsai

2004-01-01

Full Text Available Under uncertainty of exchange rate, we extend the build to order production model of Lin et al. (2002 by considering the export-oriented manufacturer to make decisions to switch production location freely between domestic and foreign ones. The export-oriented manufacturer is risk neutral and has rational expectations. When we transfer the production location from domestic (foreign to foreign (domestic, and the production location transferring cost and the drift of real exchange rate are both equal to zero, then the optimal entry and exit threshold value of Cobb-Douglas production function are equal, no matter whether we use real options or net present value method. Thus export-oriented manufacturer can make decisions at the optimal transfer threshold value for transferable locations wherever the production locations are. It provides the export-oriented manufacturer with another way of thinking.

Optimization of Korean energy planning for sustainability considering uncertainties in learning rates and external factors

International Nuclear Information System (INIS)

Kim, Seunghyok; Koo, Jamin; Lee, Chang Jun; Yoon, En Sup

2012-01-01

During the last few decades, energy planning has focused on meeting domestic demand at lower total costs. However, global warming and the shared recognition of it have transformed the problem of energy planning into a more complex task with a greater number of issues to be considered. Since the key issue is to reduce greenhouse effects, governments around the world have begun to make investments in renewable energy systems (e.g., hydro, wind, solar, and/or biomass power). The relatively high costs of renewable energy systems and the uncertain outlook of their rate of diffusion in the market make it difficult to heavily rely on them. The uncertain variations in production cost over time are especially challenging. To handle uncertainties, the concept of the learning rate was adopted in this study so as to compute the costs of energy systems in the future and Monte Carlo simulation was performed. The aim of this study was to optimize plans of conventional and prospective renewable energy systems with respect to production cost. The production cost included capital, fixed, variable, and external costs. For the case study, the energy situation in South Korea was used. The results of the case study where the proposed methodology was applied could provide useful insights economically and strategies of sustainable energy management for ambiguous environments. -- Highlights: ► We propose energy planning method for sustainability. ► We consider uncertainties such as learning rate, fuel prices, and CO 2 prices. ► We consider the possibility of CO 2 trading. ► The proposed method is applied to South Korea case. ► The added capacities of energy systems depend on uncertainties.

Uncertainties and quantification of common cause failure rates and probabilities for system analyses

International Nuclear Information System (INIS)

Vaurio, Jussi K.

2005-01-01

Simultaneous failures of multiple components due to common causes at random times are modelled by constant multiple-failure rates. A procedure is described for quantification of common cause failure (CCF) basic event probabilities for system models using plant-specific and multiple-plant failure-event data. Methodology is presented for estimating CCF-rates from event data contaminated with assessment uncertainties. Generalised impact vectors determine the moments for the rates of individual systems or plants. These moments determine the effective numbers of events and observation times to be input to a Bayesian formalism to obtain plant-specific posterior CCF-rates. The rates are used to determine plant-specific common cause event probabilities for the basic events of explicit fault tree models depending on test intervals, test schedules and repair policies. Three methods are presented to determine these probabilities such that the correct time-average system unavailability can be obtained with single fault tree quantification. Recommended numerical values are given and examples illustrate different aspects of the methodology

Self-optimized construction of transition rate matrices from accelerated atomistic simulations with Bayesian uncertainty quantification

Science.gov (United States)

Swinburne, Thomas D.; Perez, Danny

2018-05-01

A massively parallel method to build large transition rate matrices from temperature-accelerated molecular dynamics trajectories is presented. Bayesian Markov model analysis is used to estimate the expected residence time in the known state space, providing crucial uncertainty quantification for higher-scale simulation schemes such as kinetic Monte Carlo or cluster dynamics. The estimators are additionally used to optimize where exploration is performed and the degree of temperature acceleration on the fly, giving an autonomous, optimal procedure to explore the state space of complex systems. The method is tested against exactly solvable models and used to explore the dynamics of C15 interstitial defects in iron. Our uncertainty quantification scheme allows for accurate modeling of the evolution of these defects over timescales of several seconds.

Determination of uncertainties in the calculation of dose rates at transport and storage casks; Unsicherheiten bei der Berechnung von Dosisleistungen an Transport- und Lagerbehaeltern

Energy Technology Data Exchange (ETDEWEB)

Schloemer, Luc Laurent Alexander

2014-12-17

The compliance with the dose rate limits for transport and storage casks (TLB) for spent nuclear fuel from pressurised water reactors can be proved by calculation. This includes the determination of the radioactive sources and the shielding-capability of the cask. In this thesis the entire computational chain, which extends from the determination of the source terms to the final Monte-Carlo-transport-calculation is analysed and the arising uncertainties are quantified not only by benchmarks but also by variational calculi. The background of these analyses is that the comparison with measured dose rates at different TLBs shows an overestimation by the values calculated. Regarding the studies performed, the overestimation can be mainly explained by the detector characteristics for the measurement of the neutron dose rate and additionally in case of the gamma dose rates by the energy group structure, which the calculation is based on. It turns out that the consideration of the uncertainties occurring along the computational chain can lead to even greater overestimation. Concerning the dose rate calculation at cask loadings with spent uranium fuel assemblies an uncertainty of (({sup +21}{sub -28}) ±2) % (rel.) for the total gamma dose rate and of ({sup +28±23}{sub -55±4}) % (rel.) for the total neutron dose rate are estimated. For mixed-loadings with spent uranium and MOX fuel assemblies an uncertainty of ({sup +24±3}{sub -27±2}) % (rel.) for the total gamma dose rate and of ({sup +28±23}{sub -55±4}) % (rel.) for the total neutron dose rate are quantified. The results show that the computational chain has not to be modified, because the calculations performed lead to conservative dose rate predictions, even if high uncertainties at neutron dose rate measurements arise. Thus at first the uncertainties of the neutron dose rate measurement have to be decreased to enable a reduction of the overestimation of the calculated dose rate afterwards. In the present thesis

Uncertainty in oil projects

International Nuclear Information System (INIS)

Limperopoulos, G.J.

1995-01-01

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

Low-sampling-rate ultra-wideband channel estimation using a bounded-data-uncertainty approach

KAUST Repository

Ballal, Tarig

2014-01-01

This paper proposes a low-sampling-rate scheme for ultra-wideband channel estimation. In the proposed scheme, P pulses are transmitted to produce P observations. These observations are exploited to produce channel impulse response estimates at a desired sampling rate, while the ADC operates at a rate that is P times less. To avoid loss of fidelity, the interpulse interval, given in units of sampling periods of the desired rate, is restricted to be co-prime with P. This condition is affected when clock drift is present and the transmitted pulse locations change. To handle this situation and to achieve good performance without using prior information, we derive an improved estimator based on the bounded data uncertainty (BDU) model. This estimator is shown to be related to the Bayesian linear minimum mean squared error (LMMSE) estimator. The performance of the proposed sub-sampling scheme was tested in conjunction with the new estimator. It is shown that high reduction in sampling rate can be achieved. The proposed estimator outperforms the least squares estimator in most cases; while in the high SNR regime, it also outperforms the LMMSE estimator. © 2014 IEEE.

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

Science.gov (United States)

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

2017-11-01

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

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

International Nuclear Information System (INIS)

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

2017-01-01

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

Exchange Rate Volatility, Inflation Uncertainty and Foreign Direct ...

African Journals Online (AJOL)

2008-10-07

Oct 7, 2008 ... volatility on foreign direct investment (FDI) inflows is important for a developing ... and inflation uncertainty were computed using the GARCH model and the results showed that volatility .... of currency and capital accounts, coupled with stable macroeconomic environment ..... 14.67561 Akaike info criterion.

Evaluation Procedures of Random Uncertainties in Theoretical Calculations of Cross Sections and Rate Coefficients

International Nuclear Information System (INIS)

Kokoouline, V.; Richardson, W.

2014-01-01

Uncertainties in theoretical calculations may include: • Systematic uncertainty: Due to applicability limits of the chosen model. • Random: Within a model, uncertainties of model parameters result in uncertainties of final results (such as cross sections). • If uncertainties of experimental and theoretical data are known, for the purpose of data evaluation (to produce recommended data), one should combine two data sets to produce the best guess data with the smallest possible uncertainty. In many situations, it is possible to assess the accuracy of theoretical calculations because theoretical models usually rely on parameters that are uncertain, but not completely random, i.e. the uncertainties of the parameters of the models are approximately known. If there are one or several such parameters with corresponding uncertainties, even if some or all parameters are correlated, the above approach gives a conceptually simple way to calculate uncertainties of final cross sections (uncertainty propagation). Numerically, the statistical approach to the uncertainty propagation could be computationally expensive. However, in situations, where uncertainties are considered to be as important as the actual cross sections (for data validation or benchmark calculations, for example), such a numerical effort is justified. Having data from different sources (say, from theory and experiment), a systematic statistical approach allows one to compare the data and produce “unbiased” evaluated data with improved uncertainties, if uncertainties of initial data from different sources are available. Without uncertainties, the data evaluation/validation becomes impossible. This is the reason why theoreticians should assess the accuracy of their calculations in one way or another. A statistical and systematic approach, similar to the described above, is preferable.

Uncertainty in the learning rates of energy technologies. An experiment in a global multi-regional energy system model

International Nuclear Information System (INIS)

Rout, Ullash K.; Blesl, Markus; Fahl, Ulrich; Remme, Uwe; Voss, Alfred

2009-01-01

The diffusion of promising energy technologies in the market depends on their future energy production-cost development. When analyzing these technologies in an integrated assessment model using endogenous technological learning, the uncertainty in the assumed learning rates (LRs) plays a crucial role in the production-cost development and model outcomes. This study examines the uncertainty in LRs of some energy technologies under endogenous global learning implementation and presents a floor-cost modeling procedure to systematically regulate the uncertainty in LRs of energy technologies. The article narrates the difficulties of data assimilation, as compatible with mixed integer programming segmentations, and comprehensively presents the causes of uncertainty in LRs. This work is executed using a multi-regional and long-horizon energy system model based on 'TIMES' framework. All regions receive an economic advantage to learn in a common domain, and resource-ample regions obtain a marginal advantage for better exploitation of the learning technologies, due to a lower supply-side fuel-cost development. The lowest learning investment associated with the maximum LR mobilizes more deployment of the learning technologies. The uncertainty in LRs has an impact on the diffusion of energy technologies tested, and therefore this study scrutinizes the role of policy support for some of the technologies investigated. (author)

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 in hydrological signatures

Science.gov (United States)

McMillan, Hilary; Westerberg, Ida

2015-04-01

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

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)

Flood modelling : Parameterisation and inflow uncertainty

NARCIS (Netherlands)

Mukolwe, M.M.; Di Baldassarre, G.; Werner, M.; Solomatine, D.P.

2014-01-01

This paper presents an analysis of uncertainty in hydraulic modelling of floods, focusing on the inaccuracy caused by inflow errors and parameter uncertainty. In particular, the study develops a method to propagate the uncertainty induced by, firstly, application of a stage–discharge rating curve

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

Directory of Open Access Journals (Sweden)

Elise Payzan-LeNestour

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

Döviz Kuru Belirsizliğinin İhracata Etkisi : Türkiye Örneği = The Impact of Exchange Rate Uncertainty on Exports : the Case of Turkey

Directory of Open Access Journals (Sweden)

Orhan KARACA

2004-06-01

Full Text Available In this paper we examined the relationship between exchange rate uncertainty and exports in Turkey. Sample period of the study is 1981, May 1, the date Turkey introduced flexible exchange rate system after quiting fixed exchange rate system, and 2001, February 22 when exchange rates were left floating. The results of this study, in which quarterly data are used, indicate that exchange rate uncertainty affects exports negatively in Turkey. This finding is valid both for long-run and short-run.

Nuclear Physical Uncertainties in Modeling X-Ray Bursts

Science.gov (United States)

Regis, Eric; Amthor, A. Matthew

2017-09-01

Type I x-ray bursts occur when a neutron star accretes material from the surface of another star in a compact binary star system. For certain accretion rates and material compositions, much of the nuclear material is burned in short, explosive bursts. Using a one-dimensional stellar model, Kepler, and a comprehensive nuclear reaction rate library, ReacLib, we have simulated chains of type I x-ray bursts. Unfortunately, there are large remaining uncertainties in the nuclear reaction rates involved, since many of the isotopes reacting are unstable and have not yet been studied experimentally. Some individual reactions, when varied within their estimated uncertainty, alter the light curves dramatically. This limits our ability to understand the structure of the neutron star. Previous studies have looked at the effects of individual reaction rate uncertainties. We have applied a Monte Carlo method ``-simultaneously varying a set of reaction rates'' -in order to probe the expected uncertainty in x-ray burst behaviour due to the total uncertainty in all nuclear reaction rates. Furthermore, we aim to discover any nonlinear effects due to the coupling between different reaction rates. Early results show clear non-linear effects. This research was made possible by NSF-DUE Grant 1317446, BUScholars Program.

Assessing uncertainty and risk in exploited marine populations

International Nuclear Information System (INIS)

Fogarty, M.J.; Mayo, R.K.; O'Brien, L.; Serchuk, F.M.; Rosenberg, A.A.

1996-01-01

The assessment and management of exploited fish and invertebrate populations is subject to several types of uncertainty. This uncertainty translates into risk to the population in the development and implementation of fishery management advice. Here, we define risk as the probability that exploitation rates will exceed a threshold level where long term sustainability of the stock is threatened. We distinguish among several sources of error or uncertainty due to (a) stochasticity in demographic rates and processes, particularly in survival rates during the early fife stages; (b) measurement error resulting from sampling variation in the determination of population parameters or in model estimation; and (c) the lack of complete information on population and ecosystem dynamics. The first represents a form of aleatory uncertainty while the latter two factors represent forms of epistemic uncertainty. To illustrate these points, we evaluate the recent status of the Georges Bank cod stock in a risk assessment framework. Short term stochastic projections are made accounting for uncertainty in population size and for random variability in the number of young surviving to enter the fishery. We show that recent declines in this cod stock can be attributed to exploitation rates that have substantially exceeded sustainable levels

The impact of (n, γ) reaction rate uncertainties of unstable isotopes near N = 50 on the i-process nucleosynthesis in He-shell flash white dwarfs

Science.gov (United States)

Denissenkov, Pavel; Perdikakis, Georgios; Herwig, Falk; Schatz, Hendrik; Ritter, Christian; Pignatari, Marco; Jones, Samuel; Nikas, Stylianos; Spyrou, Artemis

2018-05-01

The first-peak s-process elements Rb, Sr, Y and Zr in the post-AGB star Sakurai's object (V4334 Sagittarii) have been proposed to be the result of i-process nucleosynthesis in a post-AGB very-late thermal pulse event. We estimate the nuclear physics uncertainties in the i-process model predictions to determine whether the remaining discrepancies with observations are significant and point to potential issues with the underlying astrophysical model. We find that the dominant source in the nuclear physics uncertainties are predictions of neutron capture rates on unstable neutron rich nuclei, which can have uncertainties of more than a factor 20 in the band of the i-process. We use a Monte Carlo variation of 52 neutron capture rates and a 1D multi-zone post-processing model for the i-process in Sakurai's object to determine the cumulative effect of these uncertainties on the final elemental abundance predictions. We find that the nuclear physics uncertainties are large and comparable to observational errors. Within these uncertainties the model predictions are consistent with observations. A correlation analysis of the results of our MC simulations reveals that the strongest impact on the predicted abundances of Rb, Sr, Y and Zr is made by the uncertainties in the (n, γ) reaction rates of 85Br, 86Br, 87Kr, 88Kr, 89Kr, 89Rb, 89Sr, and 92Sr. This conclusion is supported by a series of multi-zone simulations in which we increased and decreased to their maximum and minimum limits one or two reaction rates per run. We also show that simple and fast one-zone simulations should not be used instead of more realistic multi-zone stellar simulations for nuclear sensitivity and uncertainty studies of convective–reactive processes. Our findings apply more generally to any i-process site with similar neutron exposure, such as rapidly accreting white dwarfs with near-solar metallicities.

Deterministic uncertainty analysis

International Nuclear Information System (INIS)

Worley, B.A.

1987-12-01

This paper presents a deterministic uncertainty analysis (DUA) method for calculating uncertainties that has the potential to significantly reduce the number of computer runs compared to conventional statistical analysis. The method is based upon the availability of derivative and sensitivity data such as that calculated using the well known direct or adjoint sensitivity analysis techniques. Formation of response surfaces using derivative data and the propagation of input probability distributions are discussed relative to their role in the DUA method. A sample problem that models the flow of water through a borehole is used as a basis to compare the cumulative distribution function of the flow rate as calculated by the standard statistical methods and the DUA method. Propogation of uncertainties by the DUA method is compared for ten cases in which the number of reference model runs was varied from one to ten. The DUA method gives a more accurate representation of the true cumulative distribution of the flow rate based upon as few as two model executions compared to fifty model executions using a statistical approach. 16 refs., 4 figs., 5 tabs

Uncertainty Evaluation of the New Setup for Measurement of Water-Vapor Permeation Rate by a Dew-Point Sensor

Science.gov (United States)

Hudoklin, D.; Šetina, J.; Drnovšek, J.

2012-09-01

The measurement of the water-vapor permeation rate (WVPR) through materials is very important in many industrial applications such as the development of new fabrics and construction materials, in the semiconductor industry, packaging, vacuum techniques, etc. The demand for this kind of measurement grows considerably and thus many different methods for measuring the WVPR are developed and standardized within numerous national and international standards. However, comparison of existing methods shows a low level of mutual agreement. The objective of this paper is to demonstrate the necessary uncertainty evaluation for WVPR measurements, so as to provide a basis for development of a corresponding reference measurement standard. This paper presents a specially developed measurement setup, which employs a precision dew-point sensor for WVPR measurements on specimens of different shapes. The paper also presents a physical model, which tries to account for both dynamic and quasi-static methods, the common types of WVPR measurements referred to in standards and scientific publications. An uncertainty evaluation carried out according to the ISO/IEC guide to the expression of uncertainty in measurement (GUM) shows the relative expanded ( k = 2) uncertainty to be 3.0 % for WVPR of 6.71 mg . h-1 (corresponding to permeance of 30.4 mg . m-2. day-1 . hPa-1).

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

International Nuclear Information System (INIS)

Fenwick, John D.; Nahum, Alan E.

2001-01-01

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

Uncertainty in river discharge observations: a quantitative analysis

Directory of Open Access Journals (Sweden)

G. Di Baldassarre

2009-06-01

Full Text Available This study proposes a framework for analysing and quantifying the uncertainty of river flow data. Such uncertainty is often considered to be negligible with respect to other approximations affecting hydrological studies. Actually, given that river discharge data are usually obtained by means of the so-called rating curve method, a number of different sources of error affect the derived observations. These include: errors in measurements of river stage and discharge utilised to parameterise the rating curve, interpolation and extrapolation error of the rating curve, presence of unsteady flow conditions, and seasonal variations of the state of the vegetation (i.e. roughness. This study aims at analysing these sources of uncertainty using an original methodology. The novelty of the proposed framework lies in the estimation of rating curve uncertainty, which is based on hydraulic simulations. These latter are carried out on a reach of the Po River (Italy by means of a one-dimensional (1-D hydraulic model code (HEC-RAS. The results of the study show that errors in river flow data are indeed far from negligible.

Comparison of the uncertainties of several European low-dose calibration facilities

Science.gov (United States)

Dombrowski, H.; Cornejo Díaz, N. A.; Toni, M. P.; Mihelic, M.; Röttger, A.

2018-04-01

The typical uncertainty of a low-dose rate calibration of a detector, which is calibrated in a dedicated secondary national calibration laboratory, is investigated, including measurements in the photon field of metrology institutes. Calibrations at low ambient dose equivalent rates (at the level of the natural ambient radiation) are needed when environmental radiation monitors are to be characterised. The uncertainties of calibration measurements in conventional irradiation facilities above ground are compared with those obtained in a low-dose rate irradiation facility located deep underground. Four laboratories quantitatively evaluated the uncertainties of their calibration facilities, in particular for calibrations at low dose rates (250 nSv/h and 1 μSv/h). For the first time, typical uncertainties of European calibration facilities are documented in a comparison and the main sources of uncertainty are revealed. All sources of uncertainties are analysed, including the irradiation geometry, scattering, deviations of real spectra from standardised spectra, etc. As a fundamental metrological consequence, no instrument calibrated in such a facility can have a lower total uncertainty in subsequent measurements. For the first time, the need to perform calibrations at very low dose rates (< 100 nSv/h) deep underground is underpinned on the basis of quantitative data.

Uncertainty in hydrological signatures for gauged and ungauged catchments

Science.gov (United States)

Westerberg, Ida K.; Wagener, Thorsten; Coxon, Gemma; McMillan, Hilary K.; Castellarin, Attilio; Montanari, Alberto; Freer, Jim

2016-03-01

Reliable information about hydrological behavior is needed for water-resource management and scientific investigations. Hydrological signatures quantify catchment behavior as index values, and can be predicted for ungauged catchments using a regionalization procedure. The prediction reliability is affected by data uncertainties for the gauged catchments used in prediction and by uncertainties in the regionalization procedure. We quantified signature uncertainty stemming from discharge data uncertainty for 43 UK catchments and propagated these uncertainties in signature regionalization, while accounting for regionalization uncertainty with a weighted-pooling-group approach. Discharge uncertainty was estimated using Monte Carlo sampling of multiple feasible rating curves. For each sampled rating curve, a discharge time series was calculated and used in deriving the gauged signature uncertainty distribution. We found that the gauged uncertainty varied with signature type, local measurement conditions and catchment behavior, with the highest uncertainties (median relative uncertainty ±30-40% across all catchments) for signatures measuring high- and low-flow magnitude and dynamics. Our regionalization method allowed assessing the role and relative magnitudes of the gauged and regionalized uncertainty sources in shaping the signature uncertainty distributions predicted for catchments treated as ungauged. We found that (1) if the gauged uncertainties were neglected there was a clear risk of overconditioning the regionalization inference, e.g., by attributing catchment differences resulting from gauged uncertainty to differences in catchment behavior, and (2) uncertainty in the regionalization results was lower for signatures measuring flow distribution (e.g., mean flow) than flow dynamics (e.g., autocorrelation), and for average flows (and then high flows) compared to low flows.

Uncertainties in the Anti-neutrino Production at Nuclear Reactors

Energy Technology Data Exchange (ETDEWEB)

Djurcic, Zelimir; Detwiler, Jason A.; Piepke, Andreas; Foster Jr., Vince R.; Miller, Lester; Gratta, Giorgio

2008-08-06

Anti-neutrino emission rates from nuclear reactors are determined from thermal power measurements and fission rate calculations. The uncertainties in these quantities for commercial power plants and their impact on the calculated interaction rates in {bar {nu}}{sub e} detectors is examined. We discuss reactor-to-reactor correlations between the leading uncertainties, and their relevance to reactor {bar {nu}}{sub e} experiments.

Evaluating release alternatives for a long-lived bird species under uncertainty about long-term demographic rates

Science.gov (United States)

Moore, Clinton T.; Converse, Sarah J.; Folk, Martin J.; Runge, Michael C.; Nesbitt, Stephen A.

2012-01-01

The release of animals to reestablish an extirpated population is a decision problem that is often attended by considerable uncertainty about the probability of success. Annual releases of captive-reared juvenile Whooping Cranes (Grus americana) were begun in 1993 in central Florida, USA, to establish a breeding, non-migratory population. Over a 12-year period, 286 birds were released, but by 2004, the introduced flock had produced only four wild-fledged birds. Consequently, releases were halted over managers' concerns about the performance of the released flock and uncertainty about the efficacy of further releases. We used data on marked, released birds to develop predictive models for addressing whether releases should be resumed, and if so, under what schedule. To examine the outcome of different release scenarios, we simulated the survival and productivity of individual female birds under a baseline model that recognized age and breeding-class structure and which incorporated empirically estimated stochastic elements. As data on wild-fledged birds from captive-reared parents were sparse, a key uncertainty that confronts release decision-making is whether captive-reared birds and their offspring share the same vital rates. Therefore, we used data on the only population of wild Whooping Cranes in existence to construct two alternatives to the baseline model. The probability of population persistence was highly sensitive to the choice of these three models. Under the baseline model, extirpation of the population was nearly certain under any scenario of resumed releases. In contrast, the model based on estimates from wild birds projected a high probability of persistence under any release scenario, including cessation of releases. Therefore, belief in either of these models suggests that further releases are an ineffective use of resources. In the third model, which simulated a population Allee effect, population persistence was sensitive to the release decision

Assessing flood forecast uncertainty with fuzzy arithmetic

Directory of Open Access Journals (Sweden)

de Bruyn Bertrand

2016-01-01

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

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

Helium Mass Spectrometer Leak Detection: A Method to Quantify Total Measurement Uncertainty

Science.gov (United States)

Mather, Janice L.; Taylor, Shawn C.

2015-01-01

In applications where leak rates of components or systems are evaluated against a leak rate requirement, the uncertainty of the measured leak rate must be included in the reported result. However, in the helium mass spectrometer leak detection method, the sensitivity, or resolution, of the instrument is often the only component of the total measurement uncertainty noted when reporting results. To address this shortfall, a measurement uncertainty analysis method was developed that includes the leak detector unit's resolution, repeatability, hysteresis, and drift, along with the uncertainty associated with the calibration standard. In a step-wise process, the method identifies the bias and precision components of the calibration standard, the measurement correction factor (K-factor), and the leak detector unit. Together these individual contributions to error are combined and the total measurement uncertainty is determined using the root-sum-square method. It was found that the precision component contributes more to the total uncertainty than the bias component, but the bias component is not insignificant. For helium mass spectrometer leak rate tests where unit sensitivity alone is not enough, a thorough evaluation of the measurement uncertainty such as the one presented herein should be performed and reported along with the leak rate value.

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

Capital flight and the uncertainty of government policies

NARCIS (Netherlands)

Hermes, N.; Lensink, R.

2000-01-01

This paper shows that policy uncertainty, measured by the uncertainty of budget deficits, tax payments, government consumption and the inflation rate, has a statistically significant positive impact on capital flight. This result remains robust after having applied stability tests.

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

Investment Timing and Capacity Choice under Uncertainty

Directory of Open Access Journals (Sweden)

Xiumei Lv

2014-01-01

leader under greater uncertainty. Furthermore, both firms will provide more outputs in the face of increasing uncertainty and the growth rate of the follower’s capacity will exceed that of the leader’s. In addition, this paper finds that the follower will end up with a larger capacity than the leader.

Capital flight and the uncertainty of government policies

NARCIS (Netherlands)

Hermes, C.L.M.; Lensink, B.W.

This paper shows that policy uncertainty, measured by the uncertainty of budget deficits, tart payments, government consumption and the inflation rate, has a statistically significant positive impact on capital flight. This result remains robust after having applied stability tests. (C) 2001

Estimates of Uncertainty around the RBA's Forecasts

OpenAIRE

Peter Tulip; Stephanie Wallace

2012-01-01

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

The cost of uncertainty in capacity expansion problems

Energy Technology Data Exchange (ETDEWEB)

Jenhung Wang [National Chung Cheng Univ., Dept. of Business Administration, Chia-Yi (Taiwan); Sparrow, F.T. [Purdue Univ., School of Industrial Engineering, West Lafayette, IN (United States)

1999-07-01

The goals of this paper are to present a two-stage programming model of the capacity expansion problem under uncertainty of demand and explore the impact of the uncertainty on cost. The model is a mixed integer nonlinear programming (MINLP) model with the consideration of uncertainty used to maximise the expected presented value of utility profits over the planning horizon, under the constraints of rate of return and reserve margin regulation. The results reveal that the uncertainty harms the profit seriously. In this paper both microeconomics and mathematical programming are used to analyse the problem. We try to observe the economic behaviour of the utility with uncertainty involved. We also investigate the influence on the cost of uncertainty of each economic parameter. (Author)

Model Uncertainty and Exchange Rate Forecasting

NARCIS (Netherlands)

Kouwenberg, R.; Markiewicz, A.; Verhoeks, R.; Zwinkels, R.C.J.

2017-01-01

Exchange rate models with uncertain and incomplete information predict that investors focus on a small set of fundamentals that changes frequently over time. We design a model selection rule that captures the current set of fundamentals that best predicts the exchange rate. Out-of-sample tests show

Model Uncertainty and Exchange Rate Forecasting

NARCIS (Netherlands)

R.R.P. Kouwenberg (Roy); A. Markiewicz (Agnieszka); R. Verhoeks (Ralph); R.C.J. Zwinkels (Remco)

2013-01-01

textabstractWe propose a theoretical framework of exchange rate behavior where investors focus on a subset of economic fundamentals. We find that any adjustment in the set of predictors used by investors leads to changes in the relation between the exchange rate and fundamentals. We test the

Measurement uncertainty budget of an interferometric flow velocity sensor

Science.gov (United States)

Bermuske, Mike; Büttner, Lars; Czarske, Jürgen

2017-06-01

Flow rate measurements are a common topic for process monitoring in chemical engineering and food industry. To achieve the requested low uncertainties of 0:1% for flow rate measurements, a precise measurement of the shear layers of such flows is necessary. The Laser Doppler Velocimeter (LDV) is an established method for measuring local flow velocities. For exact estimation of the flow rate, the flow profile in the shear layer is of importance. For standard LDV the axial resolution and therefore the number of measurement points in the shear layer is defined by the length of the measurement volume. A decrease of this length is accompanied by a larger fringe distance variation along the measurement axis which results in a rise of the measurement uncertainty for the flow velocity (uncertainty relation between spatial resolution and velocity uncertainty). As a unique advantage, the laser Doppler profile sensor (LDV-PS) overcomes this problem by using two fan-like fringe systems to obtain the position of the measured particles along the measurement axis and therefore achieve a high spatial resolution while it still offers a low velocity uncertainty. With this technique, the flow rate can be estimated with one order of magnitude lower uncertainty, down to 0:05% statistical uncertainty.1 And flow profiles especially in film flows can be measured more accurately. The problem for this technique is, in contrast to laboratory setups where the system is quite stable, that for industrial applications the sensor needs a reliable and robust traceability to the SI units, meter and second. Small deviations in the calibration can, because of the highly position depending calibration function, cause large systematic errors in the measurement result. Therefore, a simple, stable and accurate tool is needed, that can easily be used in industrial surroundings to check or recalibrate the sensor. In this work, different calibration methods are presented and their influences to the

Uncertainty in Forest Net Present Value Estimations

Directory of Open Access Journals (Sweden)

Ilona Pietilä

2010-09-01

Full Text Available Uncertainty related to inventory data, growth models and timber price fluctuation was investigated in the assessment of forest property net present value (NPV. The degree of uncertainty associated with inventory data was obtained from previous area-based airborne laser scanning (ALS inventory studies. The study was performed, applying the Monte Carlo simulation, using stand-level growth and yield projection models and three alternative rates of interest (3, 4 and 5%. Timber price fluctuation was portrayed with geometric mean-reverting (GMR price models. The analysis was conducted for four alternative forest properties having varying compartment structures: (A a property having an even development class distribution, (B sapling stands, (C young thinning stands, and (D mature stands. Simulations resulted in predicted yield value (predicted NPV distributions at both stand and property levels. Our results showed that ALS inventory errors were the most prominent source of uncertainty, leading to a 5.1–7.5% relative deviation of property-level NPV when an interest rate of 3% was applied. Interestingly, ALS inventory led to significant biases at the property level, ranging from 8.9% to 14.1% (3% interest rate. ALS inventory-based bias was the most significant in mature stand properties. Errors related to the growth predictions led to a relative standard deviation in NPV, varying from 1.5% to 4.1%. Growth model-related uncertainty was most significant in sapling stand properties. Timber price fluctuation caused the relative standard deviations ranged from 3.4% to 6.4% (3% interest rate. The combined relative variation caused by inventory errors, growth model errors and timber price fluctuation varied, depending on the property type and applied rates of interest, from 6.4% to 12.6%. By applying the methodology described here, one may take into account the effects of various uncertainty factors in the prediction of forest yield value and to supply the

Uncertainty Propagation in Monte Carlo Depletion Analysis

International Nuclear Information System (INIS)

Shim, Hyung Jin; Kim, Yeong-il; Park, Ho Jin; Joo, Han Gyu; Kim, Chang Hyo

2008-01-01

A new formulation aimed at quantifying uncertainties of Monte Carlo (MC) tallies such as k eff and the microscopic reaction rates of nuclides and nuclide number densities in MC depletion analysis and examining their propagation behaviour as a function of depletion time step (DTS) is presented. It is shown that the variance of a given MC tally used as a measure of its uncertainty in this formulation arises from four sources; the statistical uncertainty of the MC tally, uncertainties of microscopic cross sections and nuclide number densities, and the cross correlations between them and the contribution of the latter three sources can be determined by computing the correlation coefficients between the uncertain variables. It is also shown that the variance of any given nuclide number density at the end of each DTS stems from uncertainties of the nuclide number densities (NND) and microscopic reaction rates (MRR) of nuclides at the beginning of each DTS and they are determined by computing correlation coefficients between these two uncertain variables. To test the viability of the formulation, we conducted MC depletion analysis for two sample depletion problems involving a simplified 7x7 fuel assembly (FA) and a 17x17 PWR FA, determined number densities of uranium and plutonium isotopes and their variances as well as k ∞ and its variance as a function of DTS, and demonstrated the applicability of the new formulation for uncertainty propagation analysis that need be followed in MC depletion computations. (authors)

Corporate income taxation uncertainty and foreign direct investment

OpenAIRE

Zagler, Martin; Zanzottera, Cristiana

2012-01-01

This paper analyzes the effects of legal uncertainty around corporate income taxation on foreign direct investment (FDI). Legal uncertainty can take many forms: double tax agreements, different types of legal systems and corruption. We test the effect of legal uncertainty on foreign direct investment with an international panel. We find that an increase in the ratio of the statutory corporate income tax rate of the destination relative to the source country exhibits a negati...

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.

Metallicity-Dependent Isotopic Abundances and the Impact of Helium Rate Uncertainties in Massive Stars

Science.gov (United States)

West, Christopher

2013-03-01

model compared to the linear interpolation method, for the six s--only isotopes along the weak s--process path. As a second project, we study the sensitivity of presupernova evolution and supernova nucleosynthesis yields of massive stars to variations of the helium-burning reaction rates within the range of their uncertainties. The current solar abundances from Lodders (2010) are used for the initial stellar composition. We compute a grid of 12 initial stellar masses and 176 models per stellar mass to explore the effects of independently varying the 12C(alpha,gamma)16O and 3alpha reaction rates, denoted Ralpha,12 and R3alpha, respectively. The production factors of both the intermediate-mass elements (A=16--40) and the s--only isotopes along the weak s--process path ( 70Ge, 76Se, 80Kr, 82Kr, 86Sr, and 87Sr) were found to be in reasonable agreement with predictions for variations of R3alpha and Ralpha,12 of +/-25%; the s--only isotopes, however, tend to favor higher values of R3alpha than the intermediate-mass isotopes. The experimental uncertainty (one standard deviation) in R3alpha(Ralpha,12 ) is approximately +/-10%(+/-25%). The results show that a more accurate measurement of one of these rates would decrease the uncertainty in the other as inferred from the present calculations. We also observe sharp changes in production factors and standard deviations for small changes in the reaction rates, due to differences in the convection structure of the star. The compactness parameter was used to assess which models would likely explode as successful supernovae, and hence contribute explosive nucleosynthesis yields. We also provide the approximate remnant masses for each model and the carbon mass fractions at the end of core-helium burning as a key parameter for later evolution stages.

Sediment Curve Uncertainty Estimation Using GLUE and Bootstrap Methods

Directory of Open Access Journals (Sweden)

aboalhasan fathabadi

2017-02-01

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

Uncertainty associated with the gravimetric measurement of particulate matter concentration in ambient air.

Science.gov (United States)

Lacey, Ronald E; Faulkner, William Brock

2015-07-01

This work applied a propagation of uncertainty method to typical total suspended particulate (TSP) sampling apparatus in order to estimate the overall measurement uncertainty. The objectives of this study were to estimate the uncertainty for three TSP samplers, develop an uncertainty budget, and determine the sensitivity of the total uncertainty to environmental parameters. The samplers evaluated were the TAMU High Volume TSP Sampler at a nominal volumetric flow rate of 1.42 m3 min(-1) (50 CFM), the TAMU Low Volume TSP Sampler at a nominal volumetric flow rate of 17 L min(-1) (0.6 CFM) and the EPA TSP Sampler at the nominal volumetric flow rates of 1.1 and 1.7 m3 min(-1) (39 and 60 CFM). Under nominal operating conditions the overall measurement uncertainty was found to vary from 6.1x10(-6) g m(-3) to 18.0x10(-6) g m(-3), which represented an uncertainty of 1.7% to 5.2% of the measurement. Analysis of the uncertainty budget determined that three of the instrument parameters contributed significantly to the overall uncertainty: the uncertainty in the pressure drop measurement across the orifice meter during both calibration and testing and the uncertainty of the airflow standard used during calibration of the orifice meter. Five environmental parameters occurring during field measurements were considered for their effect on overall uncertainty: ambient TSP concentration, volumetric airflow rate, ambient temperature, ambient pressure, and ambient relative humidity. Of these, only ambient TSP concentration and volumetric airflow rate were found to have a strong effect on the overall uncertainty. The technique described in this paper can be applied to other measurement systems and is especially useful where there are no methods available to generate these values empirically. This work addresses measurement uncertainty of TSP samplers used in ambient conditions. Estimation of uncertainty in gravimetric measurements is of particular interest, since as ambient particulate

Treatment of uncertainties in the geologic disposal of radioactive waste

International Nuclear Information System (INIS)

Cranwell, R.M.

1985-01-01

Uncertainty in the analysis of geologic waste disposal is generally considered to have three primary components: (1) computer code/model uncertainty, (2) model parameter uncertainty, and (3) scenario uncertainty. Computer code/model uncertainty arises from problems associated with determination of appropriate parameters for use in model construction, mathematical formulatin of models, and numerical techniques used in conjunction with the mathematical formulation of models. Model parameter uncertainty arises from problems associated with selection of appropriate values for model input, data interpretation and possible misuse of data, and variation of data. Scenario uncertainty arises from problems associated with the ''completeness' of scenarios, the definition of parameters which describe scenarios, and the rate or probability of scenario occurrence. The preceding sources of uncertainty are discussed below

A sensitivity study of s-process: the impact of uncertainties from nuclear reaction rates

Science.gov (United States)

Vinyoles, N.; Serenelli, A.

2016-01-01

The slow neutron capture process (s-process) is responsible for the production of about half the elements beyond the Fe-peak. The production sites and the conditions under which the different components of s-process occur are relatively well established. A detailed quantitative understanding of s-process nucleosynthesis may yield light in physical processes, e.g. convection and mixing, taking place in the production sites. For this, it is important that the impact of uncertainties in the nuclear physics is well understood. In this work we perform a study of the sensitivity of s-process nucleosynthesis, with particular emphasis in the main component, on the nuclear reaction rates. Our aims are: to quantify the current uncertainties in the production factors of s-process elements originating from nuclear physics and, to identify key nuclear reactions that require more precise experimental determinations. In this work we studied two different production sites in which s-process occurs with very different neutron exposures: 1) a low-mass extremely metal-poor star during the He-core flash (nn reaching up to values of ∼ 1014cm-3); 2) the TP-AGB phase of a M⊙, Z=0.01 model, the typical site of the main s-process component (nn up to 108 — 109cm-3). In the first case, the main variation in the production of s-process elements comes from the neutron poisons and with relative variations around 30%-50%. In the second, the neutron poison are not as important because of the higher metallicity of the star that actually acts as a seed and therefore, the final error of the abundances are much lower around 10%-25%.

Cross Section Measurements of the Reaction 23Na(p, γ)24Mg

Science.gov (United States)

Boeltzig, Axel; Deboer, Richard James; Macon, Kevin; Wiescher, Michael; Best, Andreas; Imbriani, Gianluca; Gyürky, György; Strieder, Frank

2017-09-01

The reaction 23Na(p, γ)24Mg can provide a link from the NeNa to the MgAl cycle in stellar burning and is therefore of interest in nuclear astrophysics. To determine the reaction rates at stellar temperatures, new cross section measurements at low proton energies have been performed recently, and further experiments are underway. The current cross section data implies that the reaction rate up to temperatures of 1 GK is determined by a few narrow resonances and direct capture. Complementary to these experimental efforts at low proton energies, cross section measurements at higher energies can help to constrain the direct capture and broad resonance contributions to the cross section and reduce the uncertainty of the extrapolation towards stellar energies. In this paper we report an experiment to measure the 23Na(p, γ)24Mg cross section with a solid target setup at the St. ANA 5U accelerator at the University of Notre Dame. The experiment and the current status of data analysis will be described. This work benefited from support by the National Science Foundation under Grant No. PHY-1430152 (JINA-CEE), the Nuclear Science Laboratory (NSL), the Istituto Nazionale di Fisica Nucleare (INFN), and the Gran Sasso Science Institute (GSSI).

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...

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.

Structural and parameteric uncertainty quantification in cloud microphysics parameterization schemes

Science.gov (United States)

van Lier-Walqui, M.; Morrison, H.; Kumjian, M. R.; Prat, O. P.; Martinkus, C.

2017-12-01

Atmospheric model parameterization schemes employ approximations to represent the effects of unresolved processes. These approximations are a source of error in forecasts, caused in part by considerable uncertainty about the optimal value of parameters within each scheme -- parameteric uncertainty. Furthermore, there is uncertainty regarding the best choice of the overarching structure of the parameterization scheme -- structrual uncertainty. Parameter estimation can constrain the first, but may struggle with the second because structural choices are typically discrete. We address this problem in the context of cloud microphysics parameterization schemes by creating a flexible framework wherein structural and parametric uncertainties can be simultaneously constrained. Our scheme makes no assuptions about drop size distribution shape or the functional form of parametrized process rate terms. Instead, these uncertainties are constrained by observations using a Markov Chain Monte Carlo sampler within a Bayesian inference framework. Our scheme, the Bayesian Observationally-constrained Statistical-physical Scheme (BOSS), has flexibility to predict various sets of prognostic drop size distribution moments as well as varying complexity of process rate formulations. We compare idealized probabilistic forecasts from versions of BOSS with varying levels of structural complexity. This work has applications in ensemble forecasts with model physics uncertainty, data assimilation, and cloud microphysics process studies.

Predictive uncertainty in auditory sequence processing

Directory of Open Access Journals (Sweden)

Niels Chr. eHansen

2014-09-01

Full Text Available Previous studies of auditory expectation have focused on the expectedness perceived by listeners retrospectively in response to events. In contrast, this research examines predictive uncertainty - a property of listeners’ prospective state of expectation prior to the onset of an event. We examine the information-theoretic concept of Shannon entropy as a model of predictive uncertainty in music cognition. This is motivated by the Statistical Learning Hypothesis, which proposes that schematic expectations reflect probabilistic relationships between sensory events learned implicitly through exposure.Using probability estimates from an unsupervised, variable-order Markov model, 12 melodic contexts high in entropy and 12 melodic contexts low in entropy were selected from two musical repertoires differing in structural complexity (simple and complex. Musicians and non-musicians listened to the stimuli and provided explicit judgments of perceived uncertainty (explicit uncertainty. We also examined an indirect measure of uncertainty computed as the entropy of expectedness distributions obtained using a classical probe-tone paradigm where listeners rated the perceived expectedness of the final note in a melodic sequence (inferred uncertainty. Finally, we simulate listeners’ perception of expectedness and uncertainty using computational models of auditory expectation. A detailed model comparison indicates which model parameters maximize fit to the data and how they compare to existing models in the literature.The results show that listeners experience greater uncertainty in high-entropy musical contexts than low-entropy contexts. This effect is particularly apparent for inferred uncertainty and is stronger in musicians than non-musicians. Consistent with the Statistical Learning Hypothesis, the results suggest that increased domain-relevant training is associated with an increasingly accurate cognitive model of probabilistic structure in music.

Predictive uncertainty in auditory sequence processing.

Science.gov (United States)

Hansen, Niels Chr; Pearce, Marcus T

2014-01-01

Previous studies of auditory expectation have focused on the expectedness perceived by listeners retrospectively in response to events. In contrast, this research examines predictive uncertainty-a property of listeners' prospective state of expectation prior to the onset of an event. We examine the information-theoretic concept of Shannon entropy as a model of predictive uncertainty in music cognition. This is motivated by the Statistical Learning Hypothesis, which proposes that schematic expectations reflect probabilistic relationships between sensory events learned implicitly through exposure. Using probability estimates from an unsupervised, variable-order Markov model, 12 melodic contexts high in entropy and 12 melodic contexts low in entropy were selected from two musical repertoires differing in structural complexity (simple and complex). Musicians and non-musicians listened to the stimuli and provided explicit judgments of perceived uncertainty (explicit uncertainty). We also examined an indirect measure of uncertainty computed as the entropy of expectedness distributions obtained using a classical probe-tone paradigm where listeners rated the perceived expectedness of the final note in a melodic sequence (inferred uncertainty). Finally, we simulate listeners' perception of expectedness and uncertainty using computational models of auditory expectation. A detailed model comparison indicates which model parameters maximize fit to the data and how they compare to existing models in the literature. The results show that listeners experience greater uncertainty in high-entropy musical contexts than low-entropy contexts. This effect is particularly apparent for inferred uncertainty and is stronger in musicians than non-musicians. Consistent with the Statistical Learning Hypothesis, the results suggest that increased domain-relevant training is associated with an increasingly accurate cognitive model of probabilistic structure in music.

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

Science.gov (United States)

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

2017-08-01

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

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 analysis of power monitoring transit time ultrasonic flow meters

International Nuclear Information System (INIS)

Orosz, A.; Miller, D. W.; Christensen, R. N.; Arndt, S.

2006-01-01

A general uncertainty analysis is applied to chordal, transit time ultrasonic flow meters that are used in nuclear power plant feedwater loops. This investigation focuses on relationships between the major parameters of the flow measurement. For this study, mass flow rate is divided into three components, profile factor, density, and a form of volumetric flow rate. All system parameters are used to calculate values for these three components. Uncertainty is analyzed using a perturbation method. Sensitivity coefficients for major system parameters are shown, and these coefficients are applicable to a range of ultrasonic flow meters used in similar applications. Also shown is the uncertainty to be expected for density along with its relationship to other system uncertainties. One other conclusion is that pipe diameter sensitivity coefficients may be a function of the calibration technique used. (authors)

Understanding Interest Rate Volatility

OpenAIRE

Volker, Desi

2016-01-01

This thesis is the result of my Ph.D. studies at the Department of Finance of the Copenhagen Business School. It consists of three essays covering topics related to the term structure of interest rates, monetary policy and interest rate volatility. The rst essay, \\Monetary Policy Uncertainty and Interest Rates", examines the role of monetary policy uncertainty on the term structure of interest rates. The second essay, \\A Regime-Switching A ne Term Structure Model with Stochast...

Accounting for Epistemic Uncertainty in Mission Supportability Assessment: A Necessary Step in Understanding Risk and Logistics Requirements

Science.gov (United States)

Owens, Andrew; De Weck, Olivier L.; Stromgren, Chel; Goodliff, Kandyce; Cirillo, William

2017-01-01

Future crewed missions to Mars present a maintenance logistics challenge that is unprecedented in human spaceflight. Mission endurance – defined as the time between resupply opportunities – will be significantly longer than previous missions, and therefore logistics planning horizons are longer and the impact of uncertainty is magnified. Maintenance logistics forecasting typically assumes that component failure rates are deterministically known and uses them to represent aleatory uncertainty, or uncertainty that is inherent to the process being examined. However, failure rates cannot be directly measured; rather, they are estimated based on similarity to other components or statistical analysis of observed failures. As a result, epistemic uncertainty – that is, uncertainty in knowledge of the process – exists in failure rate estimates that must be accounted for. Analyses that neglect epistemic uncertainty tend to significantly underestimate risk. Epistemic uncertainty can be reduced via operational experience; for example, the International Space Station (ISS) failure rate estimates are refined using a Bayesian update process. However, design changes may re-introduce epistemic uncertainty. Thus, there is a tradeoff between changing a design to reduce failure rates and operating a fixed design to reduce uncertainty. This paper examines the impact of epistemic uncertainty on maintenance logistics requirements for future Mars missions, using data from the ISS Environmental Control and Life Support System (ECLS) as a baseline for a case study. Sensitivity analyses are performed to investigate the impact of variations in failure rate estimates and epistemic uncertainty on spares mass. The results of these analyses and their implications for future system design and mission planning are discussed.

Evaluation method for uncertainty of effective delayed neutron fraction βeff

International Nuclear Information System (INIS)

Zukeran, Atsushi

1999-01-01

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

Mind the rate. Why rate global climate change matters, and how much

International Nuclear Information System (INIS)

Ambrosi, Ph.

2006-01-01

To assess climate policies in a cost-efficiency framework with constraints on the magnitude and rate of global climate change we have built RESPONSE, an optimal control integrated assessment model. Our results show that the uncertainty about climate sensitivity leads to significant short-term mitigation efforts all the more as the arrival of information regarding this parameter is belated. There exists thus a high opportunity cost to know before 2030 the true value of this parameter, which is not totally granted so far. Given this uncertainty, a +2 deg C objective could lead to rather stringent policy recommendations for the coming decades and might prove unacceptable. Furthermore, the uncertainty about climate sensitivity magnifies the influence of the rate constraint on short-term decision, leading to rather stringent policy recommendations for the coming decades. This result is particularly robust to the choice of discount rate and to the beliefs of the decision-maker about climate sensitivity. We finally show that the uncertainty about the rate constraint is even more important for short-term decision than the uncertainty about climate sensitivity or magnitude of warming. This means that the critical rate of climate change, i.e. a transient characteristic of climate risks, matters much more than the long-term objective of climate policy, i.e. the critical magnitude of climate change. Therefore, research should be aimed at better characterising climate change risks in view to help decision-makers in agreeing on a safe guardrail to limit the rate of global warming. (author)

Propagation of uncertainty and sensitivity analysis in an integral oil-gas plume model

KAUST Repository

Wang, Shitao

2016-05-27

Polynomial Chaos expansions are used to analyze uncertainties in an integral oil-gas plume model simulating the Deepwater Horizon oil spill. The study focuses on six uncertain input parameters—two entrainment parameters, the gas to oil ratio, two parameters associated with the droplet-size distribution, and the flow rate—that impact the model\\'s estimates of the plume\\'s trap and peel heights, and of its various gas fluxes. The ranges of the uncertain inputs were determined by experimental data. Ensemble calculations were performed to construct polynomial chaos-based surrogates that describe the variations in the outputs due to variations in the uncertain inputs. The surrogates were then used to estimate reliably the statistics of the model outputs, and to perform an analysis of variance. Two experiments were performed to study the impacts of high and low flow rate uncertainties. The analysis shows that in the former case the flow rate is the largest contributor to output uncertainties, whereas in the latter case, with the uncertainty range constrained by aposteriori analyses, the flow rate\\'s contribution becomes negligible. The trap and peel heights uncertainties are then mainly due to uncertainties in the 95% percentile of the droplet size and in the entrainment parameters.

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

Science.gov (United States)

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

2012-04-01

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

Measurements of fusion neutron yields by neutron activation technique: Uncertainty due to the uncertainty on activation cross-sections

Energy Technology Data Exchange (ETDEWEB)

Stankunas, Gediminas, E-mail: gediminas.stankunas@lei.lt [Lithuanian Energy Institute, Laboratory of Nuclear Installation Safety, Breslaujos str. 3, LT-44403 Kaunas (Lithuania); EUROfusion Consortium, JET, Culham Science Centre, Abingdon OX14 3DB (United Kingdom); Batistoni, Paola [ENEA, Via E. Fermi, 45, 00044 Frascati, Rome (Italy); EUROfusion Consortium, JET, Culham Science Centre, Abingdon OX14 3DB (United Kingdom); Sjöstrand, Henrik; Conroy, Sean [Department of Physics and Astronomy, Uppsala University, PO Box 516, SE-75120 Uppsala (Sweden); EUROfusion Consortium, JET, Culham Science Centre, Abingdon OX14 3DB (United Kingdom)

2015-07-11

The neutron activation technique is routinely used in fusion experiments to measure the neutron yields. This paper investigates the uncertainty on these measurements as due to the uncertainties on dosimetry and activation reactions. For this purpose, activation cross-sections were taken from the International Reactor Dosimetry and Fusion File (IRDFF-v1.05) in 640 groups ENDF-6 format for several reactions of interest for both 2.5 and 14 MeV neutrons. Activation coefficients (reaction rates) have been calculated using the neutron flux spectra at JET vacuum vessel, both for DD and DT plasmas, calculated by MCNP in the required 640-energy group format. The related uncertainties for the JET neutron spectra are evaluated as well using the covariance data available in the library. These uncertainties are in general small, but not negligible when high accuracy is required in the determination of the fusion neutron yields.

Sensitivity functions for uncertainty analysis: Sensitivity and uncertainty analysis of reactor performance parameters

International Nuclear Information System (INIS)

Greenspan, E.

1982-01-01

This chapter presents the mathematical basis for sensitivity functions, discusses their physical meaning and information they contain, and clarifies a number of issues concerning their application, including the definition of group sensitivities, the selection of sensitivity functions to be included in the analysis, and limitations of sensitivity theory. Examines the theoretical foundation; criticality reset sensitivities; group sensitivities and uncertainties; selection of sensitivities included in the analysis; and other uses and limitations of sensitivity functions. Gives the theoretical formulation of sensitivity functions pertaining to ''as-built'' designs for performance parameters of the form of ratios of linear flux functionals (such as reaction-rate ratios), linear adjoint functionals, bilinear functions (such as reactivity worth ratios), and for reactor reactivity. Offers a consistent procedure for reducing energy-dependent or fine-group sensitivities and uncertainties to broad group sensitivities and uncertainties. Provides illustrations of sensitivity functions as well as references to available compilations of such functions and of total sensitivities. Indicates limitations of sensitivity theory originating from the fact that this theory is based on a first-order perturbation theory

Uncertainties of the Yn Parameters of the Hage-Cifarelli Formalism

Energy Technology Data Exchange (ETDEWEB)

Smith-Nelson, Mark A. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Burr, Thomas Lee [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Hutchinson, Jesson D. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Cutler, Theresa Elizabeth [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2015-08-14

One method for determining the physical parameters of a multiplying system is summarized by Cifarelli [1]. In this methodology the single, double and triple rates are determined from what is commonly referred to as Feynman histograms. This paper will examine two methods for estimating the uncertainty in the parameters used in inferring these rates. These methods will be compared with simulated data in order to determine which one best approximates the sample uncertainty.

Quantifying chemical uncertainties in simulations of the ISM

Science.gov (United States)

Glover, Simon

2018-06-01

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

Monte Carlo eigenfunction strategies and uncertainties

International Nuclear Information System (INIS)

Gast, R.C.; Candelore, N.R.

1974-01-01

Comparisons of convergence rates for several possible eigenfunction source strategies led to the selection of the ''straight'' analog of the analytic power method as the source strategy for Monte Carlo eigenfunction calculations. To insure a fair game strategy, the number of histories per iteration increases with increasing iteration number. The estimate of eigenfunction uncertainty is obtained from a modification of a proposal by D. B. MacMillan and involves only estimates of the usual purely statistical component of uncertainty and a serial correlation coefficient of lag one. 14 references. (U.S.)

SPATIAL UNCERTAINTY OF NUTRIENT LOSS BY EROSION IN SUGARCANE HARVESTING SCENARIOS

Directory of Open Access Journals (Sweden)

Patrícia Gabarra Mendonça

2015-08-01

Full Text Available The assessment of spatial uncertainty in the prediction of nutrient losses by erosion associated with landscape models is an important tool for soil conservation planning. The purpose of this study was to evaluate the spatial and local uncertainty in predicting depletion rates of soil nutrients (P, K, Ca, and Mg by soil erosion from green and burnt sugarcane harvesting scenarios, using sequential Gaussian simulation (SGS. A regular grid with equidistant intervals of 50 m (626 points was established in the 200-ha study area, in Tabapuã, São Paulo, Brazil. The rate of soil depletion (SD was calculated from the relation between the nutrient concentration in the sediments and the chemical properties in the original soil for all grid points. The data were subjected to descriptive statistical and geostatistical analysis. The mean SD rate for all nutrients was higher in the slash-and-burn than the green cane harvest scenario (Student’s t-test, pMg>K>P. The SD rate was highest in areas with greater slope. Lower uncertainties were associated to the areas with higher SD and steeper slopes. Spatial uncertainties were highest for areas of transition between concave and convex landforms.

Treatment of uncertainties in atmospheric chemical systems: A combined modeling and experimental approach

Science.gov (United States)

Pun, Betty Kong-Ling

1998-12-01

Uncertainty is endemic in modeling. This thesis is a two- phase program to understand the uncertainties in urban air pollution model predictions and in field data used to validate them. Part I demonstrates how to improve atmospheric models by analyzing the uncertainties in these models and using the results to guide new experimentation endeavors. Part II presents an experiment designed to characterize atmospheric fluctuations, which have significant implications towards the model validation process. A systematic study was undertaken to investigate the effects of uncertainties in the SAPRC mechanism for gas- phase chemistry in polluted atmospheres. The uncertainties of more than 500 parameters were compiled, including reaction rate constants, product coefficients, organic composition, and initial conditions. Uncertainty propagation using the Deterministic Equivalent Modeling Method (DEMM) revealed that the uncertainties in ozone predictions can be up to 45% based on these parametric uncertainties. The key parameters found to dominate the uncertainties of the predictions include photolysis rates of NO2, O3, and formaldehyde; the rate constant for nitric acid formation; and initial amounts of NOx and VOC. Similar uncertainty analysis procedures applied to two other mechanisms used in regional air quality models led to the conclusion that in the presence of parametric uncertainties, the mechanisms cannot be discriminated. Research efforts should focus on reducing parametric uncertainties in photolysis rates, reaction rate constants, and source terms. A new tunable diode laser (TDL) infrared spectrometer was designed and constructed to measure multiple pollutants simultaneously in the same ambient air parcels. The sensitivities of the one hertz measurements were 2 ppb for ozone, 1 ppb for NO, and 0.5 ppb for NO2. Meteorological data were also collected for wind, temperature, and UV intensity. The field data showed clear correlations between ozone, NO, and NO2 in the one

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.

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.

Uncertainty analysis for secondary energy distributions

International Nuclear Information System (INIS)

Gerstl, S.A.W.

1978-01-01

In many transport calculations the integral design parameter of interest (response) is determined mainly by secondary particles such as gamma rays from (n,γ) reactions or secondary neutrons from inelastic scattering events or (n,2n) reactions. Standard sensitivity analysis usually allows to calculate the sensitivities to the production cross sections of such secondaries, but an extended formalism is needed to also obtain the sensitivities to the energy distribution of the generated secondary particles. For a 30-group standard cross-section set 84% of all non-zero table positions pertain to the description of secondary energy distributions (SED's) and only 16% to the actual reaction cross sections. Therefore, any sensitivity/uncertainty analysis which does not consider the effects of SED's is incomplete and neglects most of the input data. This paper describes the methods of how sensitivity profiles for SED's are obtained and used to estimate the uncertainty of an integral response due to uncertainties in these SED's. The detailed theory is documented elsewhere and implemented in the LASL sensitivity code SENSIT. SED sensitivity profiles have proven particularly valuable in cross-section uncertainty analyses for fusion reactors. Even when the production cross sections for secondary neutrons were assumed to be without error, the uncertainties in the energy distribution of these secondaries produced appreciable uncertainties in the calculated tritium breeding rate. However, complete error files for SED's are presently nonexistent. Therefore, methods will be described that allow rough error estimates due to estimated SED uncertainties based on integral SED sensitivities

Application of uncertainty analysis in conceptual fusion reactor design

International Nuclear Information System (INIS)

Wu, T.; Maynard, C.W.

1979-01-01

The theories of sensitivity and uncertainty analysis are described and applied to a new conceptual tokamak fusion reactor design--NUWMAK. The responses investigated in this study include the tritium breeding ratio, first wall Ti dpa and gas productions, nuclear heating in the blanket, energy leakage to the magnet, and the dpa rate in the superconducting magnet aluminum stabilizer. The sensitivities and uncertainties of these responses are calculated. The cost/benefit feature of proposed integral measurements is also studied through the uncertainty reductions of these responses

Managing the uncertainties of the streamflow data produced by the French national hydrological services

Science.gov (United States)

Puechberty, Rachel; Bechon, Pierre-Marie; Le Coz, Jérôme; Renard, Benjamin

2015-04-01

The French national hydrological services (NHS) manage the production of streamflow time series throughout the national territory. The hydrological data are made available to end-users through different web applications and the national hydrological archive (Banque Hydro). Providing end-users with qualitative and quantitative information on the uncertainty of the hydrological data is key to allow them drawing relevant conclusions and making appropriate decisions. Due to technical and organisational issues that are specific to the field of hydrometry, quantifying the uncertainty of hydrological measurements is still challenging and not yet standardized. The French NHS have made progress on building a consistent strategy to assess the uncertainty of their streamflow data. The strategy consists of addressing the uncertainties produced and propagated at each step of the data production with uncertainty analysis tools that are compatible with each other and compliant with international uncertainty guidance and standards. Beyond the necessary research and methodological developments, operational software tools and procedures are absolutely necessary to the data management and uncertainty analysis by field hydrologists. A first challenge is to assess, and if possible reduce, the uncertainty of streamgauging data, i.e. direct stage-discharge measurements. Interlaboratory experiments proved to be a very efficient way to empirically measure the uncertainty of a given streamgauging technique in given measurement conditions. The Q+ method (Le Coz et al., 2012) was developed to improve the uncertainty propagation method proposed in the ISO748 standard for velocity-area gaugings. Both empirical or computed (with Q+) uncertainty values can now be assigned in BAREME, which is the software used by the French NHS for managing streamgauging measurements. A second pivotal step is to quantify the uncertainty related to stage-discharge rating curves and their application to water level

An uncertainty inventory demonstration - a primary step in uncertainty quantification

Energy Technology Data Exchange (ETDEWEB)

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

2009-01-01

Tools, methods, and theories for assessing and quantifying uncertainties vary by application. Uncertainty quantification tasks have unique desiderata and circumstances. To realistically assess uncertainty requires the engineer/scientist to specify mathematical models, the physical phenomena of interest, and the theory or framework for assessments. For example, Probabilistic Risk Assessment (PRA) specifically identifies uncertainties using probability theory, and therefore, PRA's lack formal procedures for quantifying uncertainties that are not probabilistic. The Phenomena Identification and Ranking Technique (PIRT) proceeds by ranking phenomena using scoring criteria that results in linguistic descriptors, such as importance ranked with words, 'High/Medium/Low.' The use of words allows PIRT to be flexible, but the analysis may then be difficult to combine with other uncertainty theories. We propose that a necessary step for the development of a procedure or protocol for uncertainty quantification (UQ) is the application of an Uncertainty Inventory. An Uncertainty Inventory should be considered and performed in the earliest stages of UQ.

SU-E-J-116: Uncertainties Associated with Dose Summation of High-Dose Rate Brachytherapy and Intensity Modulated Radiotherapy for Gynecological Cases

Energy Technology Data Exchange (ETDEWEB)

Kauweloa, K; Bergamo, A; Gutierrez, A; Stathakis, S; Papanikolaou, N; Kirby, N [University of Texas HSC SA, San Antonio, TX (United States); Cancer Therapy and Research Center, San Antonio, TX (United States); Mavroidis, P [University of North Carolina, Chapel Hill, NC (United States)

2015-06-15

Purpose: Determining the cumulative dose distribution (CDD) for gynecological patients treated with both high-dose rate (HDR) brachytherapy and intensity-modulated radiotherapy (IMRT) is challenging. The purpose of this work is to study the uncertainty of performing this with a structure-guided deformable (SGD) approach in Velocity. Methods: For SGD, the Hounsfield units inside specified contours are overridden to set uniform values. Deformable image registration (DIR) is the run on these process images, which forces the DIR to focus on these contour boundaries. 18 gynecological cancer patients were used in this study. The original bladder and rectum planning contours for these patients were used to drive the SGD. A second set of contours were made of the bladder by the same person with the intent of carefully making them completely consistent with each other. This second set was utilized to evaluate the spatial accuracy of the SGD. The determined spatial accuracy was then multiplied by the local dose gradient to determine a dose uncertainty associated with the SGD dose warping. The normal tissue complication probability (NTCP) was then calculated for each dose volume histogram (DVH) that included four different probabilistic uncertainties associated with the spatial errors (e.g., 68.3% and 95.4%). Results: The NTCPs for each DVH (e.g., NTCP-−95.4%, NTCP-−68.3%, NTCP-68.3%, NTCP-95.4%) differed amongst patients. All patients had an NTCP-−95.4% close to 0%, while NTCP-95.4% ranged from 0.67% to 100%. Nine patients had an NTCP-−95.4% less than 50% while the remaining nine patients had NTCP-95.4% greater than 50%. Conclusion: The uncertainty associated with this CDD technique renders a large NTCP uncertainty. Thus, it is currently not practical for clinical use. The two ways to improve this would be to use more precise contours to drive the SGD and to use a more accurate DIR algorithm.

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.

Inflation and Inflation Uncertainty Revisited: Evidence from Egypt

Directory of Open Access Journals (Sweden)

Mesbah Fathy Sharaf

2015-07-01

Full Text Available The welfare costs of inflation and inflation uncertainty are well documented in the literature and empirical evidence on the link between the two is sparse in the case of Egypt. This paper investigates the causal relationship between inflation and inflation uncertainty in Egypt using monthly time series data during the period January 1974–April 2015. To endogenously control for any potential structural breaks in the inflation time series, Zivot and Andrews (2002 and Clemente–Montanes–Reyes (1998 unit root tests are used. The inflation–inflation uncertainty relation is modeled by the standard two-step approach as well as simultaneously using various versions of the GARCH-M model to control for any potential feedback effects. The analyses explicitly control for the effect of the Economic Reform and Structural Adjustment Program (ERSAP undertaken by the Egyptian government in the early 1990s, which affected inflation rate and its associated volatility. Results show a high degree of inflation–volatility persistence in the response to inflationary shocks. Granger-causality test along with symmetric and asymmetric GARCH-M models indicate a statistically significant bi-directional positive relationship between inflation and inflation uncertainty, supporting both the Friedman–Ball and the Cukierman–Meltzer hypotheses. The findings are robust to the various estimation methods and model specifications. The findings of this paper support the view of adopting inflation-targeting policy in Egypt, after fulfilling its preconditions, to reduce the welfare cost of inflation and its related uncertainties. Monetary authorities in Egypt should enhance the credibility of monetary policy and attempt to reduce inflation uncertainty, which will help lower inflation rates.

Managing Uncertainty for an Integrated Fishery

Directory of Open Access Journals (Sweden)

MB Hasan

2012-06-01

Full Text Available This paper investigates ways to deal with the uncertainties in fishing trawler scheduling and production planning in a quota-based integrated commercial fishery. A commercial fishery faces uncertainty mainly from variation in catch rate, which may be due to weather, and other environmental factors. The firm tries to manage this uncertainty through planning co-ordination of fishing trawler scheduling, catch quota, processing and labour allocation, and inventory control. Scheduling must necessarily be done over some finite planning horizon, and the trawler schedule itself introduces man-made variability, which in turn induces inventory in the processing plant. This induced inventory must be managed, complicated by the inability to plan easily beyond the current planning horizon. We develop a surprisingly simple innovation in inventory, which we have not seen in other papers on production management, which of requiring beginning inventory to equal ending inventory. This tool gives management a way to calculate a profit-maximizing safety stock that counter-acts the man-made variability due to the trawler scheduling. We found that the variability of catch rate had virtually no effects on the profitability with inventory. We report numerical results for several planning horizon models, based on data for a major New Zealand fishery.

Modelling of plasma-based dry reforming: how do uncertainties in the input data affect the calculation results?

Science.gov (United States)

Wang, Weizong; Berthelot, Antonin; Zhang, Quanzhi; Bogaerts, Annemie

2018-05-01

One of the main issues in plasma chemistry modeling is that the cross sections and rate coefficients are subject to uncertainties, which yields uncertainties in the modeling results and hence hinders the predictive capabilities. In this paper, we reveal the impact of these uncertainties on the model predictions of plasma-based dry reforming in a dielectric barrier discharge. For this purpose, we performed a detailed uncertainty analysis and sensitivity study. 2000 different combinations of rate coefficients, based on the uncertainty from a log-normal distribution, are used to predict the uncertainties in the model output. The uncertainties in the electron density and electron temperature are around 11% and 8% at the maximum of the power deposition for a 70% confidence level. Still, this can have a major effect on the electron impact rates and hence on the calculated conversions of CO2 and CH4, as well as on the selectivities of CO and H2. For the CO2 and CH4 conversion, we obtain uncertainties of 24% and 33%, respectively. For the CO and H2 selectivity, the corresponding uncertainties are 28% and 14%, respectively. We also identify which reactions contribute most to the uncertainty in the model predictions. In order to improve the accuracy and reliability of plasma chemistry models, we recommend using only verified rate coefficients, and we point out the need for dedicated verification experiments.

Quantifying the uncertainty in discharge data using hydraulic knowledge and uncertain gaugings: a Bayesian method named BaRatin

Science.gov (United States)

Le Coz, Jérôme; Renard, Benjamin; Bonnifait, Laurent; Branger, Flora; Le Boursicaud, Raphaël; Horner, Ivan; Mansanarez, Valentin; Lang, Michel; Vigneau, Sylvain

2015-04-01

River discharge is a crucial variable for Hydrology: as the output variable of most hydrologic models, it is used for sensitivity analyses, model structure identification, parameter estimation, data assimilation, prediction, etc. A major difficulty stems from the fact that river discharge is not measured continuously. Instead, discharge time series used by hydrologists are usually based on simple stage-discharge relations (rating curves) calibrated using a set of direct stage-discharge measurements (gaugings). In this presentation, we present a Bayesian approach (cf. Le Coz et al., 2014) to build such hydrometric rating curves, to estimate the associated uncertainty and to propagate this uncertainty to discharge time series. The three main steps of this approach are described: (1) Hydraulic analysis: identification of the hydraulic controls that govern the stage-discharge relation, identification of the rating curve equation and specification of prior distributions for the rating curve parameters; (2) Rating curve estimation: Bayesian inference of the rating curve parameters, accounting for the individual uncertainties of available gaugings, which often differ according to the discharge measurement procedure and the flow conditions; (3) Uncertainty propagation: quantification of the uncertainty in discharge time series, accounting for both the rating curve uncertainties and the uncertainty of recorded stage values. The rating curve uncertainties combine the parametric uncertainties and the remnant uncertainties that reflect the limited accuracy of the mathematical model used to simulate the physical stage-discharge relation. In addition, we also discuss current research activities, including the treatment of non-univocal stage-discharge relationships (e.g. due to hydraulic hysteresis, vegetation growth, sudden change of the geometry of the section, etc.). An operational version of the BaRatin software and its graphical interface are made available free of charge on

Propagation of uncertainty and sensitivity analysis in an integral oil-gas plume model

KAUST Repository

Wang, Shitao; Iskandarani, Mohamed; Srinivasan, Ashwanth; Thacker, W. Carlisle; Winokur, Justin; Knio, Omar

2016-01-01

Polynomial Chaos expansions are used to analyze uncertainties in an integral oil-gas plume model simulating the Deepwater Horizon oil spill. The study focuses on six uncertain input parameters—two entrainment parameters, the gas to oil ratio, two parameters associated with the droplet-size distribution, and the flow rate—that impact the model's estimates of the plume's trap and peel heights, and of its various gas fluxes. The ranges of the uncertain inputs were determined by experimental data. Ensemble calculations were performed to construct polynomial chaos-based surrogates that describe the variations in the outputs due to variations in the uncertain inputs. The surrogates were then used to estimate reliably the statistics of the model outputs, and to perform an analysis of variance. Two experiments were performed to study the impacts of high and low flow rate uncertainties. The analysis shows that in the former case the flow rate is the largest contributor to output uncertainties, whereas in the latter case, with the uncertainty range constrained by aposteriori analyses, the flow rate's contribution becomes negligible. The trap and peel heights uncertainties are then mainly due to uncertainties in the 95% percentile of the droplet size and in the entrainment parameters.

Quantification of margins and uncertainties: Alternative representations of epistemic uncertainty

International Nuclear Information System (INIS)

Helton, Jon C.; Johnson, Jay D.

2011-01-01

In 2001, the National Nuclear Security Administration of the U.S. Department of Energy in conjunction with the national security laboratories (i.e., Los Alamos National Laboratory, Lawrence Livermore National Laboratory and Sandia National Laboratories) initiated development of a process designated Quantification of Margins and Uncertainties (QMU) for the use of risk assessment methodologies in the certification of the reliability and safety of the nation's nuclear weapons stockpile. A previous presentation, 'Quantification of Margins and Uncertainties: Conceptual and Computational Basis,' describes the basic ideas that underlie QMU and illustrates these ideas with two notional examples that employ probability for the representation of aleatory and epistemic uncertainty. The current presentation introduces and illustrates the use of interval analysis, possibility theory and evidence theory as alternatives to the use of probability theory for the representation of epistemic uncertainty in QMU-type analyses. The following topics are considered: the mathematical structure of alternative representations of uncertainty, alternative representations of epistemic uncertainty in QMU analyses involving only epistemic uncertainty, and alternative representations of epistemic uncertainty in QMU analyses involving a separation of aleatory and epistemic uncertainty. Analyses involving interval analysis, possibility theory and evidence theory are illustrated with the same two notional examples used in the presentation indicated above to illustrate the use of probability to represent aleatory and epistemic uncertainty in QMU analyses.

Uncertainty analysis guide

International Nuclear Information System (INIS)

Andres, T.H.

2002-05-01

This guide applies to the estimation of uncertainty in quantities calculated by scientific, analysis and design computer programs that fall within the scope of AECL's software quality assurance (SQA) manual. The guide weaves together rational approaches from the SQA manual and three other diverse sources: (a) the CSAU (Code Scaling, Applicability, and Uncertainty) evaluation methodology; (b) the ISO Guide,for the Expression of Uncertainty in Measurement; and (c) the SVA (Systems Variability Analysis) method of risk analysis. This report describes the manner by which random and systematic uncertainties in calculated quantities can be estimated and expressed. Random uncertainty in model output can be attributed to uncertainties of inputs. The propagation of these uncertainties through a computer model can be represented in a variety of ways, including exact calculations, series approximations and Monte Carlo methods. Systematic uncertainties emerge from the development of the computer model itself, through simplifications and conservatisms, for example. These must be estimated and combined with random uncertainties to determine the combined uncertainty in a model output. This report also addresses the method by which uncertainties should be employed in code validation, in order to determine whether experiments and simulations agree, and whether or not a code satisfies the required tolerance for its application. (author)

Uncertainty analysis guide

Energy Technology Data Exchange (ETDEWEB)

Andres, T.H

2002-05-01

This guide applies to the estimation of uncertainty in quantities calculated by scientific, analysis and design computer programs that fall within the scope of AECL's software quality assurance (SQA) manual. The guide weaves together rational approaches from the SQA manual and three other diverse sources: (a) the CSAU (Code Scaling, Applicability, and Uncertainty) evaluation methodology; (b) the ISO Guide,for the Expression of Uncertainty in Measurement; and (c) the SVA (Systems Variability Analysis) method of risk analysis. This report describes the manner by which random and systematic uncertainties in calculated quantities can be estimated and expressed. Random uncertainty in model output can be attributed to uncertainties of inputs. The propagation of these uncertainties through a computer model can be represented in a variety of ways, including exact calculations, series approximations and Monte Carlo methods. Systematic uncertainties emerge from the development of the computer model itself, through simplifications and conservatisms, for example. These must be estimated and combined with random uncertainties to determine the combined uncertainty in a model output. This report also addresses the method by which uncertainties should be employed in code validation, in order to determine whether experiments and simulations agree, and whether or not a code satisfies the required tolerance for its application. (author)

Fuzzy uncertainty modeling applied to AP1000 nuclear power plant LOCA

International Nuclear Information System (INIS)

Ferreira Guimaraes, Antonio Cesar; Franklin Lapa, Celso Marcelo; Lamego Simoes Filho, Francisco Fernando; Cabral, Denise Cunha

2011-01-01

Research highlights: → This article presents an uncertainty modelling study using a fuzzy approach. → The AP1000 Westinghouse NPP was used and it is provided of passive safety systems. → The use of advanced passive safety systems in NPP has limited operational experience. → Failure rates and basic events probabilities used on the fault tree analysis. → Fuzzy uncertainty approach was employed to reliability of the AP1000 large LOCA. - Abstract: This article presents an uncertainty modeling study using a fuzzy approach applied to the Westinghouse advanced nuclear reactor. The AP1000 Westinghouse Nuclear Power Plant (NPP) is provided of passive safety systems, based on thermo physics phenomenon, that require no operating actions, soon after an incident has been detected. The use of advanced passive safety systems in NPP has limited operational experience. As it occurs in any reliability study, statistically non-significant events report introduces a significant uncertainty level about the failure rates and basic events probabilities used on the fault tree analysis (FTA). In order to model this uncertainty, a fuzzy approach was employed to reliability analysis of the AP1000 large break Loss of Coolant Accident (LOCA). The final results have revealed that the proposed approach may be successfully applied to modeling of uncertainties in safety studies.

Comprehensive neutron cross-section and secondary energy distribution uncertainty analysis for a fusion reactor

International Nuclear Information System (INIS)

Gerstl, S.A.W.; LaBauve, R.J.; Young, P.G.

1980-05-01

On the example of General Atomic's well-documented Power Generating Fusion Reactor (PGFR) design, this report exercises a comprehensive neutron cross-section and secondary energy distribution (SED) uncertainty analysis. The LASL sensitivity and uncertainty analysis code SENSIT is used to calculate reaction cross-section sensitivity profiles and integral SED sensitivity coefficients. These are then folded with covariance matrices and integral SED uncertainties to obtain the resulting uncertainties of three calculated neutronics design parameters: two critical radiation damage rates and a nuclear heating rate. The report documents the first sensitivity-based data uncertainty analysis, which incorporates a quantitative treatment of the effects of SED uncertainties. The results demonstrate quantitatively that the ENDF/B-V cross-section data files for C, H, and O, including their SED data, are fully adequate for this design application, while the data for Fe and Ni are at best marginally adequate because they give rise to response uncertainties up to 25%. Much higher response uncertainties are caused by cross-section and SED data uncertainties in Cu (26 to 45%), tungsten (24 to 54%), and Cr (up to 98%). Specific recommendations are given for re-evaluations of certain reaction cross-sections, secondary energy distributions, and uncertainty estimates

Uncertainty evaluation of reliability of shutdown system of a medium size fast breeder reactor

Energy Technology Data Exchange (ETDEWEB)

Zeliang, Chireuding; Singh, Om Pal, E-mail: singhop@iitk.ac.in; Munshi, Prabhat

2016-11-15

Highlights: • Uncertainty analysis of reliability of Shutdown System is carried out. • Monte Carlo method of sampling is used. • The effect of various reliability improvement measures of SDS are accounted. - Abstract: In this paper, results are presented on the uncertainty evaluation of the reliability of Shutdown System (SDS) of a Medium Size Fast Breeder Reactor (MSFBR). The reliability analysis results are of Kumar et al. (2005). The failure rate of the components of SDS are taken from International literature and it is assumed that these follow log-normal distribution. Fault tree method is employed to propagate the uncertainty in failure rate from components level to shutdown system level. The beta factor model is used to account different extent of diversity. The Monte Carlo sampling technique is used for the analysis. The results of uncertainty analysis are presented in terms of the probability density function, cumulative distribution function, mean, variance, percentile values, confidence intervals, etc. It is observed that the spread in the probability distribution of SDS failure rate is less than SDS components failure rate and ninety percent values of the failure rate of SDS falls below the target value. As generic values of failure rates are used, sensitivity analysis is performed with respect to failure rate of control and safety rods and beta factor. It is discovered that a large increase in failure rate of SDS rods is not carried to SDS system failure proportionately. The failure rate of SDS is very sensitive to the beta factor of common cause failure between the two systems of SDS. The results of the study provide insight in the propagation of uncertainty in the failure rate of SDS components to failure rate of shutdown system.

Subspace-based Inverse Uncertainty Quantification for Nuclear Data Assessment

Energy Technology Data Exchange (ETDEWEB)

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

2015-01-15

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

Uncertainty in reactive transport geochemical modelling

International Nuclear Information System (INIS)

Oedegaard-Jensen, A.; Ekberg, C.

2005-01-01

Full text of publication follows: Geochemical modelling is one way of predicting the transport of i.e. radionuclides in a rock formation. In a rock formation there will be fractures in which water and dissolved species can be transported. The composition of the water and the rock can either increase or decrease the mobility of the transported entities. When doing simulations on the mobility or transport of different species one has to know the exact water composition, the exact flow rates in the fracture and in the surrounding rock, the porosity and which minerals the rock is composed of. The problem with simulations on rocks is that the rock itself it not uniform i.e. larger fractures in some areas and smaller in other areas which can give different water flows. The rock composition can be different in different areas. In additions to this variance in the rock there are also problems with measuring the physical parameters used in a simulation. All measurements will perturb the rock and this perturbation will results in more or less correct values of the interesting parameters. The analytical methods used are also encumbered with uncertainties which in this case are added to the uncertainty from the perturbation of the analysed parameters. When doing simulation the effect of the uncertainties must be taken into account. As the computers are getting faster and faster the complexity of simulated systems are increased which also increase the uncertainty in the results from the simulations. In this paper we will show how the uncertainty in the different parameters will effect the solubility and mobility of different species. Small uncertainties in the input parameters can result in large uncertainties in the end. (authors)

"Spicy ice" ja klaveri talveuniversiteet / Toomas Velmet

Index Scriptorium Estoniae

Velmet, Toomas, 1942-

2011-01-01

25. veebruaril Pärnu kontserdimajas toimunud talveunversiteedi galakontserdist, kus esinesid pianistid Liidia Ilves (Eesti), Cäcilia Maria Weber (Austria) ja Nena Kozjek (Sloveenia) ja Pärnu Linnaorkester Leonid Grini dirigeerimisel

Correction to the count-rate detection limit and sample/blank time-allocation methods

International Nuclear Information System (INIS)

Alvarez, Joseph L.

2013-01-01

A common form of count-rate detection limits contains a propagation of uncertainty error. This error originated in methods to minimize uncertainty in the subtraction of the blank counts from the gross sample counts by allocation of blank and sample counting times. Correct uncertainty propagation showed that the time allocation equations have no solution. This publication presents the correct form of count-rate detection limits. -- Highlights: •The paper demonstrated a proper method of propagating uncertainty of count rate differences. •The standard count-rate detection limits were in error. •Count-time allocation methods for minimum uncertainty were in error. •The paper presented the correct form of the count-rate detection limit. •The paper discussed the confusion between count-rate uncertainty and count uncertainty

Evaluation of incremental reactivity and its uncertainty in Southern California.

Science.gov (United States)

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

2003-04-15

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

Local conditions and uncertainty bands for Semiscale Test S-02-9

International Nuclear Information System (INIS)

Varacalle, D.J. Jr.

1979-01-01

Analysis was performed to derive local conditions heat transfer parameters and their uncertainties using computer codes and experimentally derived boundary conditions for the Semiscale core for LOCA Test S-02-9. Calculations performed consisted of nominal code cases using best-estimate input parameters and cases where the specified input parameters were perturbed in accordance with the response surface method of uncertainty analysis. The output parameters of interest were those that are used in film boiling heat transfer correlations including enthalpy, pressure, quality, and coolant flow rate. Large uncertainty deviations occurred during low core mass flow periods where the relative flow uncertainties were large. Utilizing the derived local conditions and their associated uncertainties, a study was then made which showed the uncertainty in film boiling heat transfer coefficient varied between 5 and 250%

Evaluation of uncertainties in the calibration of radiation personal monitor with Cesium-137 source

International Nuclear Information System (INIS)

Mirapalheta, Tatiane; Alexandre, Anderson; Costa, Camila; Batista, Gilmar; Paulino, Thyago; Albuquerque, Marcos; Universidade do Estado do Rio de Janeiro

2016-01-01

This work shows the entire calibration process of an individual monitor, focusing on radiation protection, in health, correlating these measures associated uncertainties. The results show an expanded uncertainty of 5.81% for dose rate measurements and an expanded uncertainty of 5.61% for integrated dose measurements, these uncertainties have been evaluated the type A and type B with its components. (author)

ICYESS 2013: Understanding and Interpreting Uncertainty

Science.gov (United States)

Rauser, F.; Niederdrenk, L.; Schemann, V.; Schmidt, A.; Suesser, D.; Sonntag, S.

2013-12-01

We will report the outcomes and highlights of the Interdisciplinary Conference of Young Earth System Scientists (ICYESS) on Understanding and Interpreting Uncertainty in September 2013, Hamburg, Germany. This conference is aimed at early career scientists (Masters to Postdocs) from a large variety of scientific disciplines and backgrounds (natural, social and political sciences) and will enable 3 days of discussions on a variety of uncertainty-related aspects: 1) How do we deal with implicit and explicit uncertainty in our daily scientific work? What is uncertain for us, and for which reasons? 2) How can we communicate these uncertainties to other disciplines? E.g., is uncertainty in cloud parameterization and respectively equilibrium climate sensitivity a concept that is understood equally well in natural and social sciences that deal with Earth System questions? Or vice versa, is, e.g., normative uncertainty as in choosing a discount rate relevant for natural scientists? How can those uncertainties be reconciled? 3) How can science communicate this uncertainty to the public? Is it useful at all? How are the different possible measures of uncertainty understood in different realms of public discourse? Basically, we want to learn from all disciplines that work together in the broad Earth System Science community how to understand and interpret uncertainty - and then transfer this understanding to the problem of how to communicate with the public, or its different layers / agents. ICYESS is structured in a way that participation is only possible via presentation, so every participant will give their own professional input into how the respective disciplines deal with uncertainty. Additionally, a large focus is put onto communication techniques; there are no 'standard presentations' in ICYESS. Keynote lectures by renowned scientists and discussions will lead to a deeper interdisciplinary understanding of what we do not really know, and how to deal with it. Many

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

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.

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

Science.gov (United States)

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

2009-10-01

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

Heisenberg's principle of uncertainty and the uncertainty relations

International Nuclear Information System (INIS)

Redei, Miklos

1987-01-01

The usual verbal form of the Heisenberg uncertainty principle and the usual mathematical formulation (the so-called uncertainty theorem) are not equivalent. The meaning of the concept 'uncertainty' is not unambiguous and different interpretations are used in the literature. Recently a renewed interest has appeared to reinterpret and reformulate the precise meaning of Heisenberg's principle and to find adequate mathematical form. The suggested new theorems are surveyed and critically analyzed. (D.Gy.) 20 refs

Measurement Uncertainty

Science.gov (United States)

Koch, Michael

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

SENSIT: a cross-section and design sensitivity and uncertainty analysis code

International Nuclear Information System (INIS)

Gerstl, S.A.W.

1980-01-01

SENSIT computes the sensitivity and uncertainty of a calculated integral response (such as a dose rate) due to input cross sections and their uncertainties. Sensitivity profiles are computed for neutron and gamma-ray reaction cross sections of standard multigroup cross section sets and for secondary energy distributions (SEDs) of multigroup scattering matrices. In the design sensitivity mode, SENSIT computes changes in an integral response due to design changes and gives the appropriate sensitivity coefficients. Cross section uncertainty analyses are performed for three types of input data uncertainties: cross-section covariance matrices for pairs of multigroup reaction cross sections, spectral shape uncertainty parameters for secondary energy distributions (integral SED uncertainties), and covariance matrices for energy-dependent response functions. For all three types of data uncertainties SENSIT computes the resulting variance and estimated standard deviation in an integral response of interest, on the basis of generalized perturbation theory. SENSIT attempts to be more comprehensive than earlier sensitivity analysis codes, such as SWANLAKE

HSIP E911 Public Safety Answering Point (PSAP)

Data.gov (United States)

Earth Data Analysis Center, University of New Mexico — 911 Public Safety Answering Point (PSAP) service area boundaries in New Mexico According to the National Emergency Number Association (NENA), a Public Safety...

Psychophsyiological reactivity during uncertainty and ambiguity processing in high and low worriers.

Science.gov (United States)

Kirschner, Hans; Hilbert, Kevin; Hoyer, Jana; Lueken, Ulrike; Beesdo-Baum, Katja

2016-03-01

Intolerance of uncertainty (IU) has been linked to Generalized Anxiety Disorder (GAD), but studies experimentally manipulating uncertainty have mostly failed to find differences between GAD patients and controls, possible due to a lack of distinction between uncertainty and ambiguity. This study therefore investigated reactivity to ambiguity in addition to uncertainty in high worriers (HW) and low worriers (LW). We hypothesized an interpretation bias between the groups during ambiguity tasks, while uncertainty would facilitate threat processing of subsequent aversive stimuli. HW (N = 23) and LW (N = 23) completed a paradigm comprising the anticipation and perception of pictures with dangerous, safe, or ambiguous content. Anticipatory cues were certain (always correct information about the following picture) or uncertain (no information). Subjective ratings, reaction times and skin conductance responses (SCRs) were recorded. HW rated particularly ambiguous pictures as more aversive and showed longer reaction times to all picture conditions compared to LW. SCRs were also larger in HW compared to LW, particularly during uncertain but also safe anticipation. No group differences were observed during perception of stimuli. All participants were female. HW was used as subclinical phenotype of GAD. Intolerance of ambiguity seems to be related to individual differences in worry and possibly to the development of GAD. Threat-related interpretations differentiating HW and LW occurred particularly for ambiguous pictures but were not accompanied by increased autonomic arousal during the picture viewing. This disparity between subjective rating and arousal may be the result of worrying in response to intolerance of uncertainty, restraining physiological responses. Copyright © 2015 Elsevier Ltd. All rights reserved.

Dual long memory of inflation and test of the relationship between inflation and inflation uncertainty

OpenAIRE

LIU Jinquan; ZHENG Tingguo; SUI Jianli

2008-01-01

This paper uses the ARFIMA-FIGARCH model to investigate the China¡¯s monthly inflation rate from January 1983 to October 2005. It is found that both first moment and second moment of inflation have remarkable long memory, indicating the existence of long memory properties in both inflation level and inflation uncertainty. By the Granger-causality test on inflation rate and inflation uncertainty, it is shown that the inflation level affects the inflation uncertainty and so supports Friedman hy...

A robust Bayesian approach to modeling epistemic uncertainty in common-cause failure models

International Nuclear Information System (INIS)

Troffaes, Matthias C.M.; Walter, Gero; Kelly, Dana

2014-01-01

In a standard Bayesian approach to the alpha-factor model for common-cause failure, a precise Dirichlet prior distribution models epistemic uncertainty in the alpha-factors. This Dirichlet prior is then updated with observed data to obtain a posterior distribution, which forms the basis for further inferences. In this paper, we adapt the imprecise Dirichlet model of Walley to represent epistemic uncertainty in the alpha-factors. In this approach, epistemic uncertainty is expressed more cautiously via lower and upper expectations for each alpha-factor, along with a learning parameter which determines how quickly the model learns from observed data. For this application, we focus on elicitation of the learning parameter, and find that values in the range of 1 to 10 seem reasonable. The approach is compared with Kelly and Atwood's minimally informative Dirichlet prior for the alpha-factor model, which incorporated precise mean values for the alpha-factors, but which was otherwise quite diffuse. Next, we explore the use of a set of Gamma priors to model epistemic uncertainty in the marginal failure rate, expressed via a lower and upper expectation for this rate, again along with a learning parameter. As zero counts are generally less of an issue here, we find that the choice of this learning parameter is less crucial. Finally, we demonstrate how both epistemic uncertainty models can be combined to arrive at lower and upper expectations for all common-cause failure rates. Thereby, we effectively provide a full sensitivity analysis of common-cause failure rates, properly reflecting epistemic uncertainty of the analyst on all levels of the common-cause failure model

[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.

Understanding Interest Rate Volatility

DEFF Research Database (Denmark)

Volker, Desi

This thesis is the result of my Ph.D. studies at the Department of Finance of the Copenhagen Business School. It consists of three essays covering topics related to the term structure of interest rates, monetary policy and interest rate volatility. The rst essay, \\Monetary Policy Uncertainty...... and Interest Rates", examines the role of monetary policy uncertainty on the term structure of interest rates. The second essay, \\A Regime-Switching A ne Term Structure Model with Stochastic Volatility" (co-authored with Sebastian Fux), investigates the ability of the class of regime switching models...... with and without stochastic volatility to capture the main stylized features of U.S. interest rates. The third essay, \\Variance Risk Premia in the Interest Rate Swap Market", investigates the time-series and cross-sectional properties of the compensation demanded for holding interest rate variance risk. The essays...

Instrument uncertainty predictions

International Nuclear Information System (INIS)

Coutts, D.A.

1991-07-01

The accuracy of measurements and correlations should normally be provided for most experimental activities. The uncertainty is a measure of the accuracy of a stated value or equation. The uncertainty term reflects a combination of instrument errors, modeling limitations, and phenomena understanding deficiencies. This report provides several methodologies to estimate an instrument's uncertainty when used in experimental work. Methods are shown to predict both the pretest and post-test uncertainty

Optimum sizing of wind-battery systems incorporating resource uncertainty

International Nuclear Information System (INIS)

Roy, Anindita; Kedare, Shireesh B.; Bandyopadhyay, Santanu

2010-01-01

The inherent uncertainty of the wind is a major impediment for successful implementation of wind based power generation technology. A methodology has been proposed in this paper to incorporate wind speed uncertainty in sizing wind-battery system for isolated applications. The uncertainty associated with the wind speed is incorporated using chance constraint programming approach. For a pre-specified reliability requirement, a deterministic equivalent energy balance equation may be derived from the chance constraint that allows time series simulation of the entire system. This results in a generation of the entire set of feasible design options, satisfying different system level constraints, on a battery capacity vs. generator rating diagram, also known as the design space. The proposed methodology highlights the trade-offs between the wind turbine rating, rotor diameter and the battery size for a given reliability of power supply. The optimum configuration is chosen on the basis of the minimum cost of energy (US$/kWh). It is shown with the help of illustrative examples that the proposed methodology is generic and flexible to incorporate alternate sub-component models. (author)

The influence of isotope substitution of neon atom on the integral cross sections of rotational excitation in Ne—Na2 collisions

International Nuclear Information System (INIS)

Zang Hua-Ping; Li Wen-Feng; Linghu Rong-Feng; Cheng Xin-Lu; Yang Xiang-Dong

2011-01-01

This paper applies the multiple ellipsoid model to the 16 Ne ( 20 Ne, 28 Ne, 34 Ne)-Na 2 collision systems, and calculates integral cross sections for rotational excitation at the incident energy of 190 meV. It can be seen that the accuracy of the integral cross sections can be improved by increasing the number of equipotential ellipsoid surfaces. Moreover, by analysing the differences of these integral cross sections, it obtains the change rules of the integral cross sections with the increase of rotational angular quantum number J', and with the change of the mass of isotope substitution neon atom. Finally, the contribution of different regions of the potential to inelastic cross sections for 20 Ne-Na 2 collision system is investigated at relative incident energy of 190 meV. (general)

Uncertainty and measurement

International Nuclear Information System (INIS)

Landsberg, P.T.

1990-01-01

This paper explores how the quantum mechanics uncertainty relation can be considered to result from measurements. A distinction is drawn between the uncertainties obtained by scrutinising experiments and the standard deviation type of uncertainty definition used in quantum formalism. (UK)

THE INFLUENCE OF UNCERTAINTIES IN THE 15O(α, γ)19Ne REACTION RATE ON MODELS OF TYPE I X-RAY BURSTS

International Nuclear Information System (INIS)

Davids, Barry; Cyburt, Richard H.; Jose, Jordi; Mythili, Subramanian

2011-01-01

We present a Monte Carlo calculation of the astrophysical rate of the 15 O(α, γ) 19 Ne reaction based on an evaluation of published experimental data. By considering the likelihood distributions of individual resonance parameters derived from measurements, estimates of upper and lower limits on the reaction rate at the 99.73% confidence level are derived in addition to the recommended, median value. These three reaction rates are used as input for three separate calculations of Type I X-ray bursts (XRBs) using spherically symmetric, hydrodynamic simulations of an accreting neutron star. In this way the influence of the 15 O(α, γ) 19 Ne reaction rate on the peak luminosity, recurrence time, and associated nucleosynthesis in models of Type I XRBs is studied. Contrary to previous findings, no substantial effect on any of these quantities is observed in a sequence of four bursts when varying the reaction rate between its lower and upper limits. Rather, the differences in these quantities are comparable to the burst-to-burst variations with a fixed reaction rate, indicating that uncertainties in the 15 O(α, γ) 19 Ne reaction rate do not strongly affect the predictions of this Type I XRB model.

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

Energy Technology Data Exchange (ETDEWEB)

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

2017-03-15

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

Making predictions in a changing world-inference, uncertainty, and learning.

Science.gov (United States)

O'Reilly, Jill X

2013-01-01

To function effectively, brains need to make predictions about their environment based on past experience, i.e., they need to learn about their environment. The algorithms by which learning occurs are of interest to neuroscientists, both in their own right (because they exist in the brain) and as a tool to model participants' incomplete knowledge of task parameters and hence, to better understand their behavior. This review focusses on a particular challenge for learning algorithms-how to match the rate at which they learn to the rate of change in the environment, so that they use as much observed data as possible whilst disregarding irrelevant, old observations. To do this algorithms must evaluate whether the environment is changing. We discuss the concepts of likelihood, priors and transition functions, and how these relate to change detection. We review expected and estimation uncertainty, and how these relate to change detection and learning rate. Finally, we consider the neural correlates of uncertainty and learning. We argue that the neural correlates of uncertainty bear a resemblance to neural systems that are active when agents actively explore their environments, suggesting that the mechanisms by which the rate of learning is set may be subject to top down control (in circumstances when agents actively seek new information) as well as bottom up control (by observations that imply change in the environment).

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

Energy Technology Data Exchange (ETDEWEB)

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

2017-05-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2017-06-01

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

Improving the driver-automation interaction: an approach using automation uncertainty.

Science.gov (United States)

Beller, Johannes; Heesen, Matthias; Vollrath, Mark

2013-12-01

The aim of this study was to evaluate whether communicating automation uncertainty improves the driver-automation interaction. A false system understanding of infallibility may provoke automation misuse and can lead to severe consequences in case of automation failure. The presentation of automation uncertainty may prevent this false system understanding and, as was shown by previous studies, may have numerous benefits. Few studies, however, have clearly shown the potential of communicating uncertainty information in driving. The current study fills this gap. We conducted a driving simulator experiment, varying the presented uncertainty information between participants (no uncertainty information vs. uncertainty information) and the automation reliability (high vs.low) within participants. Participants interacted with a highly automated driving system while engaging in secondary tasks and were required to cooperate with the automation to drive safely. Quantile regressions and multilevel modeling showed that the presentation of uncertainty information increases the time to collision in the case of automation failure. Furthermore, the data indicated improved situation awareness and better knowledge of fallibility for the experimental group. Consequently, the automation with the uncertainty symbol received higher trust ratings and increased acceptance. The presentation of automation uncertaintythrough a symbol improves overall driver-automation cooperation. Most automated systems in driving could benefit from displaying reliability information. This display might improve the acceptance of fallible systems and further enhances driver-automation cooperation.

Uncertainty analysis of infinite homogeneous lead and sodium cooled fast reactors at beginning of life

Energy Technology Data Exchange (ETDEWEB)

Vanhanen, R., E-mail: risto.vanhanen@aalto.fi

2015-03-15

The objective of the present work is to estimate breeding ratio, radiation damage rate and minor actinide transmutation rate of infinite homogeneous lead and sodium cooled fast reactors. Uncertainty analysis is performed taking into account uncertainty in nuclear data and composition of the reactors. We use the recently released ENDF/B-VII.1 nuclear data library and restrict the work to the beginning of reactor life. We work under multigroup approximation. The Bondarenko method is used to acquire effective cross sections for the homogeneous reactor. Modeling error and numerical error are estimated. The adjoint sensitivity analysis is performed to calculate generalized adjoint fluxes for the responses. The generalized adjoint fluxes are used to calculate first order sensitivities of the responses to model parameters. The acquired sensitivities are used to propagate uncertainties in the input data to find out uncertainties in the responses. We show that the uncertainty in model parameters is the dominant source of uncertainty, followed by modeling error, input data precision and numerical error. The uncertainty due to composition of the reactor is low. We identify main sources of uncertainty and note that the low-fidelity evaluation of {sup 16}O is problematic due to lack of correlation between total and elastic reactions.

Uncertainty analysis of infinite homogeneous lead and sodium cooled fast reactors at beginning of life

International Nuclear Information System (INIS)

Vanhanen, R.

2015-01-01

The objective of the present work is to estimate breeding ratio, radiation damage rate and minor actinide transmutation rate of infinite homogeneous lead and sodium cooled fast reactors. Uncertainty analysis is performed taking into account uncertainty in nuclear data and composition of the reactors. We use the recently released ENDF/B-VII.1 nuclear data library and restrict the work to the beginning of reactor life. We work under multigroup approximation. The Bondarenko method is used to acquire effective cross sections for the homogeneous reactor. Modeling error and numerical error are estimated. The adjoint sensitivity analysis is performed to calculate generalized adjoint fluxes for the responses. The generalized adjoint fluxes are used to calculate first order sensitivities of the responses to model parameters. The acquired sensitivities are used to propagate uncertainties in the input data to find out uncertainties in the responses. We show that the uncertainty in model parameters is the dominant source of uncertainty, followed by modeling error, input data precision and numerical error. The uncertainty due to composition of the reactor is low. We identify main sources of uncertainty and note that the low-fidelity evaluation of 16 O is problematic due to lack of correlation between total and elastic reactions

Uncertainty in social dilemmas

OpenAIRE

Kwaadsteniet, Erik Willem de

2007-01-01

This dissertation focuses on social dilemmas, and more specifically, on environmental uncertainty in these dilemmas. Real-life social dilemma situations are often characterized by uncertainty. For example, fishermen mostly do not know the exact size of the fish population (i.e., resource size uncertainty). Several researchers have therefore asked themselves the question as to how such uncertainty influences people’s choice behavior. These researchers have repeatedly concluded that uncertainty...

Accounting for sensor calibration, data validation, measurement and sampling uncertainties in monitoring urban drainage systems.

Science.gov (United States)

Bertrand-Krajewski, J L; Bardin, J P; Mourad, M; Béranger, Y

2003-01-01

Assessing the functioning and the performance of urban drainage systems on both rainfall event and yearly time scales is usually based on online measurements of flow rates and on samples of influent effluent for some rainfall events per year. In order to draw pertinent scientific and operational conclusions from the measurement results, it is absolutely necessary to use appropriate methods and techniques in order to i) calibrate sensors and analytical methods, ii) validate raw data, iii) evaluate measurement uncertainties, iv) evaluate the number of rainfall events to sample per year in order to determine performance indicator with a given uncertainty. Based an previous work, the paper gives a synthetic review of required and techniques, and illustrates their application to storage and settling tanks. Experiments show that, controlled and careful experimental conditions, relative uncertainties are about 20% for flow rates in sewer pipes, 6-10% for volumes, 25-35% for TSS concentrations and loads, and 18-276% for TSS removal rates. In order to evaluate the annual pollutant interception efficiency of storage and settling tanks with a given uncertainty, efforts should first be devoted to decrease the sampling uncertainty by increasing the number of sampled events.

Uncertainty theory

CERN Document Server

Liu, Baoding

2015-01-01

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

Production scheduling of a lignite mine under quality and reserves uncertainty

International Nuclear Information System (INIS)

Galetakis, Michael; Roumpos, Christos; Alevizos, George; Vamvuka, Despina

2011-01-01

The effect of uncertainty sources to the stochastic optimization of the combined project of a new surface lignite mine exploitation and power plant operation for electricity generation is investigated. Major sources of uncertainty that were considered are the reserves and the quality of the lignite. Since probability distribution functions for these uncertainties were estimated during the detailed exploration phase of the deposit, the overall goal is then to determine the optimal capacity of the power plant and consequently the optimal production rate of the mine over the time. The optimization objective that was selected is the maximization of the net present value of the project. Emphasis is placed on the sensitivity analysis for the investigation of the effect of quality and reserves uncertainty on project optimization, on the mathematical formulation of risk attitude strategy and on increasing the efficiency of the optimization process by creating a limited set of feasible solutions applying empirical rules. The developed methodology was applied for the determination of the optimal annual production rate of a new surface lignite mine in the area of Ptolemais–Amynteon in Northern Greece. - Highlights: ► Quality and reserves uncertainty affects considerably the production scheduling. ► Stochastic optimization is greatly accelerated by incorporating Taylor's rule. ► Decisions can be made considering different risk level attitudes.

Uncertainties of exposure-related quantities in mammographic x-ray unit quality control

International Nuclear Information System (INIS)

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

2006-01-01

Breast screening programs operate in many countries with mammographic x-ray units subject to stringent quality control tests. These tests include the evaluation of quantities based on exposure measurements, such as half value layer, automatic exposure control reproducibility, average glandular dose, and radiation output rate. There are numerous error sources that contribute to the uncertainty of these exposure-related quantities, some of which are unique to the low energy x-ray spectrum produced by mammographic x-ray units. For each of these exposure-related quantities, the applicable error sources and their magnitudes vary, depending on the test equipment used to make the measurement, and whether or not relevant corrections have been applied. This study has identified and quantified a range of error sources that may be used to estimate the combined uncertainty of these exposure-related quantities, given the test equipment used and corrections applied. The uncertainty analysis uses methods described by the International Standards Organization's Guide to the Expression of Uncertainty in Measurement. Examples of how these error sources combine to give the uncertainty of the exposure-related quantities are presented. Using the best test equipment evaluated in this study, uncertainties of the four exposure-related quantities at the 95% confidence interval were found to be ±1.6% (half value layer), ±0.0008 (automatic exposure control reproducibility), ±2.3% (average glandular dose), and ±2.1% (radiation output rate). In some cases, using less precise test equipment or failing to apply corrections, resulted in uncertainties more than double in magnitude

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

Exchange rate policy

Directory of Open Access Journals (Sweden)

Plačkov Slađana

2013-01-01

Full Text Available Small oscillations of exchange rate certainly affect the loss of confidence in the currency (Serbian dinar, CSD and because of the shallow market even the smallest change in the supply and demand leads to a shift in exchange rate and brings uncertainty. Some economists suggest that the course should be linked to inflation and thus ensure predictable and stable exchange rates. Real exchange rate or slightly depressed exchange rate will encourage the competitiveness of exporters and perhaps ensure the development of new production lines which, in terms of overvalued exchange rate, had no economic justification. Fixed exchange rate will bring lower interest rates, lower risk and lower business uncertainty (uncertainty avoidance, but Serbia will also reduce foreign exchange reserves by following this trend. On the other hand, a completely free exchange rate, would lead to a (real fall of Serbian currency, which in a certain period would lead to a significant increase in exports, but the consequences for businessmen and citizens with loans pegged to the euro exchange rate, would be disastrous. We will pay special attention to the depreciation of the exchange rate, as it is generally favorable to the export competitiveness of Serbia and, on the other hand, it leads to an increase in debt servicing costs of the government as well as of the private sector. Oscillations of the dinar exchange rate, appreciation and depreciation, sometimes have disastrous consequences on the economy, investors, imports and exports. In subsequent work, we will observe the movement of the dinar exchange rate in Serbia, in the time interval 2009-2012, in order to strike a balance and maintain economic equilibrium. A movement of foreign currencies against the local currency is controlled in the foreign exchange market, so in case economic interests require, The National Bank of Serbia (NBS, on the basis of arbitrary criteria, can intervene in the market.

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

Energy Technology Data Exchange (ETDEWEB)

Newman, Jennifer F.; Clifton, Andrew

2017-03-08

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

Fuel cycle cost uncertainty from nuclear fuel cycle comparison

International Nuclear Information System (INIS)

Li, J.; McNelis, D.; Yim, M.S.

2013-01-01

This paper examined the uncertainty in fuel cycle cost (FCC) calculation by considering both model and parameter uncertainty. Four different fuel cycle options were compared in the analysis including the once-through cycle (OT), the DUPIC cycle, the MOX cycle and a closed fuel cycle with fast reactors (FR). The model uncertainty was addressed by using three different FCC modeling approaches with and without the time value of money consideration. The relative ratios of FCC in comparison to OT did not change much by using different modeling approaches. This observation was consistent with the results of the sensitivity study for the discount rate. Two different sets of data with uncertainty range of unit costs were used to address the parameter uncertainty of the FCC calculation. The sensitivity study showed that the dominating contributor to the total variance of FCC is the uranium price. In general, the FCC of OT was found to be the lowest followed by FR, MOX, and DUPIC. But depending on the uranium price, the FR cycle was found to have lower FCC over OT. The reprocessing cost was also found to have a major impact on FCC

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

Science.gov (United States)

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

2016-01-01

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

Mixed oxidizer hybrid propulsion system optimization under uncertainty using applied response surface methodology and Monte Carlo simulation

Science.gov (United States)

Whitehead, James Joshua

The analysis documented herein provides an integrated approach for the conduct of optimization under uncertainty (OUU) using Monte Carlo Simulation (MCS) techniques coupled with response surface-based methods for characterization of mixture-dependent variables. This novel methodology provides an innovative means of conducting optimization studies under uncertainty in propulsion system design. Analytic inputs are based upon empirical regression rate information obtained from design of experiments (DOE) mixture studies utilizing a mixed oxidizer hybrid rocket concept. Hybrid fuel regression rate was selected as the target response variable for optimization under uncertainty, with maximization of regression rate chosen as the driving objective. Characteristic operational conditions and propellant mixture compositions from experimental efforts conducted during previous foundational work were combined with elemental uncertainty estimates as input variables. Response surfaces for mixture-dependent variables and their associated uncertainty levels were developed using quadratic response equations incorporating single and two-factor interactions. These analysis inputs, response surface equations and associated uncertainty contributions were applied to a probabilistic MCS to develop dispersed regression rates as a function of operational and mixture input conditions within design space. Illustrative case scenarios were developed and assessed using this analytic approach including fully and partially constrained operational condition sets over all of design mixture space. In addition, optimization sets were performed across an operationally representative region in operational space and across all investigated mixture combinations. These scenarios were selected as representative examples relevant to propulsion system optimization, particularly for hybrid and solid rocket platforms. Ternary diagrams, including contour and surface plots, were developed and utilized to aid in

Parametric uncertainty modeling for robust control

DEFF Research Database (Denmark)

Rasmussen, K.H.; Jørgensen, Sten Bay

1999-01-01

The dynamic behaviour of a non-linear process can often be approximated with a time-varying linear model. In the presented methodology the dynamics is modeled non-conservatively as parametric uncertainty in linear lime invariant models. The obtained uncertainty description makes it possible...... to perform robustness analysis on a control system using the structured singular value. The idea behind the proposed method is to fit a rational function to the parameter variation. The parameter variation can then be expressed as a linear fractional transformation (LFT), It is discussed how the proposed...... point changes. It is shown that a diagonal PI control structure provides robust performance towards variations in feed flow rate or feed concentrations. However including both liquid and vapor flow delays robust performance specifications cannot be satisfied with this simple diagonal control structure...

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....

Radon measurements: the sources of uncertainties

International Nuclear Information System (INIS)

Zhukovsky, Michael; Onischenko, Alexandra; Bastrikov, Vladislav

2008-01-01

uncertainties for retrospective measurements conducted by surface traps techniques can be divided in two groups: errors of surface 210 Pb ( 210 Po) activity measurements and uncertainties of transfer from 210 Pb surface activity in glass objects to average radon concentration during this object exposure. The sources of 210 Pb ( 210 Po) surface activity measurement uncertainties are: errors in the calibration of energy-angle dependence of alpha-particles registration efficiency; random Poisson errors during measurements, the influence of background alpha radiation from the glass; unknown U-Ra-Th activity ratio in the glass, nonuniform 210 Po distribution on the surface of glass object. Uncertainty factors of Jacobi model for connection of 210 Pb surface activity and average radon concentration are: unknown aerosol concentration, ventilation rate, surface/volume ratio in investigated room, long term radon variations, aerosol deposition rates and errors in the age estimation of glass object. It is shown that total measurement error of surface trap retrospective technique can be decreased to 35%. The analysis of errors for grab sampling measurements, charcoal canisters and track detectors are presented in the full paper

Uncertainty and sensitivity analysis of the nuclear fuel thermal behavior

Energy Technology Data Exchange (ETDEWEB)

Boulore, A., E-mail: antoine.boulore@cea.fr [Commissariat a l' Energie Atomique (CEA), DEN, Fuel Research Department, 13108 Saint-Paul-lez-Durance (France); Struzik, C. [Commissariat a l' Energie Atomique (CEA), DEN, Fuel Research Department, 13108 Saint-Paul-lez-Durance (France); Gaudier, F. [Commissariat a l' Energie Atomique (CEA), DEN, Systems and Structure Modeling Department, 91191 Gif-sur-Yvette (France)

2012-12-15

Highlights: Black-Right-Pointing-Pointer A complete quantitative method for uncertainty propagation and sensitivity analysis is applied. Black-Right-Pointing-Pointer The thermal conductivity of UO{sub 2} is modeled as a random variable. Black-Right-Pointing-Pointer The first source of uncertainty is the linear heat rate. Black-Right-Pointing-Pointer The second source of uncertainty is the thermal conductivity of the fuel. - Abstract: In the global framework of nuclear fuel behavior simulation, the response of the models describing the physical phenomena occurring during the irradiation in reactor is mainly conditioned by the confidence in the calculated temperature of the fuel. Amongst all parameters influencing the temperature calculation in our fuel rod simulation code (METEOR V2), several sources of uncertainty have been identified as being the most sensitive: thermal conductivity of UO{sub 2}, radial distribution of power in the fuel pellet, local linear heat rate in the fuel rod, geometry of the pellet and thermal transfer in the gap. Expert judgment and inverse methods have been used to model the uncertainty of these parameters using theoretical distributions and correlation matrices. Propagation of these uncertainties in the METEOR V2 code using the URANIE framework and a Monte-Carlo technique has been performed in different experimental irradiations of UO{sub 2} fuel. At every time step of the simulated experiments, we get a temperature statistical distribution which results from the initial distributions of the uncertain parameters. We then can estimate confidence intervals of the calculated temperature. In order to quantify the sensitivity of the calculated temperature to each of the uncertain input parameters and data, we have also performed a sensitivity analysis using the Sobol' indices at first order.

Quantifying the uncertainty of wave energy conversion device cost for policy appraisal: An Irish case study

International Nuclear Information System (INIS)

Farrell, Niall; Donoghue, Cathal O’; Morrissey, Karyn

2015-01-01

Wave Energy Conversion (WEC) devices are at a pre-commercial stage of development with feasibility studies sensitive to uncertainties surrounding assumed input costs. This may affect decision making. This paper analyses the impact these uncertainties may have on investor, developer and policymaker decisions using an Irish case study. Calibrated to data present in the literature, a probabilistic methodology is shown to be an effective means to carry this out. Value at Risk (VaR) and Conditional Value at Risk (CVaR) metrics are used to quantify the certainty of achieving a given cost or return on investment. We analyse the certainty of financial return provided by the proposed Irish Feed-in Tariff (FiT) policy. The influence of cost reduction through bulk discount is also discussed, with cost reduction targets for developers identified. Uncertainty is found to have a greater impact on the profitability of smaller installations and those subject to lower rates of cost reduction. This paper emphasises that a premium is required to account for cost uncertainty when setting FiT rates. By quantifying uncertainty, a means to specify an efficient premium is presented. - Highlights: • Probabilistic model quantifies uncertainty for wave energy feasibility analyses. • Methodology presented and applied to an Irish case study. • A feed-in tariff premium of 3–4 c/kWh required to account for cost uncertainty. • Sensitivity of uncertainty and cost to rates of technological change analysed. • Use of probabilistic model for investors and developers also demonstrated

Uncertainties in the production of p nuclides in thermonuclear supernovae determined by Monte Carlo variations

Science.gov (United States)

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

2018-03-01

Thermonuclear supernovae originating from the explosion of a white dwarf accreting mass from a companion star have been suggested as a site for the production of p nuclides. Such nuclei are produced during the explosion, in layers enriched with seed nuclei coming from prior strong s processing. These seeds are transformed into proton-richer isotopes mainly by photodisintegration reactions. Several thousand trajectories from a 2D explosion model were used in a Monte Carlo approach. Temperature-dependent uncertainties were assigned individually to thousands of rates varied simultaneously in post-processing in an extended nuclear reaction network. The uncertainties in the final nuclear abundances originating from uncertainties in the astrophysical reaction rates were determined. In addition to the 35 classical p nuclides, abundance uncertainties were also determined for the radioactive nuclides 92Nb, 97, 98Tc, 146Sm, and for the abundance ratios Y(92Mo)/Y(94Mo), Y(92Nb)/Y(92Mo), Y(97Tc)/Y(98Ru), Y(98Tc)/Y(98Ru), and Y(146Sm)/Y(144Sm), important for Galactic Chemical Evolution studies. Uncertainties found were generally lower than a factor of 2, although most nucleosynthesis flows mainly involve predicted rates with larger uncertainties. The main contribution to the total uncertainties comes from a group of trajectories with high peak density originating from the interior of the exploding white dwarf. The distinction between low-density and high-density trajectories allows more general conclusions to be drawn, also applicable to other simulations of white dwarf explosions.

Status of XSUSA for sampling based nuclear data uncertainty and sensitivity analysis

International Nuclear Information System (INIS)

Zwermann, W.; Gallner, L.; Klein, M.; Krzydacz-Hausmann; Pasichnyk, I.; Pautz, A.; Velkov, K.

2013-01-01

In the present contribution, an overview of the sampling based XSUSA method for sensitivity and uncertainty analysis with respect to nuclear data is given. The focus is on recent developments and applications of XSUSA. These applications include calculations for critical assemblies, fuel assembly depletion calculations, and steady state as well as transient reactor core calculations. The analyses are partially performed in the framework of international benchmark working groups (UACSA - Uncertainty Analyses for Criticality Safety Assessment, UAM - Uncertainty Analysis in Modelling). It is demonstrated that particularly for full-scale reactor calculations the influence of the nuclear data uncertainties on the results can be substantial. For instance, for the radial fission rate distributions of mixed UO 2 /MOX light water reactor cores, the 2σ uncertainties in the core centre and periphery can reach values exceeding 10%. For a fast transient, the resulting time behaviour of the reactor power was covered by a wide uncertainty band. Overall, the results confirm the necessity of adding systematic uncertainty analyses to best-estimate reactor calculations. (authors)

Compilation of information on uncertainties involved in deposition modeling

International Nuclear Information System (INIS)

Lewellen, W.S.; Varma, A.K.; Sheng, Y.P.

1985-04-01

The current generation of dispersion models contains very simple parameterizations of deposition processes. The analysis here looks at the physical mechanisms governing these processes in an attempt to see if more valid parameterizations are available and what level of uncertainty is involved in either these simple parameterizations or any more advanced parameterization. The report is composed of three parts. The first, on dry deposition model sensitivity, provides an estimate of the uncertainty existing in current estimates of the deposition velocity due to uncertainties in independent variables such as meteorological stability, particle size, surface chemical reactivity and canopy structure. The range of uncertainty estimated for an appropriate dry deposition velocity for a plume generated by a nuclear power plant accident is three orders of magnitude. The second part discusses the uncertainties involved in precipitation scavenging rates for effluents resulting from a nuclear reactor accident. The conclusion is that major uncertainties are involved both as a result of the natural variability of the atmospheric precipitation process and due to our incomplete understanding of the underlying process. The third part involves a review of the important problems associated with modeling the interaction between the atmosphere and a forest. It gives an indication of the magnitude of the problem involved in modeling dry deposition in such environments. Separate analytics have been done for each section and are contained in the EDB

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

Science.gov (United States)

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

2009-01-01

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

Bayesian analysis for uncertainty estimation of a canopy transpiration model

Science.gov (United States)

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

2007-04-01

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

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

Science.gov (United States)

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

2012-01-01

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

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

International Nuclear Information System (INIS)

Glaeser, H.

2008-01-01

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

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

Science.gov (United States)

Rains, Stephen A; Tukachinsky, Riva

2015-01-01

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

Conditional uncertainty principle

Science.gov (United States)

Gour, Gilad; Grudka, Andrzej; Horodecki, Michał; Kłobus, Waldemar; Łodyga, Justyna; Narasimhachar, Varun

2018-04-01

We develop a general operational framework that formalizes the concept of conditional uncertainty in a measure-independent fashion. Our formalism is built upon a mathematical relation which we call conditional majorization. We define conditional majorization and, for the case of classical memory, we provide its thorough characterization in terms of monotones, i.e., functions that preserve the partial order under conditional majorization. We demonstrate the application of this framework by deriving two types of memory-assisted uncertainty relations, (1) a monotone-based conditional uncertainty relation and (2) a universal measure-independent conditional uncertainty relation, both of which set a lower bound on the minimal uncertainty that Bob has about Alice's pair of incompatible measurements, conditioned on arbitrary measurement that Bob makes on his own system. We next compare the obtained relations with their existing entropic counterparts and find that they are at least independent.

Uncertainties in container failure time predictions

International Nuclear Information System (INIS)

Williford, R.E.

1990-01-01

Stochastic variations in the local chemical environment of a geologic waste repository can cause corresponding variations in container corrosion rates and failure times, and thus in radionuclide release rates. This paper addresses how well the future variations in repository chemistries must be known in order to predict container failure times that are bounded by a finite time period within the repository lifetime. Preliminary results indicate that a 5000 year scatter in predicted container failure times requires that repository chemistries be known to within ±10% over the repository lifetime. These are small uncertainties compared to current estimates. 9 refs., 3 figs

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

International Nuclear Information System (INIS)

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

2009-01-01

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

Uncertainty and Cognitive Control

Directory of Open Access Journals (Sweden)

Faisal eMushtaq

2011-10-01

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

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, probability and information-gaps

International Nuclear Information System (INIS)

Ben-Haim, Yakov

2004-01-01

This paper discusses two main ideas. First, we focus on info-gap uncertainty, as distinct from probability. Info-gap theory is especially suited for modelling and managing uncertainty in system models: we invest all our knowledge in formulating the best possible model; this leaves the modeller with very faulty and fragmentary information about the variation of reality around that optimal model. Second, we examine the interdependence between uncertainty modelling and decision-making. Good uncertainty modelling requires contact with the end-use, namely, with the decision-making application of the uncertainty model. The most important avenue of uncertainty-propagation is from initial data- and model-uncertainties into uncertainty in the decision-domain. Two questions arise. Is the decision robust to the initial uncertainties? Is the decision prone to opportune windfall success? We apply info-gap robustness and opportunity functions to the analysis of representation and propagation of uncertainty in several of the Sandia Challenge Problems

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

Science.gov (United States)

Fischer, Andreas

2016-11-01

Optical flow velocity measurements are important for understanding the complex behavior of flows. Although a huge variety of methods exist, they are either based on a Doppler or a time-of-flight measurement principle. Doppler velocimetry evaluates the velocity-dependent frequency shift of light scattered at a moving particle, whereas time-of-flight velocimetry evaluates the traveled distance of a scattering particle per time interval. Regarding the aim of achieving a minimal measurement uncertainty, it is unclear if one principle allows to achieve lower uncertainties or if both principles can achieve equal uncertainties. For this reason, the natural, fundamental uncertainty limit according to Heisenberg's uncertainty principle is derived for Doppler and time-of-flight measurement principles, respectively. The obtained limits of the velocity uncertainty are qualitatively identical showing, e.g., a direct proportionality for the absolute value of the velocity to the power of 32 and an indirect proportionality to the square root of the scattered light power. Hence, both measurement principles have identical potentials regarding the fundamental uncertainty limit due to the quantum mechanical behavior of photons. This fundamental limit can be attained (at least asymptotically) in reality either with Doppler or time-of-flight methods, because the respective Cramér-Rao bounds for dominating photon shot noise, which is modeled as white Poissonian noise, are identical with the conclusions from Heisenberg's uncertainty principle.

Water supply infrastructure planning under multiple uncertainties: A differentiated approach

Science.gov (United States)

Fletcher, S.; Strzepek, K.

2017-12-01

Many water planners face increased pressure on water supply systems from increasing demands from population and economic growth in combination with uncertain water supply. Supply uncertainty arises from short-term climate variability and long-term climate change as well as uncertainty in groundwater availability. Social and economic uncertainties - such as sectoral competition for water, food and energy security, urbanization, and environmental protection - compound physical uncertainty. Further, the varying risk aversion of stakeholders and water managers makes it difficult to assess the necessity of expensive infrastructure investments to reduce risk. We categorize these uncertainties on two dimensions: whether they can be updated over time by collecting additional information, and whether the uncertainties can be described probabilistically or are "deep" uncertainties whose likelihood is unknown. Based on this, we apply a decision framework that combines simulation for probabilistic uncertainty, scenario analysis for deep uncertainty, and multi-stage decision analysis for uncertainties that are reduced over time with additional information. In light of these uncertainties and the investment costs of large infrastructure, we propose the assessment of staged, modular infrastructure and information updating as a hedge against risk. We apply this framework to cases in Melbourne, Australia and Riyadh, Saudi Arabia. Melbourne is a surface water system facing uncertain population growth and variable rainfall and runoff. A severe drought from 1997 to 2009 prompted investment in a 150 MCM/y reverse osmosis desalination plan with a capital cost of 3.5 billion. Our analysis shows that flexible design in which a smaller portion of capacity is developed initially with the option to add modular capacity in the future can mitigate uncertainty and reduce the expected lifetime costs by up to 1 billion. In Riyadh, urban water use relies on fossil groundwater aquifers and

A Variation on Uncertainty Principle and Logarithmic Uncertainty Principle for Continuous Quaternion Wavelet Transforms

Directory of Open Access Journals (Sweden)

Mawardi Bahri

2017-01-01

Full Text Available The continuous quaternion wavelet transform (CQWT is a generalization of the classical continuous wavelet transform within the context of quaternion algebra. First of all, we show that the directional quaternion Fourier transform (QFT uncertainty principle can be obtained using the component-wise QFT uncertainty principle. Based on this method, the directional QFT uncertainty principle using representation of polar coordinate form is easily derived. We derive a variation on uncertainty principle related to the QFT. We state that the CQWT of a quaternion function can be written in terms of the QFT and obtain a variation on uncertainty principle related to the CQWT. Finally, we apply the extended uncertainty principles and properties of the CQWT to establish logarithmic uncertainty principles related to generalized transform.

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.

Decision-making under great uncertainty

International Nuclear Information System (INIS)

Hansson, S.O.

1992-01-01

Five types of decision-uncertainty are distinguished: uncertainty of consequences, of values, of demarcation, of reliance, and of co-ordination. Strategies are proposed for each type of uncertainty. The general conclusion is that it is meaningful for decision theory to treat cases with greater uncertainty than the textbook case of 'decision-making under uncertainty'. (au)

Detailed modeling of the statistical uncertainty of Thomson scattering measurements

International Nuclear Information System (INIS)

Morton, L A; Parke, E; Hartog, D J Den

2013-01-01

The uncertainty of electron density and temperature fluctuation measurements is determined by statistical uncertainty introduced by multiple noise sources. In order to quantify these uncertainties precisely, a simple but comprehensive model was made of the noise sources in the MST Thomson scattering system and of the resulting variance in the integrated scattered signals. The model agrees well with experimental and simulated results. The signal uncertainties are then used by our existing Bayesian analysis routine to find the most likely electron temperature and density, with confidence intervals. In the model, photonic noise from scattered light and plasma background light is multiplied by the noise enhancement factor (F) of the avalanche photodiode (APD). Electronic noise from the amplifier and digitizer is added. The amplifier response function shapes the signal and induces correlation in the noise. The data analysis routine fits a characteristic pulse to the digitized signals from the amplifier, giving the integrated scattered signals. A finite digitization rate loses information and can cause numerical integration error. We find a formula for the variance of the scattered signals in terms of the background and pulse amplitudes, and three calibration constants. The constants are measured easily under operating conditions, resulting in accurate estimation of the scattered signals' uncertainty. We measure F ≈ 3 for our APDs, in agreement with other measurements for similar APDs. This value is wavelength-independent, simplifying analysis. The correlated noise we observe is reproduced well using a Gaussian response function. Numerical integration error can be made negligible by using an interpolated characteristic pulse, allowing digitization rates as low as the detector bandwidth. The effect of background noise is also determined

Reactor pressure vessels safety and reliability - certainty and uncertainty

International Nuclear Information System (INIS)

O'Neil, R.

1977-01-01

In the paper, it is suggested that the hazard to the population which would result from vessel failure rate of the order of 10 -6 to 10 -7 per vessel year could be acceptable to society on the basis of other natural and man-made risks. The paper considers the problems of demonstrating safety by calculation based on fracture mechanics, and indicates some of the uncertainties, and inconsistencies in the theory, particularly the effect of cracks in locally degraded volumes of material. The phenomenon of crack arrest is considered, and attention is drawn to the uncertainties as indicated at least by some tests. There is need for speedy resolution of this problem. The uncertainties in material properties, heat treatment and residual stresses are considered, and a proposed upper limit for residual defects ('original sin') is proposed. (orig.) [de

DS02 uncertainty analysis

International Nuclear Information System (INIS)

Kaul, Dean C.; Egbert, Stephen D.; Woolson, William A.

2005-01-01

In order to avoid the pitfalls that so discredited DS86 and its uncertainty estimates, and to provide DS02 uncertainties that are both defensible and credible, this report not only presents the ensemble uncertainties assembled from uncertainties in individual computational elements and radiation dose components but also describes how these relate to comparisons between observed and computed quantities at critical intervals in the computational process. These comparisons include those between observed and calculated radiation free-field components, where observations include thermal- and fast-neutron activation and gamma-ray thermoluminescence, which are relevant to the estimated systematic uncertainty for DS02. The comparisons also include those between calculated and observed survivor shielding, where the observations consist of biodosimetric measurements for individual survivors, which are relevant to the estimated random uncertainty for DS02. (J.P.N.)

Estimates of bias and uncertainty in recorded external dose

International Nuclear Information System (INIS)

Fix, J.J.; Gilbert, E.S.; Baumgartner, W.V.

1994-10-01

A study is underway to develop an approach to quantify bias and uncertainty in recorded dose estimates for workers at the Hanford Site based on personnel dosimeter results. This paper focuses on selected experimental studies conducted to better define response characteristics of Hanford dosimeters. The study is more extensive than the experimental studies presented in this paper and includes detailed consideration and evaluation of other sources of bias and uncertainty. Hanford worker dose estimates are used in epidemiologic studies of nuclear workers. A major objective of these studies is to provide a direct assessment of the carcinogenic risk of exposure to ionizing radiation at low doses and dose rates. Considerations of bias and uncertainty in the recorded dose estimates are important in the conduct of this work. The method developed for use with Hanford workers can be considered an elaboration of the approach used to quantify bias and uncertainty in estimated doses for personnel exposed to radiation as a result of atmospheric testing of nuclear weapons between 1945 and 1962. This approach was first developed by a National Research Council (NRC) committee examining uncertainty in recorded film badge doses during atmospheric tests (NRC 1989). It involved quantifying both bias and uncertainty from three sources (i.e., laboratory, radiological, and environmental) and then combining them to obtain an overall assessment. Sources of uncertainty have been evaluated for each of three specific Hanford dosimetry systems (i.e., the Hanford two-element film dosimeter, 1944-1956; the Hanford multi-element film dosimeter, 1957-1971; and the Hanford multi-element TLD, 1972-1993) used to estimate personnel dose throughout the history of Hanford operations. Laboratory, radiological, and environmental sources of bias and uncertainty have been estimated based on historical documentation and, for angular response, on selected laboratory measurements

Application of a Novel Dose-Uncertainty Model for Dose-Uncertainty Analysis in Prostate Intensity-Modulated Radiotherapy

International Nuclear Information System (INIS)

Jin Hosang; Palta, Jatinder R.; Kim, You-Hyun; Kim, Siyong

2010-01-01

Purpose: To analyze dose uncertainty using a previously published dose-uncertainty model, and to assess potential dosimetric risks existing in prostate intensity-modulated radiotherapy (IMRT). Methods and Materials: The dose-uncertainty model provides a three-dimensional (3D) dose-uncertainty distribution in a given confidence level. For 8 retrospectively selected patients, dose-uncertainty maps were constructed using the dose-uncertainty model at the 95% CL. In addition to uncertainties inherent to the radiation treatment planning system, four scenarios of spatial errors were considered: machine only (S1), S1 + intrafraction, S1 + interfraction, and S1 + both intrafraction and interfraction errors. To evaluate the potential risks of the IMRT plans, three dose-uncertainty-based plan evaluation tools were introduced: confidence-weighted dose-volume histogram, confidence-weighted dose distribution, and dose-uncertainty-volume histogram. Results: Dose uncertainty caused by interfraction setup error was more significant than that of intrafraction motion error. The maximum dose uncertainty (95% confidence) of the clinical target volume (CTV) was smaller than 5% of the prescribed dose in all but two cases (13.9% and 10.2%). The dose uncertainty for 95% of the CTV volume ranged from 1.3% to 2.9% of the prescribed dose. Conclusions: The dose uncertainty in prostate IMRT could be evaluated using the dose-uncertainty model. Prostate IMRT plans satisfying the same plan objectives could generate a significantly different dose uncertainty because a complex interplay of many uncertainty sources. The uncertainty-based plan evaluation contributes to generating reliable and error-resistant treatment plans.

Ruminations On NDA Measurement Uncertainty Compared TO DA Uncertainty

International Nuclear Information System (INIS)

Salaymeh, S.; Ashley, W.; Jeffcoat, R.

2010-01-01

It is difficult to overestimate the importance that physical measurements performed with nondestructive assay instruments play throughout the nuclear fuel cycle. They underpin decision making in many areas and support: criticality safety, radiation protection, process control, safeguards, facility compliance, and waste measurements. No physical measurement is complete or indeed meaningful, without a defensible and appropriate accompanying statement of uncertainties and how they combine to define the confidence in the results. The uncertainty budget should also be broken down in sufficient detail suitable for subsequent uses to which the nondestructive assay (NDA) results will be applied. Creating an uncertainty budget and estimating the total measurement uncertainty can often be an involved process, especially for non routine situations. This is because data interpretation often involves complex algorithms and logic combined in a highly intertwined way. The methods often call on a multitude of input data subject to human oversight. These characteristics can be confusing and pose a barrier to developing and understanding between experts and data consumers. ASTM subcommittee C26-10 recognized this problem in the context of how to summarize and express precision and bias performance across the range of standards and guides it maintains. In order to create a unified approach consistent with modern practice and embracing the continuous improvement philosophy a consensus arose to prepare a procedure covering the estimation and reporting of uncertainties in non destructive assay of nuclear materials. This paper outlines the needs analysis, objectives and on-going development efforts. In addition to emphasizing some of the unique challenges and opportunities facing the NDA community we hope this article will encourage dialog and sharing of best practice and furthermore motivate developers to revisit the treatment of measurement uncertainty.

RUMINATIONS ON NDA MEASUREMENT UNCERTAINTY COMPARED TO DA UNCERTAINTY

Energy Technology Data Exchange (ETDEWEB)

Salaymeh, S.; Ashley, W.; Jeffcoat, R.

2010-06-17

It is difficult to overestimate the importance that physical measurements performed with nondestructive assay instruments play throughout the nuclear fuel cycle. They underpin decision making in many areas and support: criticality safety, radiation protection, process control, safeguards, facility compliance, and waste measurements. No physical measurement is complete or indeed meaningful, without a defensible and appropriate accompanying statement of uncertainties and how they combine to define the confidence in the results. The uncertainty budget should also be broken down in sufficient detail suitable for subsequent uses to which the nondestructive assay (NDA) results will be applied. Creating an uncertainty budget and estimating the total measurement uncertainty can often be an involved process, especially for non routine situations. This is because data interpretation often involves complex algorithms and logic combined in a highly intertwined way. The methods often call on a multitude of input data subject to human oversight. These characteristics can be confusing and pose a barrier to developing and understanding between experts and data consumers. ASTM subcommittee C26-10 recognized this problem in the context of how to summarize and express precision and bias performance across the range of standards and guides it maintains. In order to create a unified approach consistent with modern practice and embracing the continuous improvement philosophy a consensus arose to prepare a procedure covering the estimation and reporting of uncertainties in non destructive assay of nuclear materials. This paper outlines the needs analysis, objectives and on-going development efforts. In addition to emphasizing some of the unique challenges and opportunities facing the NDA community we hope this article will encourage dialog and sharing of best practice and furthermore motivate developers to revisit the treatment of measurement uncertainty.

Uncertainty study of the PWR pressure vessel fluence. Adjustment of the nuclear data base

International Nuclear Information System (INIS)

Kodeli, I.A.

1994-01-01

The code system devoted to the calculation of the sensitivity and uncertainty of of the neutron flux and reaction rates calculated by the transport codes, has been developed. Adjustment of the basic data to experimental results can be performed as well. Various sources of uncertainties can be taken into account, such as those due to the uncertainties in the cross-sections, response functions, fission spectrum and space distribution of neutron source, geometry and material composition uncertainties... One -As well as two- dimensional analysis can be performed. Linear perturbation theory is applied. The code system is sufficiently general to be used for various analysis in the fields of fission and fusion. The principal objective of our studies concerns the capsule dosimetry study realized in the framework of the 900 MWe PWR pressure vessel surveillance program. The analysis indicates that the present calculations, performed by the code TRIPOLI-2, using the ENDF/B-IV based, non-perturbed neutron cross-section library in 315 energy groups, allows to estimate the neutron flux and the reaction rates in the surveillance capsules and in the most calculated and measured reaction rates permits to reduce these uncertainties. The results obtained with the adjusted iron cross-sections, response functions and fission spectrum show that the agreement between the calculation and the experiment was improved to become within 10% approximately. The neutron flux deduced from the experiment is then extrapolated from the capsule to the most exposed pressure vessel location using the calculated lead factor. The uncertainty in this factor was estimated to be about 7%. (author). 39 refs., 52 figs., 30 tabs

Analysis of uncertainties in the measurements of absorbed dose to water in a secondary standard dosimetry laboratory (SSDL) 60Cobalt

International Nuclear Information System (INIS)

Silva, Cosme Norival Mello da; Rosado, Paulo Henrique Goncalves

2011-01-01

The National Metrology Laboratory of Ionizing Radiation (LNMRI) is the laboratory designated by INMETRO in the field of Metrology of ionizing radiation and is a Secondary Standard Dosimetry Laboratory (SSDL). One of its guidelines is to maintain and disseminate LNMRI absorbed dose in water used as a national standard dosimetry in radiotherapy. For this pattern is metrologically acceptable accuracy and uncertainties should be assessed over time. The objective of this study is to analyze the uncertainties involved in determining the absorbed dose rate in water and standard uncertainty of absorbed dose calibration in water from a clinical dosimeter. The largest sources of uncertainty in determining the rate of absorbed dose in water are due to: calibration coefficient of the calibration certificate supplied by the BIPM, electrometer calibration, camber stability over time, variation of pressure and humidity, strong dependence and non-uniformity of the field. The expanded uncertainty is 0.94% for k = 2. For the calibration standard uncertainty of absorbed dose in water of a dosimeter in a clinical a major source of uncertainty is due to the absorbed dose rate in water (0.94%). The value of expanded uncertainty of calibrating a clinical dosimeter is 1.2% for k = 2. (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.

Uncertainty and sensitivity analysis: Mathematical model of coupled heat and mass transfer for a contact baking process

DEFF Research Database (Denmark)

Feyissa, Aberham Hailu; Gernaey, Krist; Adler-Nissen, Jens

2012-01-01

to uncertainty in the model predictions. The aim of the current paper is to address this uncertainty challenge in the modelling of food production processes using a combination of uncertainty and sensitivity analysis, where the uncertainty analysis and global sensitivity analysis were applied to a heat and mass......Similar to other processes, the modelling of heat and mass transfer during food processing involves uncertainty in the values of input parameters (heat and mass transfer coefficients, evaporation rate parameters, thermo-physical properties, initial and boundary conditions) which leads...

Embracing uncertainty in applied ecology.

Science.gov (United States)

Milner-Gulland, E J; Shea, K

2017-12-01

Applied ecologists often face uncertainty that hinders effective decision-making.Common traps that may catch the unwary are: ignoring uncertainty, acknowledging uncertainty but ploughing on, focussing on trivial uncertainties, believing your models, and unclear objectives.We integrate research insights and examples from a wide range of applied ecological fields to illustrate advances that are generally underused, but could facilitate ecologists' ability to plan and execute research to support management.Recommended approaches to avoid uncertainty traps are: embracing models, using decision theory, using models more effectively, thinking experimentally, and being realistic about uncertainty. Synthesis and applications . Applied ecologists can become more effective at informing management by using approaches that explicitly take account of uncertainty.

Decision-Making under Criteria Uncertainty

Science.gov (United States)

Kureychik, V. M.; Safronenkova, I. B.

2018-05-01

Uncertainty is an essential part of a decision-making procedure. The paper deals with the problem of decision-making under criteria uncertainty. In this context, decision-making under uncertainty, types and conditions of uncertainty were examined. The decision-making problem under uncertainty was formalized. A modification of the mathematical decision support method under uncertainty via ontologies was proposed. A critical distinction of the developed method is ontology usage as its base elements. The goal of this work is a development of a decision-making method under criteria uncertainty with the use of ontologies in the area of multilayer board designing. This method is oriented to improvement of technical-economic values of the examined domain.

Physical Uncertainty Bounds (PUB)

Energy Technology Data Exchange (ETDEWEB)

Vaughan, Diane Elizabeth [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Preston, Dean L. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2015-03-19

This paper introduces and motivates the need for a new methodology for determining upper bounds on the uncertainties in simulations of engineered systems due to limited fidelity in the composite continuum-level physics models needed to simulate the systems. We show that traditional uncertainty quantification methods provide, at best, a lower bound on this uncertainty. We propose to obtain bounds on the simulation uncertainties by first determining bounds on the physical quantities or processes relevant to system performance. By bounding these physics processes, as opposed to carrying out statistical analyses of the parameter sets of specific physics models or simply switching out the available physics models, one can obtain upper bounds on the uncertainties in simulated quantities of interest.

Uncertainty Propagation in OMFIT

Science.gov (United States)

Smith, Sterling; Meneghini, Orso; Sung, Choongki

2017-10-01

A rigorous comparison of power balance fluxes and turbulent model fluxes requires the propagation of uncertainties in the kinetic profiles and their derivatives. Making extensive use of the python uncertainties package, the OMFIT framework has been used to propagate covariant uncertainties to provide an uncertainty in the power balance calculation from the ONETWO code, as well as through the turbulent fluxes calculated by the TGLF code. The covariant uncertainties arise from fitting 1D (constant on flux surface) density and temperature profiles and associated random errors with parameterized functions such as a modified tanh. The power balance and model fluxes can then be compared with quantification of the uncertainties. No effort is made at propagating systematic errors. A case study will be shown for the effects of resonant magnetic perturbations on the kinetic profiles and fluxes at the top of the pedestal. A separate attempt at modeling the random errors with Monte Carlo sampling will be compared to the method of propagating the fitting function parameter covariant uncertainties. Work supported by US DOE under DE-FC02-04ER54698, DE-FG2-95ER-54309, DE-SC 0012656.

In uncertainty we trust: a median voter model with risk aversion

Directory of Open Access Journals (Sweden)

Pavel A. Yakovlev

2011-12-01

Full Text Available The principal-agent problem and uncertainty are some of the key factors affecting financial and political markets. Fear of the unknown plays an important role in human decision making, including voting. This article describes a theoretical model where voter risk aversion towards uncertainty gives political incumbents a significant advantage over their challengers, exacerbating the principal-agent problem between voters and legislators. The model presented predicts that a rise in voter uncertainty concerning the challenger allows the incumbent to deviate from the median voter’s policy preference without losing the election. This model reconciles the paradoxical coexistence of ideological shirking and high incumbent reelection rates without abandoning the elegant median voter framework.

Evaluation of uncertainty in dosimetry of irradiator system

International Nuclear Information System (INIS)

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

2005-01-01

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

Stereo-particle image velocimetry uncertainty quantification

International Nuclear Information System (INIS)

Bhattacharya, Sayantan; Vlachos, Pavlos P; Charonko, John J

2017-01-01

Particle image velocimetry (PIV) measurements are subject to multiple elemental error sources and thus estimating overall measurement uncertainty is challenging. Recent advances have led to a posteriori uncertainty estimation methods for planar two-component PIV. However, no complete methodology exists for uncertainty quantification in stereo PIV. In the current work, a comprehensive framework is presented to quantify the uncertainty stemming from stereo registration error and combine it with the underlying planar velocity uncertainties. The disparity in particle locations of the dewarped images is used to estimate the positional uncertainty of the world coordinate system, which is then propagated to the uncertainty in the calibration mapping function coefficients. Next, the calibration uncertainty is combined with the planar uncertainty fields of the individual cameras through an uncertainty propagation equation and uncertainty estimates are obtained for all three velocity components. The methodology was tested with synthetic stereo PIV data for different light sheet thicknesses, with and without registration error, and also validated with an experimental vortex ring case from 2014 PIV challenge. Thorough sensitivity analysis was performed to assess the relative impact of the various parameters to the overall uncertainty. The results suggest that in absence of any disparity, the stereo PIV uncertainty prediction method is more sensitive to the planar uncertainty estimates than to the angle uncertainty, although the latter is not negligible for non-zero disparity. Overall the presented uncertainty quantification framework showed excellent agreement between the error and uncertainty RMS values for both the synthetic and the experimental data and demonstrated reliable uncertainty prediction coverage. This stereo PIV uncertainty quantification framework provides the first comprehensive treatment on the subject and potentially lays foundations applicable to volumetric

Methodologies of Uncertainty Propagation Calculation

International Nuclear Information System (INIS)

Chojnacki, Eric

2002-01-01

After recalling the theoretical principle and the practical difficulties of the methodologies of uncertainty propagation calculation, the author discussed how to propagate input uncertainties. He said there were two kinds of input uncertainty: - variability: uncertainty due to heterogeneity, - lack of knowledge: uncertainty due to ignorance. It was therefore necessary to use two different propagation methods. He demonstrated this in a simple example which he generalised, treating the variability uncertainty by the probability theory and the lack of knowledge uncertainty by the fuzzy theory. He cautioned, however, against the systematic use of probability theory which may lead to unjustifiable and illegitimate precise answers. Mr Chojnacki's conclusions were that the importance of distinguishing variability and lack of knowledge increased as the problem was getting more and more complex in terms of number of parameters or time steps, and that it was necessary to develop uncertainty propagation methodologies combining probability theory and fuzzy theory

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.

Global sensitivity analysis for identifying important parameters of nitrogen nitrification and denitrification under model uncertainty and scenario uncertainty

Science.gov (United States)

Chen, Zhuowei; Shi, Liangsheng; Ye, Ming; Zhu, Yan; Yang, Jinzhong

2018-06-01

Nitrogen reactive transport modeling is subject to uncertainty in model parameters, structures, and scenarios. By using a new variance-based global sensitivity analysis method, this paper identifies important parameters for nitrogen reactive transport with simultaneous consideration of these three uncertainties. A combination of three scenarios of soil temperature and two scenarios of soil moisture creates a total of six scenarios. Four alternative models describing the effect of soil temperature and moisture content are used to evaluate the reduction functions used for calculating actual reaction rates. The results show that for nitrogen reactive transport problem, parameter importance varies substantially among different models and scenarios. Denitrification and nitrification process is sensitive to soil moisture content status rather than to the moisture function parameter. Nitrification process becomes more important at low moisture content and low temperature. However, the changing importance of nitrification activity with respect to temperature change highly relies on the selected model. Model-averaging is suggested to assess the nitrification (or denitrification) contribution by reducing the possible model error. Despite the introduction of biochemical heterogeneity or not, fairly consistent parameter importance rank is obtained in this study: optimal denitrification rate (Kden) is the most important parameter; reference temperature (Tr) is more important than temperature coefficient (Q10); empirical constant in moisture response function (m) is the least important one. Vertical distribution of soil moisture but not temperature plays predominant role controlling nitrogen reaction. This study provides insight into the nitrogen reactive transport modeling and demonstrates an effective strategy of selecting the important parameters when future temperature and soil moisture carry uncertainties or when modelers face with multiple ways of establishing nitrogen

The state of the art of the impact of sampling uncertainty on measurement uncertainty

Science.gov (United States)

Leite, V. J.; Oliveira, E. C.

2018-03-01

The measurement uncertainty is a parameter that marks the reliability and can be divided into two large groups: sampling and analytical variations. Analytical uncertainty is a controlled process, performed in the laboratory. The same does not occur with the sampling uncertainty, which, because it faces several obstacles and there is no clarity on how to perform the procedures, has been neglected, although it is admittedly indispensable to the measurement process. This paper aims at describing the state of the art of sampling uncertainty and at assessing its relevance to measurement uncertainty.

Decision analysis of shoreline protection under climate change uncertainty

Science.gov (United States)

Chao, Philip T.; Hobbs, Benjamin F.

1997-04-01

If global warming occurs, it could significantly affect water resource distribution and availability. Yet it is unclear whether the prospect of such change is relevant to water resources management decisions being made today. We model a shoreline protection decision problem with a stochastic dynamic program (SDP) to determine whether consideration of the possibility of climate change would alter the decision. Three questions are addressed with the SDP: (l) How important is climate change compared to other uncertainties?, (2) What is the economic loss if climate change uncertainty is ignored?, and (3) How does belief in climate change affect the timing of the decision? In the case study, sensitivity analysis shows that uncertainty in real discount rates has a stronger effect upon the decision than belief in climate change. Nevertheless, a strong belief in climate change makes the shoreline protection project less attractive and often alters the decision to build it.

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

Science.gov (United States)

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

2014-12-01

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

Uncertainties in hydrogen combustion

International Nuclear Information System (INIS)

Stamps, D.W.; Wong, C.C.; Nelson, L.S.

1988-01-01

Three important areas of hydrogen combustion with uncertainties are identified: high-temperature combustion, flame acceleration and deflagration-to-detonation transition, and aerosol resuspension during hydrogen combustion. The uncertainties associated with high-temperature combustion may affect at least three different accident scenarios: the in-cavity oxidation of combustible gases produced by core-concrete interactions, the direct containment heating hydrogen problem, and the possibility of local detonations. How these uncertainties may affect the sequence of various accident scenarios is discussed and recommendations are made to reduce these uncertainties. 40 references

Uncertainty in artificial intelligence

CERN Document Server

Kanal, LN

1986-01-01

How to deal with uncertainty is a subject of much controversy in Artificial Intelligence. This volume brings together a wide range of perspectives on uncertainty, many of the contributors being the principal proponents in the controversy.Some of the notable issues which emerge from these papers revolve around an interval-based calculus of uncertainty, the Dempster-Shafer Theory, and probability as the best numeric model for uncertainty. There remain strong dissenting opinions not only about probability but even about the utility of any numeric method in this context.

Reprint of: Production scheduling of a lignite mine under quality and reserves uncertainty

International Nuclear Information System (INIS)

Galetakis, Michael; Roumpos, Christos; Alevizos, George; Vamvuka, Despina

2012-01-01

The effect of uncertainty sources to the stochastic optimization of the combined project of a new surface lignite mine exploitation and power plant operation for electricity generation is investigated. Major sources of uncertainty that were considered are the reserves and the quality of the lignite. Since probability distribution functions for these uncertainties were estimated during the detailed exploration phase of the deposit, the overall goal is then to determine the optimal capacity of the power plant and consequently the optimal production rate of the mine over the time. The optimization objective that was selected is the maximization of the net present value of the project. Emphasis is placed on the sensitivity analysis for the investigation of the effect of quality and reserves uncertainty on project optimization, on the mathematical formulation of risk attitude strategy and on increasing the efficiency of the optimization process by creating a limited set of feasible solutions applying empirical rules. The developed methodology was applied for the determination of the optimal annual production rate of a new surface lignite mine in the area of Ptolemais–Amynteon in Northern Greece. - Highlights: ► Quality and reserves uncertainty affects considerably the production scheduling. ► Stochastic optimization is greatly accelerated by incorporating Taylor's rule. ► Decisions can be made considering different risk level attitudes.

Uncertainty: a discriminator for above and below boiling repository design decisions

International Nuclear Information System (INIS)

Wilder, D G; Lin, W; Buscheck, T A; Wolery, T J; Francis, N D

2000-01-01

The US nuclear waste disposal program is evaluating the Yucca Mountain (YM) site for possible disposal of nuclear waste. Radioactive decay of the waste, particularly spent fuel, generates sufficient heat to significantly raise repository temperatures. Environmental conditions in the repository system evolve in response to this heat. The amount of temperature increase, and thus environmental changes, depends on repository design and operations. Because the evolving environment cannot be directly measured until after waste is emplaced, licensing decisions must be based upon model and analytical projections of the environmental conditions. These analyses have inherent uncertainties. There is concern that elevated temperatures increase uncertainty, because most chemical reaction rates increase with temperature and boiling introduces additional complexity of vapor phase reactions and transport. This concern was expressed by the NWTRB, particularly for above boiling temperatures. They state that ''the cooler the repository, the lower the uncertainty about heat-driven water migration and the better the performance of waste package materials. Above this temperature, technical uncertainties tend to be significantly higher than those associated with below-boiling conditions.'' (Cohon 1999). However, not all uncertainties are reduced by lower temperatures, indeed some may even be increased. This paper addresses impacts of temperatures on uncertainties

Sensitivity and uncertainty analysis of nuclear responses in the EU HCLL TBM of ITER

International Nuclear Information System (INIS)

Leichtle, Dieter; Fischer, Ulrich; Perel, Reuven L.; Serikov, Arkady

2011-01-01

Within the EU Fusion Technology Programme dedicated theoretical and experimental efforts are conducted to provide reliable nuclear data and computational tools for design analyses for fusion devices like ITER including qualified uncertainty estimates. In this respect, the present paper reports on sensitivity and uncertainty analyses for the EU HCLL Test Blanket Module (TBM) of ITER. Neutron flux spectra and tritium production rates have been calculated using MCNP with a modified version of the ITER Alite torus sector model with integrated TBMs. Sensitivities of such parameters to nuclear cross sections of isotopes contained in the TBM as well as in the ITER device have been calculated using the Monte Carlo code MCSEN. Uncertainties could be obtained by using existing covariance data of the important nuclear cross section files, mainly from ENDF/B-VI, SCALE6.0, but also from recent JEFF/EFF evaluations. Like in the HCLL mock-up experiment two positions at front and back of the TBM have been selected. In both cases the calculated uncertainties of the responses (tritium production rate, neutron flux) are in the range of 2-4%.

Expanding Uncertainty Principle to Certainty-Uncertainty Principles with Neutrosophy and Quad-stage Method

Directory of Open Access Journals (Sweden)

Fu Yuhua

2015-03-01

Full Text Available The most famous contribution of Heisenberg is uncertainty principle. But the original uncertainty principle is improper. Considering all the possible situations (including the case that people can create laws and applying Neutrosophy and Quad-stage Method, this paper presents "certainty-uncertainty principles" with general form and variable dimension fractal form. According to the classification of Neutrosophy, "certainty-uncertainty principles" can be divided into three principles in different conditions: "certainty principle", namely a particle’s position and momentum can be known simultaneously; "uncertainty principle", namely a particle’s position and momentum cannot be known simultaneously; and neutral (fuzzy "indeterminacy principle", namely whether or not a particle’s position and momentum can be known simultaneously is undetermined. The special cases of "certain ty-uncertainty principles" include the original uncertainty principle and Ozawa inequality. In addition, in accordance with the original uncertainty principle, discussing high-speed particle’s speed and track with Newton mechanics is unreasonable; but according to "certaintyuncertainty principles", Newton mechanics can be used to discuss the problem of gravitational defection of a photon orbit around the Sun (it gives the same result of deflection angle as given by general relativity. Finally, for the reason that in physics the principles, laws and the like that are regardless of the principle (law of conservation of energy may be invalid; therefore "certaintyuncertainty principles" should be restricted (or constrained by principle (law of conservation of energy, and thus it can satisfy the principle (law of conservation of energy.

Uncertainty enabled Sensor Observation Services

Science.gov (United States)

Cornford, Dan; Williams, Matthew; Bastin, Lucy

2010-05-01

Almost all observations of reality are contaminated with errors, which introduce uncertainties into the actual observation result. Such uncertainty is often held to be a data quality issue, and quantification of this uncertainty is essential for the principled exploitation of the observations. Many existing systems treat data quality in a relatively ad-hoc manner, however if the observation uncertainty is a reliable estimate of the error on the observation with respect to reality then knowledge of this uncertainty enables optimal exploitation of the observations in further processes, or decision making. We would argue that the most natural formalism for expressing uncertainty is Bayesian probability theory. In this work we show how the Open Geospatial Consortium Sensor Observation Service can be implemented to enable the support of explicit uncertainty about observations. We show how the UncertML candidate standard is used to provide a rich and flexible representation of uncertainty in this context. We illustrate this on a data set of user contributed weather data where the INTAMAP interpolation Web Processing Service is used to help estimate the uncertainty on the observations of unknown quality, using observations with known uncertainty properties. We then go on to discuss the implications of uncertainty for a range of existing Open Geospatial Consortium standards including SWE common and Observations and Measurements. We discuss the difficult decisions in the design of the UncertML schema and its relation and usage within existing standards and show various options. We conclude with some indications of the likely future directions for UncertML in the context of Open Geospatial Consortium services.

Ethics under uncertainty: the morality and appropriateness of utilitarianism when outcomes are uncertain.

Science.gov (United States)

Kortenkamp, Katherine V; Moore, Colleen F

2014-01-01

Real-life moral dilemmas inevitably involve uncertainty, yet research has not considered how uncertainty affects utilitarian moral judgments. In addition, even though moral dilemma researchers regularly ask respondents, "What is appropriate?" but interpret it to mean, "What is moral?," little research has examined whether a difference exists between asking these 2 types of questions. In this study, 140 college students read moral dilemmas that contained certain or uncertain consequences and then responded as to whether it was appropriate and whether it was moral to kill 1 to save many (a utilitarian choice). Ratings of the appropriateness and morality of the utilitarian choice were lower under uncertainty than certainty. A follow-up experiment found that these results could not be explained entirely by a change in the expected values of the outcomes or a desire to avoid the worst-case scenario. In addition, the utilitarian choice to kill 1 to save many was rated as more appropriate than moral. The results imply that moral decision making may depend critically on whether uncertainties in outcomes are admitted and whether people are asked about appropriateness or morality.

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

International Nuclear Information System (INIS)

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

1999-01-01

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

Optimal natural resources management under uncertainty with catastrophic risk

Energy Technology Data Exchange (ETDEWEB)

Motoh, Tsujimura [Graduate School of Economics, Kyoto University, Yoshida-honmochi, Sakyo-ku, Kyoto 606-8501 (Japan)

2004-05-01

We examine an optimal natural resources management problem under uncertainty with catastrophic risk and investigate the optimal rate of use of a natural resource. For this purpose, we use stochastic control theory. We assume that, until a catastrophic event occurs, the stock of the natural resource is governed by a stochastic differential equation. We describe the catastrophic phenomenon as a Poisson process. From this analysis, we show the optimal rate of use of the natural resource in explicit form. Furthermore, we present comparative static results for the optimal rate of use of the natural resource.

Optimal natural resources management under uncertainty with catastrophic risk

International Nuclear Information System (INIS)

Motoh, Tsujimura

2004-01-01

We examine an optimal natural resources management problem under uncertainty with catastrophic risk and investigate the optimal rate of use of a natural resource. For this purpose, we use stochastic control theory. We assume that, until a catastrophic event occurs, the stock of the natural resource is governed by a stochastic differential equation. We describe the catastrophic phenomenon as a Poisson process. From this analysis, we show the optimal rate of use of the natural resource in explicit form. Furthermore, we present comparative static results for the optimal rate of use of the natural resource

Uncertainty Evaluation of Best Estimate Calculation Results

International Nuclear Information System (INIS)

Glaeser, H.

2006-01-01

Efforts are underway in Germany to perform analysis using best estimate computer codes and to include uncertainty evaluation in licensing. The German Reactor Safety Commission (RSK) issued a recommendation to perform uncertainty analysis in loss of coolant accident safety analyses (LOCA), recently. A more general requirement is included in a draft revision of the German Nuclear Regulation which is an activity of the German Ministry of Environment and Reactor Safety (BMU). According to the recommendation of the German RSK to perform safety analyses for LOCA in licensing the following deterministic requirements have still to be applied: Most unfavourable single failure, Unavailability due to preventive maintenance, Break location, Break size and break type, Double ended break, 100 percent through 200 percent, Large, medium and small break, Loss of off-site power, Core power (at accident initiation the most unfavourable conditions and values have to be assumed which may occur under normal operation taking into account the set-points of integral power and power density control. Measurement and calibration errors can be considered statistically), Time of fuel cycle. Analysis using best estimate codes with evaluation of uncertainties is the only way to quantify conservatisms with regard to code models and uncertainties of plant, fuel parameters and decay heat. This is especially the case for approaching licensing limits, e.g. due to power up-rates, higher burn-up and higher enrichment. Broader use of best estimate analysis is therefore envisaged in the future. Since some deterministic unfavourable assumptions regarding availability of NPP systems are still used, some conservatism in best-estimate analyses remains. Methods of uncertainty analyses have been developed and applied by the vendor Framatome ANP as well as by GRS in Germany. The GRS development was sponsored by the German Ministry of Economy and Labour (BMWA). (author)

Uncertainty Communication. Issues and good practice

International Nuclear Information System (INIS)

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

2007-12-01

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

Reliability analysis under epistemic uncertainty

International Nuclear Information System (INIS)

Nannapaneni, Saideep; Mahadevan, Sankaran

2016-01-01

This paper proposes a probabilistic framework to include both aleatory and epistemic uncertainty within model-based reliability estimation of engineering systems for individual limit states. Epistemic uncertainty is considered due to both data and model sources. Sparse point and/or interval data regarding the input random variables leads to uncertainty regarding their distribution types, distribution parameters, and correlations; this statistical uncertainty is included in the reliability analysis through a combination of likelihood-based representation, Bayesian hypothesis testing, and Bayesian model averaging techniques. Model errors, which include numerical solution errors and model form errors, are quantified through Gaussian process models and included in the reliability analysis. The probability integral transform is used to develop an auxiliary variable approach that facilitates a single-level representation of both aleatory and epistemic uncertainty. This strategy results in an efficient single-loop implementation of Monte Carlo simulation (MCS) and FORM/SORM techniques for reliability estimation under both aleatory and epistemic uncertainty. Two engineering examples are used to demonstrate the proposed methodology. - Highlights: • Epistemic uncertainty due to data and model included in reliability analysis. • A novel FORM-based approach proposed to include aleatory and epistemic uncertainty. • A single-loop Monte Carlo approach proposed to include both types of uncertainties. • Two engineering examples used for illustration.

Simplified propagation of standard uncertainties

International Nuclear Information System (INIS)

Shull, A.H.

1997-01-01

An essential part of any measurement control program is adequate knowledge of the uncertainties of the measurement system standards. Only with an estimate of the standards'' uncertainties can one determine if the standard is adequate for its intended use or can one calculate the total uncertainty of the measurement process. Purchased standards usually have estimates of uncertainty on their certificates. However, when standards are prepared and characterized by a laboratory, variance propagation is required to estimate the uncertainty of the standard. Traditional variance propagation typically involves tedious use of partial derivatives, unfriendly software and the availability of statistical expertise. As a result, the uncertainty of prepared standards is often not determined or determined incorrectly. For situations meeting stated assumptions, easier shortcut methods of estimation are now available which eliminate the need for partial derivatives and require only a spreadsheet or calculator. A system of simplifying the calculations by dividing into subgroups of absolute and relative uncertainties is utilized. These methods also incorporate the International Standards Organization (ISO) concepts for combining systematic and random uncertainties as published in their Guide to the Expression of Measurement Uncertainty. Details of the simplified methods and examples of their use are included in the paper

Fate of organic microcontaminants in wastewater treatment and river systems: An uncertainty assessment in view of sampling strategy, and compound consumption rate and degradability.

Science.gov (United States)

Aymerich, I; Acuña, V; Ort, C; Rodríguez-Roda, I; Corominas, Ll

2017-11-15

The growing awareness of the relevance of organic microcontaminants on the environment has led to a growing number of studies on attenuation of these compounds in wastewater treatment plants (WWTP) and rivers. However, the effects of the sampling strategies (frequency and duration of composite samples) on the attenuation estimates are largely unknown. Our goal was to assess how frequency and duration of composite samples influence uncertainty of the attenuation estimates in WWTPs and rivers. Furthermore, we also assessed how compound consumption rate and degradability influence uncertainty. The assessment was conducted through simulating the integrated wastewater system of Puigcerdà (NE Iberian Peninsula) using a sewer pattern generator and a coupled model of WWTP and river. Results showed that the sampling strategy is especially critical at the influent of WWTP, particularly when the number of toilet flushes containing the compound of interest is small (≤100 toilet flushes with compound day -1 ), and less critical at the effluent of the WWTP and in the river due to the mixing effects of the WWTP. For example, at the WWTP, when evaluating a compound that is present in 50 pulses·d -1 using a sampling frequency of 15-min to collect a 24-h composite sample, the attenuation uncertainty can range from 94% (0% degradability) to 9% (90% degradability). The estimation of attenuation in rivers is less critical than in WWTPs, as the attenuation uncertainty was lower than 10% for all evaluated scenarios. Interestingly, the errors in the estimates of attenuation are usually lower than those of loads for most sampling strategies and compound characteristics (e.g. consumption and degradability), although the opposite occurs for compounds with low consumption and inappropriate sampling strategies at the WWTP. Hence, when designing a sampling campaign, one should consider the influence of compounds' consumption and degradability as well as the desired level of accuracy in

Evaluating prediction uncertainty

International Nuclear Information System (INIS)

McKay, M.D.

1995-03-01

The probability distribution of a model prediction is presented as a proper basis for evaluating the uncertainty in a model prediction that arises from uncertainty in input values. Determination of important model inputs and subsets of inputs is made through comparison of the prediction distribution with conditional prediction probability distributions. Replicated Latin hypercube sampling and variance ratios are used in estimation of the distributions and in construction of importance indicators. The assumption of a linear relation between model output and inputs is not necessary for the indicators to be effective. A sequential methodology which includes an independent validation step is applied in two analysis applications to select subsets of input variables which are the dominant causes of uncertainty in the model predictions. Comparison with results from methods which assume linearity shows how those methods may fail. Finally, suggestions for treating structural uncertainty for submodels are presented

Oil price uncertainty in Canada

Energy Technology Data Exchange (ETDEWEB)

Elder, John [Department of Finance and Real Estate, 1272 Campus Delivery, Colorado State University, Fort Collins, CO 80523 (United States); Serletis, Apostolos [Department of Economics, University of Calgary, Calgary, Alberta (Canada)

2009-11-15

Bernanke [Bernanke, Ben S. Irreversibility, uncertainty, and cyclical investment. Quarterly Journal of Economics 98 (1983), 85-106.] shows how uncertainty about energy prices may induce optimizing firms to postpone investment decisions, thereby leading to a decline in aggregate output. Elder and Serletis [Elder, John and Serletis, Apostolos. Oil price uncertainty.] find empirical evidence that uncertainty about oil prices has tended to depress investment in the United States. In this paper we assess the robustness of these results by investigating the effects of oil price uncertainty in Canada. Our results are remarkably similar to existing results for the United States, providing additional evidence that uncertainty about oil prices may provide another explanation for why the sharp oil price declines of 1985 failed to produce rapid output growth. Impulse-response analysis suggests that uncertainty about oil prices may tend to reinforce the negative response of output to positive oil shocks. (author)

Quantification of design margins and safety factors based on the prediction uncertainty in tritium production rate from fusion integral experiments of the USDOE/JAERI collaborative program on fusion blanket neutronics

International Nuclear Information System (INIS)

Youssef, M.Z.; Konno, C.; Maekawa, F.; Ikeda, Y.; Kosako, K.; Nakagawa, M.; Mori, T.; Maekawa, H.

1995-01-01

Several fusion integral experiments were performed within a collaboration between the USA and Japan on fusion breeder neutronics aimed at verifying the prediction accuracy of key neutronics parameters in a fusion reactor blanket based on current neutron transport codes and basic nuclear databases. The focus has been on the tritium production rate (TRP) as an important design parameter to resolve the issue of tritium self-sufficiency in a fusion reactor. In this paper, the calculational and experimental uncertainties (errors) in local TPR in each experiment performed i were interpolated and propagated to estimate the prediction uncertainty u i in the line-integrated TPR and its standard deviation σ i . The measured data are based on Li-glass and NE213 detectors. From the quantities u i and σ i , normalized density functions (NDFs) were constructed, considering all the experiments and their associated analyses performed independently by the UCLA and JAERI. Several statistical parameters were derived, including the mean prediction uncertainties u and the possible spread ±σ u around them. Design margins and safety factors were derived from these NDFs. Distinction was made between the results obtained by UCLA and JAERI and between calculational results based on the discrete ordinates and Monte Carlo methods. The prediction uncertainties, their standard deviations and the design margins and safety factors were derived for the line-integrated TPR from Li-6 T 6 , and Li-7 T 7 . These parameters were used to estimate the corresponding uncertainties and safety factor for the line-integrated TPR from natural lithium T n . (orig.)

Low flow measurement for infusion pumps: implementation and uncertainty determination of the normalized method

International Nuclear Information System (INIS)

Cebeiro, J; Musacchio, A; Sardá, E Fernández

2011-01-01

Intravenous drug delivery is a standard practice in hospitalized patients. As the blood concentration reached depends directly on infusion rate, it is important to use safe devices that guarantee output accuracy. In pediatric intensive care units, low infusion rates (i.e. lower than 10.0 ml/h) are frequently used. Thus, it would be necessary to use control programs to search for deviations at this flow range. We describe the implementation of a gravimetric method to test infusion pumps in low flow delivery. The procedure recommended by the ISO/IEC 60601-2-24 standard was used being a reasonable option among the methods frequently used in hospitals, such as infusion pumps analyzers and volumetric cylinders. The main uncertainty sources affecting this method are revised and a numeric and graphic uncertainty analysis is presented in order to show its dependence on flow. Additionally, the obtained uncertainties are compared to those presented by an automatic flow analyzer. Finally, the results of a series of tests performed on a syringe infusion pump operating at low rates are shown.

Additivity of entropic uncertainty relations

Directory of Open Access Journals (Sweden)

René Schwonnek

2018-03-01

Full Text Available We consider the uncertainty between two pairs of local projective measurements performed on a multipartite system. We show that the optimal bound in any linear uncertainty relation, formulated in terms of the Shannon entropy, is additive. This directly implies, against naive intuition, that the minimal entropic uncertainty can always be realized by fully separable states. Hence, in contradiction to proposals by other authors, no entanglement witness can be constructed solely by comparing the attainable uncertainties of entangled and separable states. However, our result gives rise to a huge simplification for computing global uncertainty bounds as they now can be deduced from local ones. Furthermore, we provide the natural generalization of the Maassen and Uffink inequality for linear uncertainty relations with arbitrary positive coefficients.

Bayesian Chance-Constrained Hydraulic Barrier Design under Geological Structure Uncertainty.

Science.gov (United States)

Chitsazan, Nima; Pham, Hai V; Tsai, Frank T-C

2015-01-01

The groundwater community has widely recognized geological structure uncertainty as a major source of model structure uncertainty. Previous studies in aquifer remediation design, however, rarely discuss the impact of geological structure uncertainty. This study combines chance-constrained (CC) programming with Bayesian model averaging (BMA) as a BMA-CC framework to assess the impact of geological structure uncertainty in remediation design. To pursue this goal, the BMA-CC method is compared with traditional CC programming that only considers model parameter uncertainty. The BMA-CC method is employed to design a hydraulic barrier to protect public supply wells of the Government St. pump station from salt water intrusion in the "1500-foot" sand and the "1700-foot" sand of the Baton Rouge area, southeastern Louisiana. To address geological structure uncertainty, three groundwater models based on three different hydrostratigraphic architectures are developed. The results show that using traditional CC programming overestimates design reliability. The results also show that at least five additional connector wells are needed to achieve more than 90% design reliability level. The total amount of injected water from the connector wells is higher than the total pumpage of the protected public supply wells. While reducing the injection rate can be achieved by reducing the reliability level, the study finds that the hydraulic barrier design to protect the Government St. pump station may not be economically attractive. © 2014, National Ground Water Association.

General properties of astrophysical reaction rates in explosive nucleosynthesis

International Nuclear Information System (INIS)

Rauscher, Thomas

2013-01-01

Fundamental differences in the prediction of reaction rates with intermediate and heavy target nuclei compared to the ones with light nuclei are discussed, with special emphasis on stellar modifications of the rates. Ground and excited state contributions to the stellar rates are quantified, deriving a linear weighting of excited state contributions despite of a Boltzmann population of the nuclear states. A Coulomb suppression effect of the excited state contributions is identified, acting against the usual Q-value rule in some reactions. The proper inclusion of experimental data in revised stellar rates is shown, containing revised uncertainties. An application to the s-process shows that the actual uncertainties in the neutron capture rates are larger than would be expected from the experimental errors alone. Sensitivities of reaction rates and cross sections are defined and their application in reaction studies is discussed. The conclusion provides a guide to experiment as well as theory on how to best improve the rates used in astrophysical simulations and how to assess their uncertainties.

Articulating uncertainty as part of scientific argumentation during model-based exoplanet detection tasks

Science.gov (United States)

Lee, Hee-Sun; Pallant, Amy; Pryputniewicz, Sarah

2015-08-01

Teaching scientific argumentation has emerged as an important goal for K-12 science education. In scientific argumentation, students are actively involved in coordinating evidence with theory based on their understanding of the scientific content and thinking critically about the strengths and weaknesses of the cited evidence in the context of the investigation. We developed a one-week-long online curriculum module called "Is there life in space?" where students conduct a series of four model-based tasks to learn how scientists detect extrasolar planets through the “wobble” and transit methods. The simulation model allows students to manipulate various parameters of an imaginary star and planet system such as planet size, orbit size, planet-orbiting-plane angle, and sensitivity of telescope equipment, and to adjust the display settings for graphs illustrating the relative velocity and light intensity of the star. Students can use model-based evidence to formulate an argument on whether particular signals in the graphs guarantee the presence of a planet. Students' argumentation is facilitated by the four-part prompts consisting of multiple-choice claim, open-ended explanation, Likert-scale uncertainty rating, and open-ended uncertainty rationale. We analyzed 1,013 scientific arguments formulated by 302 high school student groups taught by 7 teachers. We coded these arguments in terms of the accuracy of their claim, the sophistication of explanation connecting evidence to the established knowledge base, the uncertainty rating, and the scientific validity of uncertainty. We found that (1) only 18% of the students' uncertainty rationale involved critical reflection on limitations inherent in data and concepts, (2) 35% of students' uncertainty rationale reflected their assessment of personal ability and knowledge, rather than scientific sources of uncertainty related to the evidence, and (3) the nature of task such as the use of noisy data or the framing of

Measurement uncertainty and probability

CERN Document Server

Willink, Robin

2013-01-01

A measurement result is incomplete without a statement of its 'uncertainty' or 'margin of error'. But what does this statement actually tell us? By examining the practical meaning of probability, this book discusses what is meant by a '95 percent interval of measurement uncertainty', and how such an interval can be calculated. The book argues that the concept of an unknown 'target value' is essential if probability is to be used as a tool for evaluating measurement uncertainty. It uses statistical concepts, such as a conditional confidence interval, to present 'extended' classical methods for evaluating measurement uncertainty. The use of the Monte Carlo principle for the simulation of experiments is described. Useful for researchers and graduate students, the book also discusses other philosophies relating to the evaluation of measurement uncertainty. It employs clear notation and language to avoid the confusion that exists in this controversial field of science.

Cross-section sensitivity and uncertainty analysis of the FNG copper benchmark experiment

Energy Technology Data Exchange (ETDEWEB)

Kodeli, I., E-mail: ivan.kodeli@ijs.si [Jožef Stefan Institute, Jamova 39, SI-1000 Ljubljana (Slovenia); Kondo, K. [Karlsruhe Institute of Technology, Postfach 3640, D-76021 Karlsruhe (Germany); Japan Atomic Energy Agency, Rokkasho-mura (Japan); Perel, R.L. [Racah Institute of Physics, Hebrew University of Jerusalem, IL-91904 Jerusalem (Israel); Fischer, U. [Karlsruhe Institute of Technology, Postfach 3640, D-76021 Karlsruhe (Germany)

2016-11-01

A neutronics benchmark experiment on copper assembly was performed end 2014–beginning 2015 at the 14-MeV Frascati neutron generator (FNG) of ENEA Frascati with the objective to provide the experimental database required for the validation of the copper nuclear data relevant for ITER design calculations, including the related uncertainties. The paper presents the pre- and post-analysis of the experiment performed using cross-section sensitivity and uncertainty codes, both deterministic (SUSD3D) and Monte Carlo (MCSEN5). Cumulative reaction rates and neutron flux spectra, their sensitivity to the cross sections, as well as the corresponding uncertainties were estimated for different selected detector positions up to ∼58 cm in the copper assembly. This permitted in the pre-analysis phase to optimize the geometry, the detector positions and the choice of activation reactions, and in the post-analysis phase to interpret the results of the measurements and the calculations, to conclude on the quality of the relevant nuclear cross-section data, and to estimate the uncertainties in the calculated nuclear responses and fluxes. Large uncertainties in the calculated reaction rates and neutron spectra of up to 50%, rarely observed at this level in the benchmark analysis using today's nuclear data, were predicted, particularly high for fast reactions. Observed C/E (dis)agreements with values as low as 0.5 partly confirm these predictions. Benchmark results are therefore expected to contribute to the improvement of both cross section as well as covariance data evaluations.

Effect of activation cross section uncertainties in transmutation analysis of realistic low-activation steels for IFMIF

Energy Technology Data Exchange (ETDEWEB)

Cabellos, O.; Garcya-Herranz, N.; Sanz, J. [Institute of Nuclear Fusion, UPM, Madrid (Spain); Cabellos, O.; Garcya-Herranz, N.; Fernandez, P.; Fernandez, B. [Dept. of Nuclear Engineering, UPM, Madrid (Spain); Sanz, J. [Dept. of Power Engineering, UNED, Madrid (Spain); Reyes, S. [Safety, Environment and Health Group, ITER Joint Work Site, Cadarache Center (France)

2008-07-01

We address uncertainty analysis to draw conclusions on the reliability of the activation calculation in the International Fusion Materials Irradiation Facility (IFMIF) under the potential impact of activation cross section uncertainties. The Monte Carlo methodology implemented in ACAB code gives the uncertainty estimates due to the synergetic/global effect of the complete set of cross section uncertainties. An element-by-element analysis has been demonstrated as a helpful tool to easily analyse the transmutation performance of irradiated materials.The uncertainty analysis results showed that for times over about 24 h the relative error in the contact dose rate can be as large as 23 per cent. We have calculated the effect of cross section uncertainties in the IFMIF activation of all different elements. For EUROFER, uncertainties in H and He elements are 7.3% and 5.6%, respectively. We have found significant uncertainties in the transmutation response for C, P and Nb.

Model uncertainty and probability

International Nuclear Information System (INIS)

Parry, G.W.

1994-01-01

This paper discusses the issue of model uncertainty. The use of probability as a measure of an analyst's uncertainty as well as a means of describing random processes has caused some confusion, even though the two uses are representing different types of uncertainty with respect to modeling a system. The importance of maintaining the distinction between the two types is illustrated with a simple example

A new uncertainty importance measure

International Nuclear Information System (INIS)

Borgonovo, E.

2007-01-01

Uncertainty in parameters is present in many risk assessment problems and leads to uncertainty in model predictions. In this work, we introduce a global sensitivity indicator which looks at the influence of input uncertainty on the entire output distribution without reference to a specific moment of the output (moment independence) and which can be defined also in the presence of correlations among the parameters. We discuss its mathematical properties and highlight the differences between the present indicator, variance-based uncertainty importance measures and a moment independent sensitivity indicator previously introduced in the literature. Numerical results are discussed with application to the probabilistic risk assessment model on which Iman [A matrix-based approach to uncertainty and sensitivity analysis for fault trees. Risk Anal 1987;7(1):22-33] first introduced uncertainty importance measures

A new uncertainty reduction method for PWR cores with erbia bearing fuel

International Nuclear Information System (INIS)

Takeda, Toshikazu; Sano, Tadafumi; Kitada, Takanori; Kuroishi, Takeshi; Yamasaki, Masatoshi; Unesaki, Hironobu

2008-01-01

The concept of a PWR with erbia bearing high burnup fuel has been proposed. The erbia is added to all fuel with over 5% 235 U enrichment to retain the neutronics characteristics to that within 5% 235 U enrichment. There is a problem of the prediction accuracy of the neutronics characteristics with erbia bearing fuel because of the short of experimental data of erbia bearing fuel. The purpose of the present work is to reduce the uncertainty. A new method has been proposed by combining the bias factor method and the cross section adjustment method. For the PWR core, the uncertainty reduction, which shows the rate of reduction of uncertainty, of the k eff is 0.865 by the present method and 0.801 by the conventional bias factor method. Thus the prediction uncertainties are reduced by the present method compared to the bias factor method. (authors)

Uncertainty calculations made easier

International Nuclear Information System (INIS)

Hogenbirk, A.

1994-07-01

The results are presented of a neutron cross section sensitivity/uncertainty analysis performed in a complicated 2D model of the NET shielding blanket design inside the ITER torus design, surrounded by the cryostat/biological shield as planned for ITER. The calculations were performed with a code system developed at ECN Petten, with which sensitivity/uncertainty calculations become relatively simple. In order to check the deterministic neutron transport calculations (performed with DORT), calculations were also performed with the Monte Carlo code MCNP. Care was taken to model the 2.0 cm wide gaps between two blanket segments, as the neutron flux behind the vacuum vessel is largely determined by neutrons streaming through these gaps. The resulting neutron flux spectra are in excellent agreement up to the end of the cryostat. It is noted, that at this position the attenuation of the neutron flux is about 1 l orders of magnitude. The uncertainty in the energy integrated flux at the beginning of the vacuum vessel and at the beginning of the cryostat was determined in the calculations. The uncertainty appears to be strongly dependent on the exact geometry: if the gaps are filled with stainless steel, the neutron spectrum changes strongly, which results in an uncertainty of 70% in the energy integrated flux at the beginning of the cryostat in the no-gap-geometry, compared to an uncertainty of only 5% in the gap-geometry. Therefore, it is essential to take into account the exact geometry in sensitivity/uncertainty calculations. Furthermore, this study shows that an improvement of the covariance data is urgently needed in order to obtain reliable estimates of the uncertainties in response parameters in neutron transport calculations. (orig./GL)

Unexpected uncertainty, volatility and decision-making

Directory of Open Access Journals (Sweden)

Amy Rachel Bland

2012-06-01

Full Text Available The study of uncertainty in decision making is receiving greater attention in the fields of cognitive and computational neuroscience. Several lines of evidence are beginning to elucidate different variants of uncertainty. Particularly, risk, ambiguity and expected and unexpected forms of uncertainty are well articulated in the literature. In this article we review both empirical and theoretical evidence arguing for the potential distinction between three forms of uncertainty; expected uncertainty, unexpected uncertainty and volatility. Particular attention will be devoted to exploring the distinction between unexpected uncertainty and volatility which has been less appreciated in the literature. This includes evidence from computational modelling, neuromodulation, neuroimaging and electrophysiological studies. We further address the possible differentiation of cognitive control mechanisms used to deal with these forms of uncertainty. Particularly we explore a role for conflict monitoring and the temporal integration of information into working memory. Finally, we explore whether the Dual Modes of Control theory provides a theoretical framework for understanding the distinction between unexpected uncertainty and volatility.

Model uncertainty in safety assessment

International Nuclear Information System (INIS)

Pulkkinen, U.; Huovinen, T.

1996-01-01

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

Model uncertainty in safety assessment

Energy Technology Data Exchange (ETDEWEB)

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

1996-01-01

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

Uncertainty Management and Sensitivity Analysis

DEFF Research Database (Denmark)

Rosenbaum, Ralph K.; Georgiadis, Stylianos; Fantke, Peter

2018-01-01

Uncertainty is always there and LCA is no exception to that. The presence of uncertainties of different types and from numerous sources in LCA results is a fact, but managing them allows to quantify and improve the precision of a study and the robustness of its conclusions. LCA practice sometimes...... suffers from an imbalanced perception of uncertainties, justifying modelling choices and omissions. Identifying prevalent misconceptions around uncertainties in LCA is a central goal of this chapter, aiming to establish a positive approach focusing on the advantages of uncertainty management. The main...... objectives of this chapter are to learn how to deal with uncertainty in the context of LCA, how to quantify it, interpret and use it, and how to communicate it. The subject is approached more holistically than just focusing on relevant statistical methods or purely mathematical aspects. This chapter...

A critique of recent models for human error rate assessment

International Nuclear Information System (INIS)

Apostolakis, G.E.

1988-01-01

This paper critically reviews two groups of models for assessing human error rates under accident conditions. The first group, which includes the US Nuclear Regulatory Commission (NRC) handbook model and the human cognitive reliability (HCR) model, considers as fundamental the time that is available to the operators to act. The second group, which is represented by the success likelihood index methodology multiattribute utility decomposition (SLIM-MAUD) model, relies on ratings of the human actions with respect to certain qualitative factors and the subsequent derivation of error rates. These models are evaluated with respect to two criteria: the treatment of uncertainties and the internal coherence of the models. In other words, this evaluation focuses primarily on normative aspects of these models. The principal findings are as follows: (1) Both of the time-related models provide human error rates as a function of the available time for action and the prevailing conditions. However, the HCR model ignores the important issue of state-of-knowledge uncertainties, dealing exclusively with stochastic uncertainty, whereas the model presented in the NRC handbook handles both types of uncertainty. (2) SLIM-MAUD provides a highly structured approach for the derivation of human error rates under given conditions. However, the treatment of the weights and ratings in this model is internally inconsistent. (author)

Impacts of generalized uncertainty principle on black hole thermodynamics and Salecker-Wigner inequalities

International Nuclear Information System (INIS)

Tawfik, A.

2013-01-01

We investigate the impacts of Generalized Uncertainty Principle (GUP) proposed by some approaches to quantum gravity such as String Theory and Doubly Special Relativity on black hole thermodynamics and Salecker-Wigner inequalities. Utilizing Heisenberg uncertainty principle, the Hawking temperature, Bekenstein entropy, specific heat, emission rate and decay time are calculated. As the evaporation entirely eats up the black hole mass, the specific heat vanishes and the temperature approaches infinity with an infinite radiation rate. It is found that the GUP approach prevents the black hole from the entire evaporation. It implies the existence of remnants at which the specific heat vanishes. The same role is played by the Heisenberg uncertainty principle in constructing the hydrogen atom. We discuss how the linear GUP approach solves the entire-evaporation-problem. Furthermore, the black hole lifetime can be estimated using another approach; the Salecker-Wigner inequalities. Assuming that the quantum position uncertainty is limited to the minimum wavelength of measuring signal, Wigner second inequality can be obtained. If the spread of quantum clock is limited to some minimum value, then the modified black hole lifetime can be deduced. Based on linear GUP approach, the resulting lifetime difference depends on black hole relative mass and the difference between black hole mass with and without GUP is not negligible

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

Science.gov (United States)

Hogg, Michael A; Adelman, Janice R; Blagg, Robert D

2010-02-01

The authors characterize religions as social groups and religiosity as the extent to which a person identifies with a religion, subscribes to its ideology or worldview, and conforms to its normative practices. They argue that religions have attributes that make them well suited to reduce feelings of self-uncertainty. According to uncertainty-identity theory, people are motivated to reduce feelings of uncertainty about or reflecting on self; and identification with groups, particularly highly entitative groups, is a very effective way to reduce uncertainty. All groups provide belief systems and normative prescriptions related to everyday life. However, religions also address the nature of existence, invoking sacred entities and associated rituals and ceremonies. They are entitative groups that provide a moral compass and rules for living that pervade a person's life, making them particularly attractive in times of uncertainty. The authors document data supporting their analysis and discuss conditions that transform religiosity into religious zealotry and extremism.

Calibration Uncertainties in the Droplet Measurement Technologies Cloud Condensation Nuclei Counter

Science.gov (United States)

Hibert, Kurt James

Cloud condensation nuclei (CCN) serve as the nucleation sites for the condensation of water vapor in Earth's atmosphere and are important for their effect on climate and weather. The influence of CCN on cloud radiative properties (aerosol indirect effect) is the most uncertain of quantified radiative forcing changes that have occurred since pre-industrial times. CCN influence the weather because intrinsic and extrinsic aerosol properties affect cloud formation and precipitation development. To quantify these effects, it is necessary to accurately measure CCN, which requires accurate calibrations using a consistent methodology. Furthermore, the calibration uncertainties are required to compare measurements from different field projects. CCN uncertainties also aid the integration of CCN measurements with atmospheric models. The commercially available Droplet Measurement Technologies (DMT) CCN Counter is used by many research groups, so it is important to quantify its calibration uncertainty. Uncertainties in the calibration of the DMT CCN counter exist in the flow rate and supersaturation values. The concentration depends on the accuracy of the flow rate calibration, which does not have a large (4.3 %) uncertainty. The supersaturation depends on chamber pressure, temperature, and flow rate. The supersaturation calibration is a complex process since the chamber's supersaturation must be inferred from a temperature difference measurement. Additionally, calibration errors can result from the Kohler theory assumptions, fitting methods utilized, the influence of multiply-charged particles, and calibration points used. In order to determine the calibration uncertainties and the pressure dependence of the supersaturation calibration, three calibrations are done at each pressure level: 700, 840, and 980 hPa. Typically 700 hPa is the pressure used for aircraft measurements in the boundary layer, 840 hPa is the calibration pressure at DMT in Boulder, CO, and 980 hPa is the

Communicating diagnostic uncertainty in surgical pathology reports: disparities between sender and receiver.

Science.gov (United States)

Lindley, Sarah W; Gillies, Elizabeth M; Hassell, Lewis A

2014-10-01

Surgical pathologists use a variety of phrases to communicate varying degrees of diagnostic certainty which have the potential to be interpreted differently than intended. This study sought to: (1) assess the setting, varieties and frequency of use of phrases of diagnostic uncertainty in the diagnostic line of surgical pathology reports, (2) evaluate use of uncertainty expressions by experience and gender, (3) determine how these phrases are interpreted by clinicians and pathologists, and (4) assess solutions to this communication problem. We evaluated 1500 surgical pathology reports to determine frequency of use of uncertainty terms, identified those most commonly used, and looked for variations in usage rates on the basis of case type, experience and gender. We surveyed 76 physicians at tumor boards who were asked to assign a percentage of certainty to diagnoses containing expressions of uncertainty. We found expressions of uncertainty in 35% of diagnostic reports, with no statistically significant difference in usage based on age or gender. We found wide variation in the percentage of certainty clinicians assigned to the phrases studied. We conclude that non-standardized language used in the communication of diagnostic uncertainty is a significant source of miscommunication, both amongst pathologists and between pathologists and clinicians. Copyright © 2014 The Authors. Published by Elsevier GmbH.. All rights reserved.

Climate-carbon cycle feedbacks under stabilization: uncertainty and observational constraints

International Nuclear Information System (INIS)

Jones, Chris D.; Cox, Peter M.; Huntingford, Chris

2006-01-01

Avoiding 'dangerous climate change' by stabilization of atmospheric CO 2 concentrations at a desired level requires reducing the rate of anthropogenic carbon emissions so that they are balanced by uptake of carbon by the natural terrestrial and oceanic carbon cycles. Previous calculations of profiles of emissions which lead to stabilized CO 2 levels have assumed no impact of climate change on this natural carbon uptake. However, future climate change effects on the land carbon cycle are predicted to reduce its ability to act as a sink for anthropogenic carbon emissions and so quantification of this feedback is required to determine future permissible emissions. Here, we assess the impact of the climate-carbon cycle feedback and attempt to quantify its uncertainty due to both within-model parameter uncertainty and between-model structural uncertainty. We assess the use of observational constraints to reduce uncertainty in the future permissible emissions for climate stabilization and find that all realistic carbon cycle feedbacks consistent with the observational record give permissible emissions significantly less than previously assumed. However, the observational record proves to be insufficient to tightly constrain carbon cycle processes or future feedback strength with implications for climate-carbon cycle model evaluation

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

Science.gov (United States)

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

2013-01-01

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

Parameters-related uncertainty in modeling sugar cane yield with an agro-Land Surface Model

Science.gov (United States)

Valade, A.; Ciais, P.; Vuichard, N.; Viovy, N.; Ruget, F.; Gabrielle, B.

2012-12-01

Agro-Land Surface Models (agro-LSM) have been developed from the coupling of specific crop models and large-scale generic vegetation models. They aim at accounting for the spatial distribution and variability of energy, water and carbon fluxes within soil-vegetation-atmosphere continuum with a particular emphasis on how crop phenology and agricultural management practice influence the turbulent fluxes exchanged with the atmosphere, and the underlying water and carbon pools. A part of the uncertainty in these models is related to the many parameters included in the models' equations. In this study, we quantify the parameter-based uncertainty in the simulation of sugar cane biomass production with the agro-LSM ORCHIDEE-STICS on a multi-regional approach with data from sites in Australia, La Reunion and Brazil. First, the main source of uncertainty for the output variables NPP, GPP, and sensible heat flux (SH) is determined through a screening of the main parameters of the model on a multi-site basis leading to the selection of a subset of most sensitive parameters causing most of the uncertainty. In a second step, a sensitivity analysis is carried out on the parameters selected from the screening analysis at a regional scale. For this, a Monte-Carlo sampling method associated with the calculation of Partial Ranked Correlation Coefficients is used. First, we quantify the sensitivity of the output variables to individual input parameters on a regional scale for two regions of intensive sugar cane cultivation in Australia and Brazil. Then, we quantify the overall uncertainty in the simulation's outputs propagated from the uncertainty in the input parameters. Seven parameters are identified by the screening procedure as driving most of the uncertainty in the agro-LSM ORCHIDEE-STICS model output at all sites. These parameters control photosynthesis (optimal temperature of photosynthesis, optimal carboxylation rate), radiation interception (extinction coefficient), root

78 FR 19442 - Public Safety and Homeland Security Bureau Seeks To Refresh the Record Regarding Options for...

Science.gov (United States)

2013-04-01

... blocking NSI devices used to make fraudulent 911 calls, and suggestions for making this a more viable... fraudulent 911 calls made from NSI devices; (2) concerns with blocking NSI devices used to make fraudulent... the `all calls' rule.'' According to NENA, ``PSAPs face an ever- growing onslaught [[Page 19443

Uncertainty in Measurement: Procedures for Determining Uncertainty With Application to Clinical Laboratory Calculations.

Science.gov (United States)

Frenkel, Robert B; Farrance, Ian

2018-01-01

The "Guide to the Expression of Uncertainty in Measurement" (GUM) is the foundational document of metrology. Its recommendations apply to all areas of metrology including metrology associated with the biomedical sciences. When the output of a measurement process depends on the measurement of several inputs through a measurement equation or functional relationship, the propagation of uncertainties in the inputs to the uncertainty in the output demands a level of understanding of the differential calculus. This review is intended as an elementary guide to the differential calculus and its application to uncertainty in measurement. The review is in two parts. In Part I, Section 3, we consider the case of a single input and introduce the concepts of error and uncertainty. Next we discuss, in the following sections in Part I, such notions as derivatives and differentials, and the sensitivity of an output to errors in the input. The derivatives of functions are obtained using very elementary mathematics. The overall purpose of this review, here in Part I and subsequently in Part II, is to present the differential calculus for those in the medical sciences who wish to gain a quick but accurate understanding of the propagation of uncertainties. © 2018 Elsevier Inc. All rights reserved.

Big bang nucleosynthesis - Predictions and uncertainties

International Nuclear Information System (INIS)

Krauss, L.M.; Romanelli, P.

1990-01-01

A detailed reexamination is made of primordial big-bang nucleosynthesis (BBN), concentrating on the data for the main nuclear reactions leading to the production of Li-7, He-3 and D, and on the neutron half-life, relevant for He-4 production. The new values for reaction rates and uncertainties are then used as input in a Monte Carlo analysis of big bang nucleosynthesis of light elements. This allows confidence levels for the predictions of the standard BBN model to be high. 70 refs

Properties of Extreme Precipitation and Their Uncertainties in 3-year GPM Precipitation Radar Data

Science.gov (United States)

Liu, N.; Liu, C.

2017-12-01

Extreme high precipitation rates are often related to flash floods and have devastating impacts on human society and the environments. To better understand these rare events, 3-year Precipitation Features (PFs) are defined by grouping the contiguous areas with nonzero near-surface precipitation derived using Global Precipitation Measurement (GPM) Ku band Precipitation Radar (KuPR). The properties of PFs with extreme precipitation rates greater than 20, 50, 100 mm/hr, such as the geographical distribution, volumetric precipitation contribution, seasonal and diurnal variations, are examined. In addition to the large seasonal and regional variations, the rare extreme precipitation rates often have a larger contribution to the local total precipitation. Extreme precipitation rates occur more often over land than over ocean. The challenges in the retrieval of extreme precipitation might be from the attenuation correction and large uncertainties in the Z-R relationships from near-surface radar reflectivity to precipitation rates. These potential uncertainties are examined by using collocated ground based radar reflectivity and precipitation retrievals.

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

Uncertainty analysis and design optimization of hybrid rocket motor powered vehicle for suborbital flight

Directory of Open Access Journals (Sweden)

Zhu Hao

2015-06-01

Full Text Available In this paper, we propose an uncertainty analysis and design optimization method and its applications on a hybrid rocket motor (HRM powered vehicle. The multidisciplinary design model of the rocket system is established and the design uncertainties are quantified. The sensitivity analysis of the uncertainties shows that the uncertainty generated from the error of fuel regression rate model has the most significant effect on the system performances. Then the differences between deterministic design optimization (DDO and uncertainty-based design optimization (UDO are discussed. Two newly formed uncertainty analysis methods, including the Kriging-based Monte Carlo simulation (KMCS and Kriging-based Taylor series approximation (KTSA, are carried out using a global approximation Kriging modeling method. Based on the system design model and the results of design uncertainty analysis, the design optimization of an HRM powered vehicle for suborbital flight is implemented using three design optimization methods: DDO, KMCS and KTSA. The comparisons indicate that the two UDO methods can enhance the design reliability and robustness. The researches and methods proposed in this paper can provide a better way for the general design of HRM powered vehicles.

Deterministic uncertainty analysis

International Nuclear Information System (INIS)

Worley, B.A.

1987-01-01

Uncertainties of computer results are of primary interest in applications such as high-level waste (HLW) repository performance assessment in which experimental validation is not possible or practical. This work presents an alternate deterministic approach for calculating uncertainties that has the potential to significantly reduce the number of computer runs required for conventional statistical analysis. 7 refs., 1 fig

Uncertainty and simulation

International Nuclear Information System (INIS)

Depres, B.; Dossantos-Uzarralde, P.

2009-01-01

More than 150 researchers and engineers from universities and the industrial world met to discuss on the new methodologies developed around assessing uncertainty. About 20 papers were presented and the main topics were: methods to study the propagation of uncertainties, sensitivity analysis, nuclear data covariances or multi-parameter optimisation. This report gathers the contributions of CEA researchers and engineers

The uncertainty budget in pharmaceutical industry

DEFF Research Database (Denmark)

Heydorn, Kaj

of their uncertainty, exactly as described in GUM [2]. Pharmaceutical industry has therefore over the last 5 years shown increasing interest in accreditation according to ISO 17025 [3], and today uncertainty budgets are being developed for all so-called critical measurements. The uncertainty of results obtained...... that the uncertainty of a particular result is independent of the method used for its estimation. Several examples of uncertainty budgets for critical parameters based on the bottom-up procedure will be discussed, and it will be shown how the top-down method is used as a means of verifying uncertainty budgets, based...

Uncertainty and operational considerations in mass prophylaxis workforce planning.

Science.gov (United States)

Hupert, Nathaniel; Xiong, Wei; King, Kathleen; Castorena, Michelle; Hawkins, Caitlin; Wu, Cindie; Muckstadt, John A

2009-12-01

The public health response to an influenza pandemic or other large-scale health emergency may include mass prophylaxis using multiple points of dispensing (PODs) to deliver countermeasures rapidly to affected populations. Computer models created to date to determine "optimal" staffing levels at PODs typically assume stable patient demand for service. The authors investigated POD function under dynamic and uncertain operational environments. The authors constructed a Monte Carlo simulation model of mass prophylaxis (the Dynamic POD Simulator, or D-PODS) to assess the consequences of nonstationary patient arrival patterns on POD function under a variety of POD layouts and staffing plans. Compared are the performance of a standard POD layout under steady-state and variable patient arrival rates that may mimic real-life variation in patient demand. To achieve similar performance, PODs functioning under nonstationary patient arrival rates require higher staffing levels than would be predicted using the assumption of stationary arrival rates. Furthermore, PODs may develop severe bottlenecks unless staffing levels vary over time to meet changing patient arrival patterns. Efficient POD networks therefore require command and control systems capable of dynamically adjusting intra- and inter-POD staff levels to meet demand. In addition, under real-world operating conditions of heightened uncertainty, fewer large PODs will require a smaller total staff than many small PODs to achieve comparable performance. Modeling environments that capture the effects of fundamental uncertainties in public health disasters are essential for the realistic evaluation of response mechanisms and policies. D-PODS quantifies POD operational efficiency under more realistic conditions than have been modeled previously. The authors' experiments demonstrate that effective POD staffing plans must be responsive to variation and uncertainty in POD arrival patterns. These experiments highlight the need

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

Directory of Open Access Journals (Sweden)

Kunlin Wei

2010-05-01

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

Assessing the reliability of calculated catalytic ammonia synthesis rates

DEFF Research Database (Denmark)

Medford, Andrew James; Wellendorff, Jess; Vojvodic, Aleksandra

2014-01-01

We introduce a general method for estimating the uncertainty in calculated materials properties based on density functional theory calculations. We illustrate the approach for a calculation of the catalytic rate of ammonia synthesis over a range of transition-metal catalysts. The correlation...... between errors in density functional theory calculations is shown to play an important role in reducing the predicted error on calculated rates. Uncertainties depend strongly on reaction conditions and catalyst material, and the relative rates between different catalysts are considerably better described...

LOFT uncertainty-analysis methodology

International Nuclear Information System (INIS)

Lassahn, G.D.

1983-01-01

The methodology used for uncertainty analyses of measurements in the Loss-of-Fluid Test (LOFT) nuclear-reactor-safety research program is described and compared with other methodologies established for performing uncertainty analyses

LOFT uncertainty-analysis methodology

International Nuclear Information System (INIS)

Lassahn, G.D.

1983-01-01

The methodology used for uncertainty analyses of measurements in the Loss-of-Fluid Test (LOFT) nuclear reactor safety research program is described and compared with other methodologies established for performing uncertainty analyses

Do Orthopaedic Surgeons Acknowledge Uncertainty?

NARCIS (Netherlands)

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

2016-01-01

Much of the decision-making in orthopaedics rests on uncertain evidence. Uncertainty is therefore part of our normal daily practice, and yet physician uncertainty regarding treatment could diminish patients' health. It is not known if physician uncertainty is a function of the evidence alone or if

Uncertainty quantification of ion chemistry in lean and stoichiometric homogenous mixtures of methane, oxygen, and argon

KAUST Repository

Kim, Daesang

2015-07-01

Uncertainty quantification (UQ) methods are implemented to obtain a quantitative characterization of the evolution of electrons and ions during the ignition of methane-oxygen mixtures under lean and stoichiometric conditions. The GRI-Mech 3.0 mechanism is combined with an extensive set of ion chemistry pathways and the forward propagation of uncertainty from model parameters to observables is performed using response surfaces. The UQ analysis considers 22 uncertain rate parameters, which include both chemi-ionization, proton transfer, and electron attachment reactions as well as neutral reactions pertaining to the chemistry of the CH radical. The uncertainty ranges for each rate parameter are discussed. Our results indicate that the uncertainty in the time evolution of the electron number density is due mostly to the chemi-ionization reaction CH+O⇌HCO+ +E- and to the main CH consumption reaction CH+O2 ⇌O+HCO. Similar conclusions hold for the hydronium ion H3O+, since electrons and H3O+ account for more than 99% of the total negative and positive charge density, respectively. Surprisingly, the statistics of the number density of charged species show very little sensitivity to the uncertainty in the rate of the recombination reaction H3O+ +E- →products, until very late in the decay process, when the electron number density has fallen below 20% of its peak value. Finally, uncertainties in the secondary reactions within networks leading to the formation of minor ions (e.g., C2H3O+, HCO+, OH-, and O-) do not play any role in controlling the mean and variance of electrons and H3O+, but do affect the statistics of the minor ions significantly. The observed trends point to the role of key neutral reactions in controlling the mean and variance of the charged species number density in an indirect fashion. Furthermore, total sensitivity indices provide quantitative metrics to focus future efforts aiming at improving the rates of key reactions responsible for the

Uncertainty quantification of ion chemistry in lean and stoichiometric homogenous mixtures of methane, oxygen, and argon

KAUST Repository

Kim, Daesang; Rizzi, Francesco; Cheng, Kwok Wah; Han, Jie; Bisetti, Fabrizio; Knio, Omar Mohamad

2015-01-01

Uncertainty quantification (UQ) methods are implemented to obtain a quantitative characterization of the evolution of electrons and ions during the ignition of methane-oxygen mixtures under lean and stoichiometric conditions. The GRI-Mech 3.0 mechanism is combined with an extensive set of ion chemistry pathways and the forward propagation of uncertainty from model parameters to observables is performed using response surfaces. The UQ analysis considers 22 uncertain rate parameters, which include both chemi-ionization, proton transfer, and electron attachment reactions as well as neutral reactions pertaining to the chemistry of the CH radical. The uncertainty ranges for each rate parameter are discussed. Our results indicate that the uncertainty in the time evolution of the electron number density is due mostly to the chemi-ionization reaction CH+O⇌HCO+ +E- and to the main CH consumption reaction CH+O2 ⇌O+HCO. Similar conclusions hold for the hydronium ion H3O+, since electrons and H3O+ account for more than 99% of the total negative and positive charge density, respectively. Surprisingly, the statistics of the number density of charged species show very little sensitivity to the uncertainty in the rate of the recombination reaction H3O+ +E- →products, until very late in the decay process, when the electron number density has fallen below 20% of its peak value. Finally, uncertainties in the secondary reactions within networks leading to the formation of minor ions (e.g., C2H3O+, HCO+, OH-, and O-) do not play any role in controlling the mean and variance of electrons and H3O+, but do affect the statistics of the minor ions significantly. The observed trends point to the role of key neutral reactions in controlling the mean and variance of the charged species number density in an indirect fashion. Furthermore, total sensitivity indices provide quantitative metrics to focus future efforts aiming at improving the rates of key reactions responsible for the

Decay heat and gamma dose-rate prediction capability in spent LWR fuel

International Nuclear Information System (INIS)

Neely, G.J.; Schmittroth, F.

1982-08-01

The ORIGEN2 code was established as a valid means to predict decay heat from LWR spent fuel assemblies for decay times up to 10,000 year. Calculational uncertainties ranged from 8.6% to a maximum of 16% at 2.5 years and 300 years cooling time, respectively. The calculational uncertainties at 2.5 years cooling time are supported by experiment. Major sources of uncertainty at the 2.5 year cooling time were identifed as irradiation history (5.7%) and nuclear data together with calculational methods (6.3%). The QAD shielding code was established as a valid means to predict interior and exterior gamma dose rates of spent LWR fuel assemblies. A calculational/measurement comparison was done on two assemblies with different irradiation histories and supports a 35% calculational uncertainty at the 1.8 and 3.0 year decay times studied. Uncertainties at longer times are expected to increase, but not significantly, due to an increased contribution from the actinides whose inventories are assigned a higher uncertainty. The uncertainty in decay heat rises to a maximum of 16% due to actinide uncertainties. A previous study was made of the neutron emission rate from a typical Turkey Point Unit 3, Region 4 spent fuel assembly at 5 years decay time. A conservative estimate of the neutron dose rate at the assembly surface was less than 0.5 rem/hr

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.

Justification for recommended uncertainties

International Nuclear Information System (INIS)

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

2007-01-01

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

Impact of magnitude uncertainties on seismic catalogue properties

Science.gov (United States)

Leptokaropoulos, K. M.; Adamaki, A. K.; Roberts, R. G.; Gkarlaouni, C. G.; Paradisopoulou, P. M.

2018-05-01

Catalogue-based studies are of central importance in seismological research, to investigate the temporal, spatial and size distribution of earthquakes in specified study areas. Methods for estimating the fundamental catalogue parameters like the Gutenberg-Richter (G-R) b-value and the completeness magnitude (Mc) are well established and routinely applied. However, the magnitudes reported in seismicity catalogues contain measurement uncertainties which may significantly distort the estimation of the derived parameters. In this study, we use numerical simulations of synthetic data sets to assess the reliability of different methods for determining b-value and Mc, assuming the G-R law validity. After contaminating the synthetic catalogues with Gaussian noise (with selected standard deviations), the analysis is performed for numerous data sets of different sample size (N). The noise introduced to the data generally leads to a systematic overestimation of magnitudes close to and above Mc. This fact causes an increase of the average number of events above Mc, which in turn leads to an apparent decrease of the b-value. This may result to a significant overestimation of seismicity rate even well above the actual completeness level. The b-value can in general be reliably estimated even for relatively small data sets (N < 1000) when only magnitudes higher than the actual completeness level are used. Nevertheless, a correction of the total number of events belonging in each magnitude class (i.e. 0.1 unit) should be considered, to deal with the magnitude uncertainty effect. Because magnitude uncertainties (here with the form of Gaussian noise) are inevitable in all instrumental catalogues, this finding is fundamental for seismicity rate and seismic hazard assessment analyses. Also important is that for some data analyses significant bias cannot necessarily be avoided by choosing a high Mc value for analysis. In such cases, there may be a risk of severe miscalculation of

Adjoint-Based Uncertainty Quantification with MCNP

Energy Technology Data Exchange (ETDEWEB)

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

2011-09-01

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

Parameter Uncertainty on AGCM-simulated Tropical Cyclones

Science.gov (United States)

He, F.

2015-12-01

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

A risk assessment methodology for incorporating uncertainties using fuzzy concepts

International Nuclear Information System (INIS)

Cho, Hyo-Nam; Choi, Hyun-Ho; Kim, Yoon-Bae

2002-01-01

This paper proposes a new methodology for incorporating uncertainties using fuzzy concepts into conventional risk assessment frameworks. This paper also introduces new forms of fuzzy membership curves, designed to consider the uncertainty range that represents the degree of uncertainties involved in both probabilistic parameter estimates and subjective judgments, since it is often difficult or even impossible to precisely estimate the occurrence rate of an event in terms of one single crisp probability. It is to be noted that simple linguistic variables such as 'High/Low' and 'Good/Bad' have the limitations in quantifying the various risks inherent in construction projects, but only represent subjective mental cognition adequately. Therefore, in this paper, the statements that include some quantification with giving specific value or scale, such as 'Close to any value' or 'Higher/Lower than analyzed value', are used in order to get over the limitations. It may be stated that the proposed methodology will be very useful for the systematic and rational risk assessment of construction projects

Risk Analysis of Reservoir Flood Routing Calculation Based on Inflow Forecast Uncertainty

Directory of Open Access Journals (Sweden)

Binquan Li

2016-10-01

Full Text Available Possible risks in reservoir flood control and regulation cannot be objectively assessed by deterministic flood forecasts, resulting in the probability of reservoir failure. We demonstrated a risk analysis of reservoir flood routing calculation accounting for inflow forecast uncertainty in a sub-basin of Huaihe River, China. The Xinanjiang model was used to provide deterministic flood forecasts, and was combined with the Hydrologic Uncertainty Processor (HUP to quantify reservoir inflow uncertainty in the probability density function (PDF form. Furthermore, the PDFs of reservoir water level (RWL and the risk rate of RWL exceeding a defined safety control level could be obtained. Results suggested that the median forecast (50th percentiles of HUP showed better agreement with observed inflows than the Xinanjiang model did in terms of the performance measures of flood process, peak, and volume. In addition, most observations (77.2% were bracketed by the uncertainty band of 90% confidence interval, with some small exceptions of high flows. Results proved that this framework of risk analysis could provide not only the deterministic forecasts of inflow and RWL, but also the fundamental uncertainty information (e.g., 90% confidence band for the reservoir flood routing calculation.

Linear Programming Problems for Generalized Uncertainty

Science.gov (United States)

Thipwiwatpotjana, Phantipa

2010-01-01

Uncertainty occurs when there is more than one realization that can represent an information. This dissertation concerns merely discrete realizations of an uncertainty. Different interpretations of an uncertainty and their relationships are addressed when the uncertainty is not a probability of each realization. A well known model that can handle…

Uncertainty analysis in estimating Japanese ingestion of global fallout Cs-137 using health risk evaluation model

International Nuclear Information System (INIS)

Shimada, Yoko; Morisawa, Shinsuke

1998-01-01

Most of model estimation of the environmental contamination includes some uncertainty associated with the parameter uncertainty in the model. In this study, the uncertainty was analyzed in a model for evaluating the ingestion of radionuclide caused by the long-term global low-level radioactive contamination by using various uncertainty analysis methods: the percentile estimate, the robustness analysis and the fuzzy estimate. The model is mainly composed of five sub-models, which include their own uncertainty; we also analyzed the uncertainty. The major findings obtained in this study include that the possibility of the discrepancy between predicted value by the model simulation and the observed data is less than 10%; the uncertainty of the predicted value is higher before 1950 and after 1980; the uncertainty of the predicted value can be reduced by decreasing the uncertainty of some environmental parameters in the model; the reliability of the model can definitively depend on the following environmental factors: direct foliar absorption coefficient, transfer factor of radionuclide from stratosphere down to troposphere, residual rate by food processing and cooking, transfer factor of radionuclide in ocean and sedimentation in ocean. (author)

Towards quantifying uncertainty in predictions of Amazon 'dieback'.

Science.gov (United States)

Huntingford, Chris; Fisher, Rosie A; Mercado, Lina; Booth, Ben B B; Sitch, Stephen; Harris, Phil P; Cox, Peter M; Jones, Chris D; Betts, Richard A; Malhi, Yadvinder; Harris, Glen R; Collins, Mat; Moorcroft, Paul

2008-05-27

Simulations with the Hadley Centre general circulation model (HadCM3), including carbon cycle model and forced by a 'business-as-usual' emissions scenario, predict a rapid loss of Amazonian rainforest from the middle of this century onwards. The robustness of this projection to both uncertainty in physical climate drivers and the formulation of the land surface scheme is investigated. We analyse how the modelled vegetation cover in Amazonia responds to (i) uncertainty in the parameters specified in the atmosphere component of HadCM3 and their associated influence on predicted surface climate. We then enhance the land surface description and (ii) implement a multilayer canopy light interception model and compare with the simple 'big-leaf' approach used in the original simulations. Finally, (iii) we investigate the effect of changing the method of simulating vegetation dynamics from an area-based model (TRIFFID) to a more complex size- and age-structured approximation of an individual-based model (ecosystem demography). We find that the loss of Amazonian rainforest is robust across the climate uncertainty explored by perturbed physics simulations covering a wide range of global climate sensitivity. The introduction of the refined light interception model leads to an increase in simulated gross plant carbon uptake for the present day, but, with altered respiration, the net effect is a decrease in net primary productivity. However, this does not significantly affect the carbon loss from vegetation and soil as a consequence of future simulated depletion in soil moisture; the Amazon forest is still lost. The introduction of the more sophisticated dynamic vegetation model reduces but does not halt the rate of forest dieback. The potential for human-induced climate change to trigger the loss of Amazon rainforest appears robust within the context of the uncertainties explored in this paper. Some further uncertainties should be explored, particularly with respect to the

Uncertainty and validation. Effect of model complexity on uncertainty estimates

Energy Technology Data Exchange (ETDEWEB)

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

1996-09-01

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

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

Measurement uncertainty: Friend or foe?

Science.gov (United States)

Infusino, Ilenia; Panteghini, Mauro

2018-02-02

The definition and enforcement of a reference measurement system, based on the implementation of metrological traceability of patients' results to higher order reference methods and materials, together with a clinically acceptable level of measurement uncertainty, are fundamental requirements to produce accurate and equivalent laboratory results. The uncertainty associated with each step of the traceability chain should be governed to obtain a final combined uncertainty on clinical samples fulfilling the requested performance specifications. It is important that end-users (i.e., clinical laboratory) may know and verify how in vitro diagnostics (IVD) manufacturers have implemented the traceability of their calibrators and estimated the corresponding uncertainty. However, full information about traceability and combined uncertainty of calibrators is currently very difficult to obtain. Laboratory professionals should investigate the need to reduce the uncertainty of the higher order metrological references and/or to increase the precision of commercial measuring systems. Accordingly, the measurement uncertainty should not be considered a parameter to be calculated by clinical laboratories just to fulfil the accreditation standards, but it must become a key quality indicator to describe both the performance of an IVD measuring system and the laboratory itself. Copyright © 2018 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

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

International Nuclear Information System (INIS)

Mensing, R.W.

1985-01-01

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

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

Science.gov (United States)

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

1998-01-01

An assessment of the experimental uncertainty in obtaining the kinetic activation energy from thermogravimetric analysis (TGA) data is presented. A neat phenolic resin, Borden SC1O08, was heated at three heating rates to obtain weight loss vs temperature data. Activation energy was calculated by two methods: the traditional Flynn and Wall method based on the slope of log(q) versus 1/T, and a modification of this method where the ordinate and abscissa are reversed in the linear regression. The modified method produced a more accurate curve fit of the data, was more sensitive to data nonlinearity, and gave a value of activation energy 75 percent greater than the original method. An uncertainty analysis using the modified method yielded a 60 percent uncertainty in the average activation energy. Based on this result, the activation energy for a carbon-phenolic material was doubled and used to calculate the ablation rate In a typical solid rocket environment. Doubling the activation energy increased surface recession by 3 percent. Current TGA data reduction techniques that use the traditional Flynn and Wall approach to calculate activation energy should be changed to the modified method.

Left Dislocation in North-Eastern Neo-Aramaic dialects | Khan ...

African Journals Online (AJOL)

The North-Eastern Neo-Aramaic (NENA) dialects, which are the focus of this paper, were spoken across a wide area encompassing northern Iraq, north-west Iran, south-eastern Turkey, Armenia and Georgia. In these spoken dialects a distinction should be made between two major types of Left Dislocation (LD) structures.

Uncertainty Characterization of Reactor Vessel Fracture Toughness

International Nuclear Information System (INIS)

Li, Fei; Modarres, Mohammad

2002-01-01

To perform fracture mechanics analysis of reactor vessel, fracture toughness (K Ic ) at various temperatures would be necessary. In a best estimate approach, K Ic uncertainties resulting from both lack of sufficient knowledge and randomness in some of the variables of K Ic must be characterized. Although it may be argued that there is only one type of uncertainty, which is lack of perfect knowledge about the subject under study, as a matter of practice K Ic uncertainties can be divided into two types: aleatory and epistemic. Aleatory uncertainty is related to uncertainty that is very difficult to reduce, if not impossible; epistemic uncertainty, on the other hand, can be practically reduced. Distinction between aleatory and epistemic uncertainties facilitates decision-making under uncertainty and allows for proper propagation of uncertainties in the computation process. Typically, epistemic uncertainties representing, for example, parameters of a model are sampled (to generate a 'snapshot', single-value of the parameters), but the totality of aleatory uncertainties is carried through the calculation as available. In this paper a description of an approach to account for these two types of uncertainties associated with K Ic has been provided. (authors)

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

Science.gov (United States)

Alonso, Ariel; Laenen, Annouschka

2013-05-01

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

Strategy under uncertainty.

Science.gov (United States)

Courtney, H; Kirkland, J; Viguerie, P

1997-01-01

At the heart of the traditional approach to strategy lies the assumption that by applying a set of powerful analytic tools, executives can predict the future of any business accurately enough to allow them to choose a clear strategic direction. But what happens when the environment is so uncertain that no amount of analysis will allow us to predict the future? What makes for a good strategy in highly uncertain business environments? The authors, consultants at McKinsey & Company, argue that uncertainty requires a new way of thinking about strategy. All too often, they say, executives take a binary view: either they underestimate uncertainty to come up with the forecasts required by their companies' planning or capital-budging processes, or they overestimate it, abandon all analysis, and go with their gut instinct. The authors outline a new approach that begins by making a crucial distinction among four discrete levels of uncertainty that any company might face. They then explain how a set of generic strategies--shaping the market, adapting to it, or reserving the right to play at a later time--can be used in each of the four levels. And they illustrate how these strategies can be implemented through a combination of three basic types of actions: big bets, options, and no-regrets moves. The framework can help managers determine which analytic tools can inform decision making under uncertainty--and which cannot. At a broader level, it offers executives a discipline for thinking rigorously and systematically about uncertainty and its implications for strategy.

Where do uncertainties reside within environmental risk assessments? Expert opinion on uncertainty distributions for pesticide risks to surface water organisms.

Science.gov (United States)

Skinner, Daniel J C; Rocks, Sophie A; Pollard, Simon J T

2016-12-01

A reliable characterisation of uncertainties can aid uncertainty identification during environmental risk assessments (ERAs). However, typologies can be implemented inconsistently, causing uncertainties to go unidentified. We present an approach based on nine structured elicitations, in which subject-matter experts, for pesticide risks to surface water organisms, validate and assess three dimensions of uncertainty: its level (the severity of uncertainty, ranging from determinism to ignorance); nature (whether the uncertainty is epistemic or aleatory); and location (the data source or area in which the uncertainty arises). Risk characterisation contains the highest median levels of uncertainty, associated with estimating, aggregating and evaluating the magnitude of risks. Regarding the locations in which uncertainty is manifest, data uncertainty is dominant in problem formulation, exposure assessment and effects assessment. The comprehensive description of uncertainty described will enable risk analysts to prioritise the required phases, groups of tasks, or individual tasks within a risk analysis according to the highest levels of uncertainty, the potential for uncertainty to be reduced or quantified, or the types of location-based uncertainty, thus aiding uncertainty prioritisation during environmental risk assessments. In turn, it is expected to inform investment in uncertainty reduction or targeted risk management action. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Uncertainty budget for k0-NAA

International Nuclear Information System (INIS)

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

2000-01-01

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

Uncertainty 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

Decision making under uncertainty

International Nuclear Information System (INIS)

Cyert, R.M.

1989-01-01

This paper reports on ways of improving the reliability of products and systems in this country if we are to survive as a first-rate industrial power. The use of statistical techniques have, since the 1920s, been viewed as one of the methods for testing quality and estimating the level of quality in a universe of output. Statistical quality control is not relevant, generally, to improving systems in an industry like yours, but certainly the use of probability concepts is of significance. In addition, when it is recognized that part of the problem involves making decisions under uncertainty, it becomes clear that techniques such as sequential decision making and Bayesian analysis become major methodological approaches that must be utilized

Development of default uncertainties for the value/benefit attributes in the regulatory analysis technical evaluation handbook

International Nuclear Information System (INIS)

Gallucci, Raymond H.V.

2016-01-01

Highlights: • Uncertainties for values/benefits. • Upper bound four times higher than mean. • Distributional histograms. - Abstract: NUREG/BR-0184, Regulatory Analysis Technical Evaluation (RATE) Handbook, was produced in 1997 as an update to the original NUREG/CR-3568, A Handbook for Value-Impact Assessment (1983). Both documents, especially the later RATE Handbook, have been used extensively by the USNRC and its contractors not only for regulatory analyses to support backfit considerations but also for similar applications, such as Severe Accident Management Alternative (SAMA) analyses as part of license renewals. While both provided high-level guidance on the performance of uncertainty analyses for the various value/benefit attributes, detailed quantification was not of prime interest at the times of the Handbooks’ development, defaulting only to best estimates with low and high bounds on these attributes. As the USNRC examines the possibility of updating the RATE Handbook, renewed interest in a more quantitative approach to uncertainty analyses for the attributes has surfaced. As the result of an effort to enhance the RATE Handbook to permit at least default uncertainty analyses for the value/benefit attributes, it has proven feasible to assign default uncertainties in terms of 95th %ile upper bounds (and absolute lower bounds) on the five dominant value/benefit attributes, and their sum, when performing a regulatory analysis via the RATE Handbook. Appropriate default lower bounds of zero (no value/benefit) and an upper bound (95th %ile) that is four times higher than the mean (for individual value/benefit attributes) or three times higher (for their summation) can be recommended. Distributions in the form of histograms on the summed value/benefit attributes are also provided which could be combined, after appropriate scaling and most likely via simulation, with their counterpart(s) from the impact/cost analysis to yield a final distribution on the net

Investment under Uncertainty and Financial Crisis

DEFF Research Database (Denmark)

Jensen, Camilla

The objective of the paper is to test the stability hypothesis – that foreign investors are relatively insulated from uncertainty and how it spills over on their investment adjustment cost. The Q model (implying that investments are explained by the fundamental value of the firm) is implemented...... with reasonable success for firm level panels in Turkey. Robustness of the results and despite the general obstacle that inflation poses on the study is increased by applying different datasets with different time horizons, different measures of investment and profitability and different problems of attrition...... it is found that the decline in the growth of the investment rate for domestic firms is at least twice as high compared to the decline in the growth of the investment rate among foreign held firms....

Verification of uncertainty budgets

DEFF Research Database (Denmark)

Heydorn, Kaj; Madsen, B.S.

2005-01-01

, and therefore it is essential that the applicability of the overall uncertainty budget to actual measurement results be verified on the basis of current experimental data. This should be carried out by replicate analysis of samples taken in accordance with the definition of the measurand, but representing...... the full range of matrices and concentrations for which the budget is assumed to be valid. In this way the assumptions made in the uncertainty budget can be experimentally verified, both as regards sources of variability that are assumed negligible, and dominant uncertainty components. Agreement between...

Entropic uncertainty relations-a survey

International Nuclear Information System (INIS)

Wehner, Stephanie; Winter, Andreas

2010-01-01

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

Propagation of dynamic measurement uncertainty

International Nuclear Information System (INIS)

Hessling, J P

2011-01-01

The time-dependent measurement uncertainty has been evaluated in a number of recent publications, starting from a known uncertain dynamic model. This could be defined as the 'downward' propagation of uncertainty from the model to the targeted measurement. The propagation of uncertainty 'upward' from the calibration experiment to a dynamic model traditionally belongs to system identification. The use of different representations (time, frequency, etc) is ubiquitous in dynamic measurement analyses. An expression of uncertainty in dynamic measurements is formulated for the first time in this paper independent of representation, joining upward as well as downward propagation. For applications in metrology, the high quality of the characterization may be prohibitive for any reasonably large and robust model to pass the whiteness test. This test is therefore relaxed by not directly requiring small systematic model errors in comparison to the randomness of the characterization. Instead, the systematic error of the dynamic model is propagated to the uncertainty of the measurand, analogously but differently to how stochastic contributions are propagated. The pass criterion of the model is thereby transferred from the identification to acceptance of the total accumulated uncertainty of the measurand. This increases the relevance of the test of the model as it relates to its final use rather than the quality of the calibration. The propagation of uncertainty hence includes the propagation of systematic model errors. For illustration, the 'upward' propagation of uncertainty is applied to determine if an appliance box is damaged in an earthquake experiment. In this case, relaxation of the whiteness test was required to reach a conclusive result

Uncertainties associated with the use of optically stimulated luminescence in personal dosimetry

International Nuclear Information System (INIS)

Benevides, L.; Romanyukha, A.; Hull, F.; Duffy, M.; Voss, S.; Moscovitch, M.

2011-01-01

This study investigates several sources of uncertainty associated with the application of optically stimulated luminescence (OSL) to personal dosimetry. A commercial OSL system based on Al 2 O 3 :C was used for this study. First, it is demonstrated that the concept of repeated evaluation (readout) of the same dosemeter, often referred to as 're-analysis', can introduce uncertainty in the re-estimated dose. This uncertainty is associated with the fact that the re-analysis process depletes some of the populated traps, resulting in a continuous decrease of the OSL signal with each repeated reading. Furthermore, the rate of depletion may be dose-dependent. Second, it is shown that the previously reported light-induced fading in this system is the result of light leaks through miniature openings in the dosemeter badge. (authors)

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

Uncertainty quantification in resonance absorption

International Nuclear Information System (INIS)

Williams, M.M.R.

2012-01-01

We assess the uncertainty in the resonance escape probability due to uncertainty in the neutron and radiation line widths for the first 21 resonances in 232 Th as given by . Simulation, quadrature and polynomial chaos methods are used and the resonance data are assumed to obey a beta distribution. We find the uncertainty in the total resonance escape probability to be the equivalent, in reactivity, of 75–130 pcm. Also shown are pdfs of the resonance escape probability for each resonance and the variation of the uncertainty with temperature. The viability of the polynomial chaos expansion method is clearly demonstrated.

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)

Mechanics and uncertainty

CERN Document Server

Lemaire, Maurice

2014-01-01

Science is a quest for certainty, but lack of certainty is the driving force behind all of its endeavors. This book, specifically, examines the uncertainty of technological and industrial science. Uncertainty and Mechanics studies the concepts of mechanical design in an uncertain setting and explains engineering techniques for inventing cost-effective products. Though it references practical applications, this is a book about ideas and potential advances in mechanical science.

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)

Cross section sensitivity and uncertainty analysis for European INTOR and U.S. FED designs

International Nuclear Information System (INIS)

Pelloni, S.

1982-06-01

The European Community International Tokamak Reactor (INTOR-EC) and U.S. Fusion Engineering Device (FED) were used as a basis to investigate the uncertainties of several neutronics performance parameters such as tritium breeding ratio in the blanket, atomic displacement rate in the copper stabilizer, and nuclear heating in the epoxy-based insulator that arise due to nuclear data uncertainties and data processing discrepancies. Neutronics calculations were performed and reaction rates estimated for the recent INTOR-EC using the DLC-37 and DLC-41 cross section libraries. In general, the basic cross section data are known accurately enough to determine the tritium breeding ratio of the INTOR-EC within +-2%. The atomic displacement rate and nuclear heating rate in the superconducting magnet of FED (and presumably also INTOR-EC), however, can be predicted to only about +-12% to 24%. If additional accuracy is required, improved measurements of the iron, chromium, and nickel cross sections in the energy range between 12 and 14 MeV will be needed. (Auth.)

Uncertainty in social dilemmas

NARCIS (Netherlands)

Kwaadsteniet, Erik Willem de

2007-01-01

This dissertation focuses on social dilemmas, and more specifically, on environmental uncertainty in these dilemmas. Real-life social dilemma situations are often characterized by uncertainty. For example, fishermen mostly do not know the exact size of the fish population (i.e., resource size

CEC/USDOE workshop on uncertainty analysis

International Nuclear Information System (INIS)

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

1990-07-01

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

Refinement of the concept of uncertainty.

Science.gov (United States)

Penrod, J

2001-04-01

To analyse the conceptual maturity of uncertainty; to develop an expanded theoretical definition of uncertainty; to advance the concept using methods of concept refinement; and to analyse congruency with the conceptualization of uncertainty presented in the theory of hope, enduring, and suffering. Uncertainty is of concern in nursing as people experience complex life events surrounding health. In an earlier nursing study that linked the concepts of hope, enduring, and suffering into a single theoretical scheme, a state best described as 'uncertainty' arose. This study was undertaken to explore how this conceptualization fit with the scientific literature on uncertainty and to refine the concept. Initially, a concept analysis using advanced methods described by Morse, Hupcey, Mitcham and colleagues was completed. The concept was determined to be partially mature. A theoretical definition was derived and techniques of concept refinement using the literature as data were applied. The refined concept was found to be congruent with the concept of uncertainty that had emerged in the model of hope, enduring and suffering. Further investigation is needed to explore the extent of probabilistic reasoning and the effects of confidence and control on feelings of uncertainty and certainty.

Characterizing Epistemic Uncertainty for Launch Vehicle Designs

Science.gov (United States)

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

2016-01-01

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

Applied research in uncertainty modeling and analysis

CERN Document Server

Ayyub, Bilal

2005-01-01

Uncertainty has been a concern to engineers, managers, and scientists for many years. For a long time uncertainty has been considered synonymous with random, stochastic, statistic, or probabilistic. Since the early sixties views on uncertainty have become more heterogeneous. In the past forty years numerous tools that model uncertainty, above and beyond statistics, have been proposed by several engineers and scientists. The tool/method to model uncertainty in a specific context should really be chosen by considering the features of the phenomenon under consideration, not independent of what is known about the system and what causes uncertainty. In this fascinating overview of the field, the authors provide broad coverage of uncertainty analysis/modeling and its application. Applied Research in Uncertainty Modeling and Analysis presents the perspectives of various researchers and practitioners on uncertainty analysis and modeling outside their own fields and domain expertise. Rather than focusing explicitly on...

Uncertainty Analyses and Strategy

International Nuclear Information System (INIS)

Kevin Coppersmith

2001-01-01

The DOE identified a variety of uncertainties, arising from different sources, during its assessment of the performance of a potential geologic repository at the Yucca Mountain site. In general, the number and detail of process models developed for the Yucca Mountain site, and the complex coupling among those models, make the direct incorporation of all uncertainties difficult. The DOE has addressed these issues in a number of ways using an approach to uncertainties that is focused on producing a defensible evaluation of the performance of a potential repository. The treatment of uncertainties oriented toward defensible assessments has led to analyses and models with so-called ''conservative'' assumptions and parameter bounds, where conservative implies lower performance than might be demonstrated with a more realistic representation. The varying maturity of the analyses and models, and uneven level of data availability, result in total system level analyses with a mix of realistic and conservative estimates (for both probabilistic representations and single values). That is, some inputs have realistically represented uncertainties, and others are conservatively estimated or bounded. However, this approach is consistent with the ''reasonable assurance'' approach to compliance demonstration, which was called for in the U.S. Nuclear Regulatory Commission's (NRC) proposed 10 CFR Part 63 regulation (64 FR 8640 [DIRS 101680]). A risk analysis that includes conservatism in the inputs will result in conservative risk estimates. Therefore, the approach taken for the Total System Performance Assessment for the Site Recommendation (TSPA-SR) provides a reasonable representation of processes and conservatism for purposes of site recommendation. However, mixing unknown degrees of conservatism in models and parameter representations reduces the transparency of the analysis and makes the development of coherent and consistent probability statements about projected repository

An examination of the relationships among uncertainty, appraisal, and information-seeking behavior proposed in uncertainty management theory.

Science.gov (United States)

Rains, Stephen A; Tukachinsky, Riva

2015-01-01

Uncertainty management theory (UMT; Brashers, 2001, 2007) is rooted in the assumption that, as opposed to being inherently negative, health-related uncertainty is appraised for its meaning. Appraisals influence subsequent behaviors intended to manage uncertainty, such as information seeking. This study explores the connections among uncertainty, appraisal, and information-seeking behavior proposed in UMT. A laboratory study was conducted in which participants (N = 157) were primed to feel and desire more or less uncertainty about skin cancer and were given the opportunity to search for skin cancer information using the World Wide Web. The results show that desired uncertainty level predicted appraisal intensity, and appraisal intensity predicted information-seeking depth-although the latter relationship was in the opposite direction of what was expected.

Uncertainty

International Nuclear Information System (INIS)

Silva, T.A. da

1988-01-01

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

Uncertainty estimation with a small number of measurements, part II: a redefinition of uncertainty and an estimator method

Science.gov (United States)

Huang, Hening

2018-01-01

This paper is the second (Part II) in a series of two papers (Part I and Part II). Part I has quantitatively discussed the fundamental limitations of the t-interval method for uncertainty estimation with a small number of measurements. This paper (Part II) reveals that the t-interval is an ‘exact’ answer to a wrong question; it is actually misused in uncertainty estimation. This paper proposes a redefinition of uncertainty, based on the classical theory of errors and the theory of point estimation, and a modification of the conventional approach to estimating measurement uncertainty. It also presents an asymptotic procedure for estimating the z-interval. The proposed modification is to replace the t-based uncertainty with an uncertainty estimator (mean- or median-unbiased). The uncertainty estimator method is an approximate answer to the right question to uncertainty estimation. The modified approach provides realistic estimates of uncertainty, regardless of whether the population standard deviation is known or unknown, or if the sample size is small or large. As an application example of the modified approach, this paper presents a resolution to the Du-Yang paradox (i.e. Paradox 2), one of the three paradoxes caused by the misuse of the t-interval in uncertainty estimation.

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...

Analysis of uncertainties in CRAC2 calculations: wet deposition and plume rise

International Nuclear Information System (INIS)

Ward, R.C.; Kocher, D.C.; Hicks, B.B.; Hosker, R.P. Jr.; Ku, J.Y.; Rao, K.S.

1984-01-01

We have studied the sensitivity of results from the CRAC2 computer code, which predicts health impacts from a reactor-accident scenario, to uncertainties in selected meteorological models and parameters. The sources of uncertainty examined include the models for plume rise and wet deposition and the meteorological bin-sampling procedure. An alternative plume-rise model usually had little effect on predicted health impacts. In an alternative wet-deposition model, the scavenging rate depends only on storm type, rather than on rainfall rate and atmospheric stability class as in the CRAC2 model. Use of the alternative wet-deposition model in meteorological bin-sampling runs decreased predicted mean early injuries by as much as a factor of 2 to 3 and, for large release heights and sensible heat rates, decreased mean early fatalities by nearly an order of magnitude. The bin-sampling procedure in CRAC2 was expanded by dividing each rain bin into four bins that depend on rainfall rate. Use of the modified bin structure in conjunction with the CRAC2 wet-deposition model changed all predicted health impacts by less than a factor of 2. 9 references

A Bayesian approach to model uncertainty

International Nuclear Information System (INIS)

Buslik, A.

1994-01-01

A Bayesian approach to model uncertainty is taken. For the case of a finite number of alternative models, the model uncertainty is equivalent to parameter uncertainty. A derivation based on Savage's partition problem is given

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

Chemical model reduction under uncertainty

KAUST Repository

Najm, Habib; Galassi, R. Malpica; Valorani, M.

2016-01-01

We outline a strategy for chemical kinetic model reduction under uncertainty. We present highlights of our existing deterministic model reduction strategy, and describe the extension of the formulation to include parametric uncertainty in the detailed mechanism. We discuss the utility of this construction, as applied to hydrocarbon fuel-air kinetics, and the associated use of uncertainty-aware measures of error between predictions from detailed and simplified models.

Chemical model reduction under uncertainty

KAUST Repository

Najm, Habib

2016-01-05

We outline a strategy for chemical kinetic model reduction under uncertainty. We present highlights of our existing deterministic model reduction strategy, and describe the extension of the formulation to include parametric uncertainty in the detailed mechanism. We discuss the utility of this construction, as applied to hydrocarbon fuel-air kinetics, and the associated use of uncertainty-aware measures of error between predictions from detailed and simplified models.

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

Essays on model uncertainty in financial models

NARCIS (Netherlands)

Li, Jing

2018-01-01

This dissertation studies model uncertainty, particularly in financial models. It consists of two empirical chapters and one theoretical chapter. The first empirical chapter (Chapter 2) classifies model uncertainty into parameter uncertainty and misspecification uncertainty. It investigates the

Applications of uncertainty analysis to visual evaluation of density in radiographs

International Nuclear Information System (INIS)

Uchida, Suguru; Ohtsuka, Akiyoshi; Fujita, Hiroshi.

1981-01-01

Uncertainty analysis, developed as a method of absolute judgment in psychology, is applied to a method of radiographic image evaluation with perceptual fluctuations and to an examination of visual evaluation of density in radiographs. Subjects are composed of three groups of four neurosurgeons, four radiologic technologists and four nonprofessionals. By using a five-category rating scale, each observer is directed to classify 255 radiographs randomly presented without feedback. Characteristics of each observer and each group can be shown quantitatively by calculated information values. It is also described that bivariate uncertainty analysis or entropy method can be used to calculate the degree of agreement of evaluation. (author)

Applications of uncertainty analysis to visual evaluation of density in radiographs

Energy Technology Data Exchange (ETDEWEB)

Uchida, S [Gifu Univ. (Japan); Ohtsuka, A; Fujita, H

1981-03-01

Uncertainty analysis, developed as a method of absolute judgment in psychology, is applied to a method of radiographic image evaluation with perceptual fluctuations and to an examination of visual evaluation of density in radiographs. Subjects are composed of three groups of four neurosurgeons, four radiologic technologists and four nonprofessionals. By using a five-category rating scale, each observer is directed to classify 255 radiographs randomly presented without feedback. Characteristics of each observer and each group can be shown quantitatively by calculated information values. It is also described that bivariate uncertainty analysis or entropy method can be used to calculate the degree of agreement of evaluation.

How much is new information worth? Evaluating the financial benefit of resolving management uncertainty

Science.gov (United States)

Maxwell, Sean L.; Rhodes, Jonathan R.; Runge, Michael C.; Possingham, Hugh P.; Ng, Chooi Fei; McDonald Madden, Eve

2015-01-01

Conservation decision-makers face a trade-off between spending limited funds on direct management action, or gaining new information in an attempt to improve management performance in the future. Value-of-information analysis can help to resolve this trade-off by evaluating how much management performance could improve if new information was gained. Value-of-information analysis has been used extensively in other disciplines, but there are only a few examples where it has informed conservation planning, none of which have used it to evaluate the financial value of gaining new information. We address this gap by applying value-of-information analysis to the management of a declining koala Phascolarctos cinereuspopulation. Decision-makers responsible for managing this population face uncertainty about survival and fecundity rates, and how habitat cover affects mortality threats. The value of gaining new information about these uncertainties was calculated using a deterministic matrix model of the koala population to find the expected population growth rate if koala mortality threats were optimally managed under alternative model hypotheses, which represented the uncertainties faced by koala managers. Gaining new information about survival and fecundity rates and the effect of habitat cover on mortality threats will do little to improve koala management. Across a range of management budgets, no more than 1·7% of the budget should be spent on resolving these uncertainties. The value of information was low because optimal management decisions were not sensitive to the uncertainties we considered. Decisions were instead driven by a substantial difference in the cost efficiency of management actions. The value of information was up to forty times higher when the cost efficiencies of different koala management actions were similar. Synthesis and applications. This study evaluates the ecological and financial benefits of gaining new information to inform a conservation

Uncertainty estimation of ultrasonic thickness measurement

International Nuclear Information System (INIS)

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

2009-01-01

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

Uncertainties 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

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.

Chemical kinetic model uncertainty minimization through laminar flame speed measurements

Science.gov (United States)

Park, Okjoo; Veloo, Peter S.; Sheen, David A.; Tao, Yujie; Egolfopoulos, Fokion N.; Wang, Hai

2016-01-01

Laminar flame speed measurements were carried for mixture of air with eight C3-4 hydrocarbons (propene, propane, 1,3-butadiene, 1-butene, 2-butene, iso-butene, n-butane, and iso-butane) at the room temperature and ambient pressure. Along with C1-2 hydrocarbon data reported in a recent study, the entire dataset was used to demonstrate how laminar flame speed data can be utilized to explore and minimize the uncertainties in a reaction model for foundation fuels. The USC Mech II kinetic model was chosen as a case study. The method of uncertainty minimization using polynomial chaos expansions (MUM-PCE) (D.A. Sheen and H. Wang, Combust. Flame 2011, 158, 2358–2374) was employed to constrain the model uncertainty for laminar flame speed predictions. Results demonstrate that a reaction model constrained only by the laminar flame speed values of methane/air flames notably reduces the uncertainty in the predictions of the laminar flame speeds of C3 and C4 alkanes, because the key chemical pathways of all of these flames are similar to each other. The uncertainty in model predictions for flames of unsaturated C3-4 hydrocarbons remain significant without considering fuel specific laminar flames speeds in the constraining target data set, because the secondary rate controlling reaction steps are different from those in the saturated alkanes. It is shown that the constraints provided by the laminar flame speeds of the foundation fuels could reduce notably the uncertainties in the predictions of laminar flame speeds of C4 alcohol/air mixtures. Furthermore, it is demonstrated that an accurate prediction of the laminar flame speed of a particular C4 alcohol/air mixture is better achieved through measurements for key molecular intermediates formed during the pyrolysis and oxidation of the parent fuel. PMID:27890938

Efficient Characterization of Parametric Uncertainty of Complex (Biochemical Networks.

Directory of Open Access Journals (Sweden)

Claudia Schillings

2015-08-01

Full Text Available Parametric uncertainty is a particularly challenging and relevant aspect of systems analysis in domains such as systems biology where, both for inference and for assessing prediction uncertainties, it is essential to characterize the system behavior globally in the parameter space. However, current methods based on local approximations or on Monte-Carlo sampling cope only insufficiently with high-dimensional parameter spaces associated with complex network models. Here, we propose an alternative deterministic methodology that relies on sparse polynomial approximations. We propose a deterministic computational interpolation scheme which identifies most significant expansion coefficients adaptively. We present its performance in kinetic model equations from computational systems biology with several hundred parameters and state variables, leading to numerical approximations of the parametric solution on the entire parameter space. The scheme is based on adaptive Smolyak interpolation of the parametric solution at judiciously and adaptively chosen points in parameter space. As Monte-Carlo sampling, it is "non-intrusive" and well-suited for massively parallel implementation, but affords higher convergence rates. This opens up new avenues for large-scale dynamic network analysis by enabling scaling for many applications, including parameter estimation, uncertainty quantification, and systems design.

The Uncertainty Multiplier and Business Cycles

OpenAIRE

Saijo, Hikaru

2013-01-01

I study a business cycle model where agents learn about the state of the economy by accumulating capital. During recessions, agents invest less, and this generates noisier estimates of macroeconomic conditions and an increase in uncertainty. The endogenous increase in aggregate uncertainty further reduces economic activity, which in turn leads to more uncertainty, and so on. Thus, through changes in uncertainty, learning gives rise to a multiplier effect that amplifies business cycles. I use ...

Inventories and sales uncertainty\\ud

OpenAIRE

Caglayan, M.; Maioli, S.; Mateut, S.

2011-01-01

We investigate the empirical linkages between sales uncertainty and firms´ inventory investment behavior while controlling for firms´ financial strength. Using large panels of manufacturing firms from several European countries we find that higher sales uncertainty leads to larger stocks of inventories. We also identify an indirect effect of sales uncertainty on inventory accumulation through the financial strength of firms. Our results provide evidence that financial strength mitigates the a...

Adoption of residential solar power under uncertainty: Implications for renewable energy incentives

International Nuclear Information System (INIS)

Bauner, Christoph; Crago, Christine L.

2015-01-01

Many incentives at the state and federal level exist for household adoption of renewable energy like solar photovoltaic (PV) panels. Despite generous financial incentives the adoption rate is low. We use the option value framework, which takes into account the benefit of delaying investment in response to uncertainty, to examine the decision by households to invest in solar PV. Using a simulation model, we determine optimal adoption times, critical values of discounted benefits, and adoption rates over time for solar PV investments using data from Massachusetts. We find that the option value multiplier is 1.6, which implies that the discounted value of benefits from solar PV needs to exceed installation cost by 60% for investment to occur. Without any policies, median adoption time is eight years longer under the option value decision rule compared to the net present value decision rule where households equate discounted benefits to installation cost. Rebates and other financial incentives decrease adoption time, but their effect is attenuated if households apply the option value decision rule to solar PV investments. Results suggest that policies that reduce the uncertainty in returns from solar PV investments would be most effective at incentivizing adoption. - Highlights: • We examine household adoption of solar PV using the option value framework. • Uncertainty in benefits and costs leads to delay in investment timing. • Discounted benefits from solar PV have to exceed investment cost by 60% to trigger investment. • Policy incentives that reduce uncertainty in returns from solar PV are most effective.

Uncertainty quantification for PZT bimorph actuators

Science.gov (United States)

Bravo, Nikolas; Smith, Ralph C.; Crews, John

2018-03-01

In this paper, we discuss the development of a high fidelity model for a PZT bimorph actuator used for micro-air vehicles, which includes the Robobee. We developed a high-fidelity model for the actuator using the homogenized energy model (HEM) framework, which quantifies the nonlinear, hysteretic, and rate-dependent behavior inherent to PZT in dynamic operating regimes. We then discussed an inverse problem on the model. We included local and global sensitivity analysis of the parameters in the high-fidelity model. Finally, we will discuss the results of Bayesian inference and uncertainty quantification on the HEM.

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

Science.gov (United States)

Farrance, Ian; Frenkel, Robert

2014-01-01

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

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

Science.gov (United States)

Farrance, Ian; Frenkel, Robert

2014-02-01

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

Petroleum taxation under uncertainty - contingent claims

International Nuclear Information System (INIS)

Lund, D.

1990-01-01

A workable method for the analysis of incentive effects of petroleum taxes under uncertainty is presented. The main advantage of the method is that it concludes with a single number for the after-tax value of any development plan, and thus allows for a quantification of incentive effects for any given description of production possibilities. It is, however, not possible to describe tax effects under uncertainty by simple magnitudes independent of production possibilities, such as wedges in rates of return. The theoretical basis is the contingent claims analysis from finance theory, which is applicable in particular to companies that are owned by well-diversified shareholders. It is not obvious that the tax authorities of poorly diversified countries should value uncertain income streams by the same method. The Norwegian petroleum taxation is shown to have strongly distortionary effects compared to a no-tax situation or a cash flow tax. These distortions were reduced by the tax changes that followed the 1986 decreases in crude oil prices. A weakness of the model of the Norwegian system is that an exactly optimal financial policy for the company has not been found. 30 refs., 2 figs., 3 tabs

Relational uncertainty in service dyads

DEFF Research Database (Denmark)

Kreye, Melanie

2017-01-01

in service dyads and how they resolve it through suitable organisational responses to increase the level of service quality. Design/methodology/approach: We apply the overall logic of Organisational Information-Processing Theory (OIPT) and present empirical insights from two industrial case studies collected...... the relational uncertainty increased the functional quality while resolving the partner’s organisational uncertainty increased the technical quality of the delivered service. Originality: We make two contributions. First, we introduce relational uncertainty to the OM literature as the inability to predict...... and explain the actions of a partnering organisation due to a lack of knowledge about their abilities and intentions. Second, we present suitable organisational responses to relational uncertainty and their effect on service quality....

Sensitivity and uncertainty studies of the CRAC2 computer code

International Nuclear Information System (INIS)

Kocher, D.C.; Ward, R.C.; Killough, G.G.; Dunning, D.E. Jr.; Hicks, B.B.; Hosker, R.P. Jr.; Ku, J.Y.; Rao, K.S.

1987-01-01

The authors have studied the sensitivity of health impacts from nuclear reactor accidents, as predicted by the CRAC2 computer code, to the following sources of uncertainty: (1) the model for plume rise, (2) the model for wet deposition, (3) the meteorological bin-sampling procedure for selecting weather sequences with rain, (4) the dose conversion factors for inhalation as affected by uncertainties in the particle size of the carrier aerosol and the clearance rates of radionuclides from the respiratory tract, (5) the weathering half-time for external ground-surface exposure, and (6) the transfer coefficients for terrestrial foodchain pathways. Predicted health impacts usually showed little sensitivity to use of an alternative plume-rise model or a modified rain-bin structure in bin-sampling. Health impacts often were quite sensitive to use of an alternative wet-deposition model in single-trial runs with rain during plume passage, but were less sensitive to the model in bin-sampling runs. Uncertainties in the inhalation dose conversion factors had important effects on early injuries in single-trial runs. Latent cancer fatalities were moderately sensitive to uncertainties in the weathering half-time for ground-surface exposures, but showed little sensitivity to the transfer coefficients for terrestrial foodchain pathways. Sensitivities of CRAC2 predictions to uncertainties in the models and parameters also depended on the magnitude of the source term, and some of the effects on early health effects were comparable to those that were due only to selection of different sets of weather sequences in bin-sampling

Evaluating the effectiveness of mixed-integer linear programming for day-ahead hydro-thermal self-scheduling considering price uncertainty and forced outage rate

International Nuclear Information System (INIS)

Esmaeily, Ali; Ahmadi, Abdollah; Raeisi, Fatima; Ahmadi, Mohammad Reza; Esmaeel Nezhad, Ali; Janghorbani, Mohammadreza

2017-01-01

A new optimization framework based on MILP model is introduced in the paper for the problem of stochastic self-scheduling of hydrothermal units known as HTSS Problem implemented in a joint energy and reserve electricity market with day-ahead mechanism. The proposed MILP framework includes some practical constraints such as the cost due to valve-loading effect, the limit due to DRR and also multi-POZs, which have been less investigated in electricity market models. For the sake of more accuracy, for hydro generating units’ model, multi performance curves are also used. The problem proposed in this paper is formulated using a model on the basis of a stochastic optimization technique while the objective function is maximizing the expected profit utilizing MILP technique. The suggested stochastic self-scheduling model employs the price forecast error in order to take into account the uncertainty due to price. Besides, LMCS is combined with roulette wheel mechanism so that the scenarios corresponding to the non-spinning reserve price and spinning reserve price as well as the energy price at each hour of the scheduling are generated. Finally, the IEEE 118-bus power system is used to indicate the performance and the efficiency of the suggested technique. - Highlights: • Characterizing the uncertainties of price and FOR of units. • Replacing the fixed ramping rate constraints with the dynamic ones. • Proposing linearized model for the valve-point effects of thermal units. • Taking into consideration the multi-POZs relating to the thermal units. • Taking into consideration the multi-performance curves of hydroelectric units.

ON THE ESTIMATION OF RANDOM UNCERTAINTIES OF STAR FORMATION HISTORIES

Energy Technology Data Exchange (ETDEWEB)

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

2013-09-20

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

ON THE ESTIMATION OF RANDOM UNCERTAINTIES OF STAR FORMATION HISTORIES

International Nuclear Information System (INIS)

Dolphin, Andrew E.

2013-01-01

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

Uncertainties and severe-accident management

International Nuclear Information System (INIS)

Kastenberg, W.E.

1991-01-01

Severe-accident management can be defined as the use of existing and or alternative resources, systems, and actions to prevent or mitigate a core-melt accident. Together with risk management (e.g., changes in plant operation and/or addition of equipment) and emergency planning (off-site actions), accident management provides an extension of the defense-indepth safety philosophy for severe accidents. A significant number of probabilistic safety assessments have been completed, which yield the principal plant vulnerabilities, and can be categorized as (a) dominant sequences with respect to core-melt frequency, (b) dominant sequences with respect to various risk measures, (c) dominant threats that challenge safety functions, and (d) dominant threats with respect to failure of safety systems. Severe-accident management strategies can be generically classified as (a) use of alternative resources, (b) use of alternative equipment, and (c) use of alternative actions. For each sequence/threat and each combination of strategy, there may be several options available to the operator. Each strategy/option involves phenomenological and operational considerations regarding uncertainty. These include (a) uncertainty in key phenomena, (b) uncertainty in operator behavior, (c) uncertainty in system availability and behavior, and (d) uncertainty in information availability (i.e., instrumentation). This paper focuses on phenomenological uncertainties associated with severe-accident management strategies

Pharmacological Fingerprints of Contextual Uncertainty.

Directory of Open Access Journals (Sweden)

Louise Marshall

2016-11-01

Full Text Available Successful interaction with the environment requires flexible updating of our beliefs about the world. By estimating the likelihood of future events, it is possible to prepare appropriate actions in advance and execute fast, accurate motor responses. According to theoretical proposals, agents track the variability arising from changing environments by computing various forms of uncertainty. Several neuromodulators have been linked to uncertainty signalling, but comprehensive empirical characterisation of their relative contributions to perceptual belief updating, and to the selection of motor responses, is lacking. Here we assess the roles of noradrenaline, acetylcholine, and dopamine within a single, unified computational framework of uncertainty. Using pharmacological interventions in a sample of 128 healthy human volunteers and a hierarchical Bayesian learning model, we characterise the influences of noradrenergic, cholinergic, and dopaminergic receptor antagonism on individual computations of uncertainty during a probabilistic serial reaction time task. We propose that noradrenaline influences learning of uncertain events arising from unexpected changes in the environment. In contrast, acetylcholine balances attribution of uncertainty to chance fluctuations within an environmental context, defined by a stable set of probabilistic associations, or to gross environmental violations following a contextual switch. Dopamine supports the use of uncertainty representations to engender fast, adaptive responses.

Trapped between two tails: trading off scientific uncertainties via climate targets

International Nuclear Information System (INIS)

Lemoine, Derek; McJeon, Haewon C

2013-01-01

Climate change policies must trade off uncertainties about future warming, about the social and ecological impacts of warming, and about the cost of reducing greenhouse gas emissions. We show that laxer carbon targets produce broader distributions for climate damages, skewed towards severe outcomes. However, if potential low-carbon technologies fill overlapping niches, then more stringent carbon targets produce broader distributions for the cost of reducing emissions, skewed towards high-cost outcomes. We use the technology-rich GCAM integrated assessment model to assess the robustness of 450 and 500 ppm carbon targets to each uncertain factor. The 500 ppm target provides net benefits across a broad range of futures. The 450 ppm target provides net benefits only when impacts are greater than conventionally assumed, when multiple technological breakthroughs lower the cost of abatement, or when evaluated with a low discount rate. Policy evaluations are more sensitive to uncertainty about abatement technology and impacts than to uncertainty about warming. (letter)

Trapped between two tails: trading off scientific uncertainties via climate targets

Science.gov (United States)

Lemoine, Derek; McJeon, Haewon C.

2013-09-01

Climate change policies must trade off uncertainties about future warming, about the social and ecological impacts of warming, and about the cost of reducing greenhouse gas emissions. We show that laxer carbon targets produce broader distributions for climate damages, skewed towards severe outcomes. However, if potential low-carbon technologies fill overlapping niches, then more stringent carbon targets produce broader distributions for the cost of reducing emissions, skewed towards high-cost outcomes. We use the technology-rich GCAM integrated assessment model to assess the robustness of 450 and 500 ppm carbon targets to each uncertain factor. The 500 ppm target provides net benefits across a broad range of futures. The 450 ppm target provides net benefits only when impacts are greater than conventionally assumed, when multiple technological breakthroughs lower the cost of abatement, or when evaluated with a low discount rate. Policy evaluations are more sensitive to uncertainty about abatement technology and impacts than to uncertainty about warming.

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

Science.gov (United States)

Fergus, Thomas A; Rowatt, Wade C

2015-03-01

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

Stronger Schrödinger-like uncertainty relations

International Nuclear Information System (INIS)

Song, Qiu-Cheng; Qiao, Cong-Feng

2016-01-01

Highlights: • A stronger Schrödinger-like uncertainty relation in the sum of variances of two observables is obtained. • An improved Schrödinger-like uncertainty relation in the product of variances of two observables is obtained. • A stronger uncertainty relation in the sum of variances of three observables is proposed. - Abstract: Uncertainty relation is one of the fundamental building blocks of quantum theory. Nevertheless, the traditional uncertainty relations do not fully capture the concept of incompatible observables. Here we present a stronger Schrödinger-like uncertainty relation, which is stronger than the relation recently derived by Maccone and Pati (2014) [11]. Furthermore, we give an additive uncertainty relation which holds for three incompatible observables, which is stronger than the relation newly obtained by Kechrimparis and Weigert (2014) [12] and the simple extension of the Schrödinger uncertainty relation.

Uncertainty in prediction and in inference

NARCIS (Netherlands)

Hilgevoord, J.; Uffink, J.

1991-01-01

The concepts of uncertainty in prediction and inference are introduced and illustrated using the diffraction of light as an example. The close re-lationship between the concepts of uncertainty in inference and resolving power is noted. A general quantitative measure of uncertainty in

Rational consensus under uncertainty: Expert judgment in the EC-USNRC uncertainty study

International Nuclear Information System (INIS)

Cooke, R.; Kraan, B.; Goossens, L.

1999-01-01

Governmental bodies are confronted with the problem of achieving rational consensus in the face of substantial uncertainties. The area of accident consequence management for nuclear power plants affords a good example. Decisions with regard to evacuation, decontamination, and food bans must be taken on the basis of predictions of environmental transport of radioactive material, contamination through the food chain, cancer induction, and the like. These predictions use mathematical models containing scores of uncertain parameters. Decision makers want to take, and want to be perceived to take, these decisions in a rational manner. The question is, how can this be accomplished in the face of large uncertainties? Indeed, the very presence of uncertainty poses a threat to rational consensus. Decision makers will necessarily base their actions on the judgments of experts. The experts, however, will not agree among themselves, as otherwise we would not speak of large uncertainties. Any given expert's viewpoint will be favorable to the interests of some stakeholders, and hostile to the interests of others. If a decision maker bases his/her actions on the views of one single expert, then (s)he is invariably open to charges of partiality toward the interests favored by this viewpoint. An appeal to 'impartial' or 'disinterested' experts will fail for two reasons. First, experts have interests; they have jobs, mortgages and professional reputations. Second, even if expert interests could somehow be quarantined, even then the experts would disagree. Expert disagreement is not explained by diverging interests, and consensus cannot be reached by shielding the decision process from expert interests. If rational consensus requires expert agreement, then rational consensus is simply not possible in the face of uncertainty. If rational consensus under uncertainty is to be achieved, then evidently the views of a diverse set of experts must be taken into account. The question is how

Hour of the brave. While the prices of turnkey solar power plants are getting lower, there is still uncertainty about reimbursement rates; Die Stunde der Mutigen. Die Preise fuer schluesselfertige Solarstromanlagen sinken, die Verguetungshoehe bleibt ungewiss

Energy Technology Data Exchange (ETDEWEB)

Krause, Matthias B.

2012-07-15

More than two months of uncertainty about reimbursement rates for solar power have left their mark in Germany. Customers are confused, demand is waning, and prices have decreased again as a new market survey shows. Manufacturers and fitters try to react by various different strategies.

Reduction and Uncertainty Analysis of Chemical Mechanisms Based on Local and Global Sensitivities

Science.gov (United States)

Esposito, Gaetano

Numerical simulations of critical reacting flow phenomena in hypersonic propulsion devices require accurate representation of finite-rate chemical kinetics. The chemical kinetic models available for hydrocarbon fuel combustion are rather large, involving hundreds of species and thousands of reactions. As a consequence, they cannot be used in multi-dimensional computational fluid dynamic calculations in the foreseeable future due to the prohibitive computational cost. In addition to the computational difficulties, it is also known that some fundamental chemical kinetic parameters of detailed models have significant level of uncertainty due to limited experimental data available and to poor understanding of interactions among kinetic parameters. In the present investigation, local and global sensitivity analysis techniques are employed to develop a systematic approach of reducing and analyzing detailed chemical kinetic models. Unlike previous studies in which skeletal model reduction was based on the separate analysis of simple cases, in this work a novel strategy based on Principal Component Analysis of local sensitivity values is presented. This new approach is capable of simultaneously taking into account all the relevant canonical combustion configurations over different composition, temperature and pressure conditions. Moreover, the procedure developed in this work represents the first documented inclusion of non-premixed extinction phenomena, which is of great relevance in hypersonic combustors, in an automated reduction algorithm. The application of the skeletal reduction to a detailed kinetic model consisting of 111 species in 784 reactions is demonstrated. The resulting reduced skeletal model of 37--38 species showed that the global ignition/propagation/extinction phenomena of ethylene-air mixtures can be predicted within an accuracy of 2% of the full detailed model. The problems of both understanding non-linear interactions between kinetic parameters and

First Reprocessing of Southern Hemisphere ADditional OZonesondes Profile Records: 3. Uncertainty in Ozone Profile and Total Column

Science.gov (United States)

Witte, Jacquelyn C.; Thompson, Anne M.; Smit, Herman G. J.; Vömel, Holger; Posny, Françoise; Stübi, Rene

2018-03-01

Reprocessed ozonesonde data from eight SHADOZ (Southern Hemisphere ADditional OZonesondes) sites have been used to derive the first analysis of uncertainty estimates for both profile and total column ozone (TCO). The ozone uncertainty is a composite of the uncertainties of the individual terms in the ozone partial pressure (PO3) equation, those being the ozone sensor current, background current, internal pump temperature, pump efficiency factors, conversion efficiency, and flow rate. Overall, PO3 uncertainties (ΔPO3) are within 15% and peak around the tropopause (15 ± 3 km) where ozone is a minimum and ΔPO3 approaches the measured signal. The uncertainty in the background and sensor currents dominates the overall ΔPO3 in the troposphere including the tropopause region, while the uncertainties in the conversion efficiency and flow rate dominate in the stratosphere. Seasonally, ΔPO3 is generally a maximum in the March-May, with the exception of SHADOZ sites in Asia, for which the highest ΔPO3 occurs in September-February. As a first approach, we calculate sonde TCO uncertainty (ΔTCO) by integrating the profile ΔPO3 and adding the ozone residual uncertainty, derived from the McPeters and Labow (2012, doi:10.1029/2011JD017006) 1σ ozone mixing ratios. Overall, ΔTCO are within ±15 Dobson units (DU), representing 5-6% of the TCO. Total Ozone Mapping Spectrometer and Ozone Monitoring Instrument (TOMS and OMI) satellite overpasses are generally within the sonde ΔTCO. However, there is a discontinuity between TOMS v8.6 (1998 to September 2004) and OMI (October 2004-2016) TCO on the order of 10 DU that accounts for the significant 16 DU overall difference observed between sonde and TOMS. By comparison, the sonde-OMI absolute difference for the eight stations is only 4 DU.

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).

Addressing uncertainties in the ERICA Integrated Approach

International Nuclear Information System (INIS)

Oughton, D.H.; Agueero, A.; Avila, R.; Brown, J.E.; Copplestone, D.; Gilek, M.

2008-01-01

Like any complex environmental problem, ecological risk assessment of the impacts of ionising radiation is confounded by uncertainty. At all stages, from problem formulation through to risk characterisation, the assessment is dependent on models, scenarios, assumptions and extrapolations. These include technical uncertainties related to the data used, conceptual uncertainties associated with models and scenarios, as well as social uncertainties such as economic impacts, the interpretation of legislation, and the acceptability of the assessment results to stakeholders. The ERICA Integrated Approach has been developed to allow an assessment of the risks of ionising radiation, and includes a number of methods that are intended to make the uncertainties and assumptions inherent in the assessment more transparent to users and stakeholders. Throughout its development, ERICA has recommended that assessors deal openly with the deeper dimensions of uncertainty and acknowledge that uncertainty is intrinsic to complex systems. Since the tool is based on a tiered approach, the approaches to dealing with uncertainty vary between the tiers, ranging from a simple, but highly conservative screening to a full probabilistic risk assessment including sensitivity analysis. This paper gives on overview of types of uncertainty that are manifest in ecological risk assessment and the ERICA Integrated Approach to dealing with some of these uncertainties

Uncertainty analysis for geologic disposal of radioactive waste

International Nuclear Information System (INIS)

Cranwell, R.M.; Helton, J.C.

1981-01-01

The incorporation and representation of uncertainty in the analysis of the consequences and risks associated with the geologic disposal of high-level radioactive waste are discussed. Such uncertainty has three primary components: process modeling uncertainty, model input data uncertainty, and scenario uncertainty. The following topics are considered in connection with the preceding components: propagation of uncertainty in the modeling of a disposal site, sampling of input data for models, and uncertainty associated with model output

SENSIT: a cross-section and design sensitivity and uncertainty analysis code. [In FORTRAN for CDC-7600, IBM 360

Energy Technology Data Exchange (ETDEWEB)

Gerstl, S.A.W.

1980-01-01

SENSIT computes the sensitivity and uncertainty of a calculated integral response (such as a dose rate) due to input cross sections and their uncertainties. Sensitivity profiles are computed for neutron and gamma-ray reaction cross sections of standard multigroup cross section sets and for secondary energy distributions (SEDs) of multigroup scattering matrices. In the design sensitivity mode, SENSIT computes changes in an integral response due to design changes and gives the appropriate sensitivity coefficients. Cross section uncertainty analyses are performed for three types of input data uncertainties: cross-section covariance matrices for pairs of multigroup reaction cross sections, spectral shape uncertainty parameters for secondary energy distributions (integral SED uncertainties), and covariance matrices for energy-dependent response functions. For all three types of data uncertainties SENSIT computes the resulting variance and estimated standard deviation in an integral response of interest, on the basis of generalized perturbation theory. SENSIT attempts to be more comprehensive than earlier sensitivity analysis codes, such as SWANLAKE.

The Role of Type and Source of Uncertainty on the Processing of Climate Models Projections.

Science.gov (United States)

Benjamin, Daniel M; Budescu, David V

2018-01-01

Scientists agree that the climate is changing due to human activities, but there is less agreement about the specific consequences and their timeline. Disagreement among climate projections is attributable to the complexity of climate models that differ in their structure, parameters, initial conditions, etc. We examine how different sources of uncertainty affect people's interpretation of, and reaction to, information about climate change by presenting participants forecasts from multiple experts. Participants viewed three types of sets of sea-level rise projections: (1) precise, but conflicting ; (2) imprecise , but agreeing, and (3) hybrid that were both conflicting and imprecise. They estimated the most likely sea-level rise, provided a range of possible values and rated the sets on several features - ambiguity, credibility, completeness, etc. In Study 1, everyone saw the same hybrid set. We found that participants were sensitive to uncertainty between sources, but not to uncertainty about which model was used. The impacts of conflict and imprecision were combined for estimation tasks and compromised for feature ratings . Estimates were closer to the experts' original projections, and sets were rated more favorably under imprecision. Estimates were least consistent with (narrower than) the experts in the hybrid condition, but participants rated the conflicting set least favorably. In Study 2, we investigated the hybrid case in more detail by creating several distinct interval sets that combine conflict and imprecision. Two factors drive perceptual differences: overlap - the structure of the forecast set (whether intersecting, nested, tangent, or disjoint) - and a symmetry - the balance of the set. Estimates were primarily driven by asymmetry, and preferences were primarily driven by overlap. Asymmetric sets were least consistent with the experts: estimated ranges were narrower, and estimates of the most likely value were shifted further below the set mean

Uncertainty and validation. Effect of model complexity on uncertainty estimates

International Nuclear Information System (INIS)

Elert, M.

1996-09-01

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

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

Science.gov (United States)

Rivera, Diego; Rivas, Yessica; Godoy, Alex

2015-02-01

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

Approach to uncertainty in risk analysis

Energy Technology Data Exchange (ETDEWEB)

Rish, W.R.

1988-08-01

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

Approach to uncertainty in risk analysis

International Nuclear Information System (INIS)

Rish, W.R.

1988-08-01

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

A review of uncertainty research in impact assessment

International Nuclear Information System (INIS)

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

2015-01-01

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

A review of uncertainty research in impact assessment

Energy Technology Data Exchange (ETDEWEB)

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

2015-01-15

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

Some illustrative examples of model uncertainty

International Nuclear Information System (INIS)

Bier, V.M.

1994-01-01

In this paper, we first discuss the view of model uncertainty proposed by Apostolakis. We then present several illustrative examples related to model uncertainty, some of which are not well handled by this formalism. Thus, Apostolakis' approach seems to be well suited to describing some types of model uncertainty, but not all. Since a comprehensive approach for characterizing and quantifying model uncertainty is not yet available, it is hoped that the examples presented here will service as a springboard for further discussion

The accountability imperative for quantifying the uncertainty of emission forecasts: evidence from Mexico

DEFF Research Database (Denmark)

Puig, Daniel; Morales-Nápoles, Oswaldo; Bakhtiari, Fatemeh

2017-01-01

forecasting approaches can reflect prevailing uncertainties. We apply a transparent and replicable method to quantify the uncertainty associated with projections of gross domestic product growth rates for Mexico, a key driver of GHG emissions in the country. We use those projections to produce probabilistic...... forecasts of GHG emissions for Mexico. We contrast our probabilistic forecasts with Mexico’s governmental deterministic forecasts. We show that, because they fail to reflect such key uncertainty, deterministic forecasts are ill-suited for use in target-setting processes. We argue that (i) guidelines should...... be agreed upon, to ensure that governmental forecasts meet certain minimum transparency and quality standards, and (ii) governments should be held accountable for the appropriateness of the forecasting approach applied to prepare governmental forecasts, especially when those forecasts are used to derive...

Critical loads - assessment of uncertainty

Energy Technology Data Exchange (ETDEWEB)

Barkman, A.

1998-10-01

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

Evacuation decision-making: process and uncertainty

Energy Technology Data Exchange (ETDEWEB)

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

1985-09-01

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

Uncertainty modeling process for semantic technology

Directory of Open Access Journals (Sweden)

Rommel N. Carvalho

2016-08-01

Full Text Available The ubiquity of uncertainty across application domains generates a need for principled support for uncertainty management in semantically aware systems. A probabilistic ontology provides constructs for representing uncertainty in domain ontologies. While the literature has been growing on formalisms for representing uncertainty in ontologies, there remains little guidance in the knowledge engineering literature for how to design probabilistic ontologies. To address the gap, this paper presents the Uncertainty Modeling Process for Semantic Technology (UMP-ST, a new methodology for modeling probabilistic ontologies. To explain how the methodology works and to verify that it can be applied to different scenarios, this paper describes step-by-step the construction of a proof-of-concept probabilistic ontology. The resulting domain model can be used to support identification of fraud in public procurements in Brazil. While the case study illustrates the development of a probabilistic ontology in the PR-OWL probabilistic ontology language, the methodology is applicable to any ontology formalism that properly integrates uncertainty with domain semantics.

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

Evacuation decision-making: process and uncertainty

International Nuclear Information System (INIS)

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

1985-09-01

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

Participation under Uncertainty

International Nuclear Information System (INIS)

Boudourides, Moses A.

2003-01-01

This essay reviews a number of theoretical perspectives about uncertainty and participation in the present-day knowledge-based society. After discussing the on-going reconfigurations of science, technology and society, we examine how appropriate for policy studies are various theories of social complexity. Post-normal science is such an example of a complexity-motivated approach, which justifies civic participation as a policy response to an increasing uncertainty. But there are different categories and models of uncertainties implying a variety of configurations of policy processes. A particular role in all of them is played by expertise whose democratization is an often-claimed imperative nowadays. Moreover, we discuss how different participatory arrangements are shaped into instruments of policy-making and framing regulatory processes. As participation necessitates and triggers deliberation, we proceed to examine the role and the barriers of deliberativeness. Finally, we conclude by referring to some critical views about the ultimate assumptions of recent European policy frameworks and the conceptions of civic participation and politicization that they invoke

Uncertainty and Climate Change

OpenAIRE

Berliner, L. Mark

2003-01-01

Anthropogenic, or human-induced, climate change is a critical issue in science and in the affairs of humankind. Though the target of substantial research, the conclusions of climate change studies remain subject to numerous uncertainties. This article presents a very brief review of the basic arguments regarding anthropogenic climate change with particular emphasis on uncertainty.

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)

Probabilistic accident consequence uncertainty analysis: Food chain uncertainty assessment. Volume 1: Main report

Energy Technology Data Exchange (ETDEWEB)

Brown, J. [National Radiological Protection Board (United Kingdom); Goossens, L.H.J.; Kraan, B.C.P. [Delft Univ. of Technology (Netherlands)] [and others

1997-06-01

This volume is the first of a two-volume document that summarizes a joint project conducted by the US Nuclear Regulatory Commission and the European Commission to assess uncertainties in the MACCS and COSYMA probabilistic accident consequence codes. These codes were developed primarily for estimating the risks presented by nuclear reactors based on postulated frequencies and magnitudes of potential accidents. This document reports on an ongoing project to assess uncertainty in the MACCS and COSYMA calculations for the offsite consequences of radionuclide releases by hypothetical nuclear power plant accidents. A panel of sixteen experts was formed to compile credible and traceable uncertainty distributions for food chain variables that affect calculations of offsite consequences. The expert judgment elicitation procedure and its outcomes are described in these volumes. Other panels were formed to consider uncertainty in other aspects of the codes. Their results are described in companion reports. Volume 1 contains background information and a complete description of the joint consequence uncertainty study. Volume 2 contains appendices that include (1) a summary of the MACCS and COSYMA consequence codes, (2) the elicitation questionnaires and case structures for both panels, (3) the rationales and results for the panels on soil and plant transfer and animal transfer, (4) short biographies of the experts, and (5) the aggregated results of their responses.

Probabilistic accident consequence uncertainty analysis: Food chain uncertainty assessment. Volume 1: Main report

International Nuclear Information System (INIS)

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

1997-06-01

This volume is the first of a two-volume document that summarizes a joint project conducted by the US Nuclear Regulatory Commission and the European Commission to assess uncertainties in the MACCS and COSYMA probabilistic accident consequence codes. These codes were developed primarily for estimating the risks presented by nuclear reactors based on postulated frequencies and magnitudes of potential accidents. This document reports on an ongoing project to assess uncertainty in the MACCS and COSYMA calculations for the offsite consequences of radionuclide releases by hypothetical nuclear power plant accidents. A panel of sixteen experts was formed to compile credible and traceable uncertainty distributions for food chain variables that affect calculations of offsite consequences. The expert judgment elicitation procedure and its outcomes are described in these volumes. Other panels were formed to consider uncertainty in other aspects of the codes. Their results are described in companion reports. Volume 1 contains background information and a complete description of the joint consequence uncertainty study. Volume 2 contains appendices that include (1) a summary of the MACCS and COSYMA consequence codes, (2) the elicitation questionnaires and case structures for both panels, (3) the rationales and results for the panels on soil and plant transfer and animal transfer, (4) short biographies of the experts, and (5) the aggregated results of their responses

The management of subsurface uncertainty using probabilistic modeling of life cycle production forecasts and cash flows

International Nuclear Information System (INIS)

Olatunbosun, O. O.

1998-01-01

The subject pertains to the implementation of the full range of subsurface uncertainties in life cycle probabilistic forecasting and its extension to project cash flows using the methodology of probabilities. A new tool has been developed in the probabilistic application of Crystal-Ball which can model reservoir volumetrics, life cycle production forecasts and project cash flows in a single environment. The tool is modular such that the volumetrics and cash flow modules are optional. Production forecasts are often generated by applying a decline equation to single best estimate values of input parameters such as initial potential, decline rate, abandonment rate etc -or sometimes by results of reservoir simulation. This new tool provides a means of implementing the full range of uncertainties and interdependencies of the input parameters into the production forecasts by defining the input parameters as probability density functions, PDFs and performing several iterations to generate an expectation curve forecast. Abandonment rate is implemented in each iteration via a link to an OPEX model. The expectation curve forecast is input into a cash flow model to generate a probabilistic NPV. Base case and sensitivity runs from reservoir simulation can likewise form the basis for a probabilistic production forecast from which a probabilistic cash flow can be generated. A good illustration of the application of this tool is in the modelling of the production forecast for a well that encounters its target reservoirs in OUT/ODT situation and thus has significant uncertainties. The uncertainty in presence and size (if present) of gas cap and dependency between ultimate recovery and initial potential amongst other uncertainties can be easily implemented in the production forecast with this tool. From the expectation curve forecast, a probabilistic NPV can be easily generated. Possible applications of this tool include: i. estimation of range of actual recoverable volumes based

Nuclear Data Uncertainty Propagation in Depletion Calculations Using Cross Section Uncertainties in One-group or Multi-group

Energy Technology Data Exchange (ETDEWEB)

Díez, C.J., E-mail: cj.diez@upm.es [Dpto. de Ingeníera Nuclear, Universidad Politécnica de Madrid, 28006 Madrid (Spain); Cabellos, O. [Dpto. de Ingeníera Nuclear, Universidad Politécnica de Madrid, 28006 Madrid (Spain); Instituto de Fusión Nuclear, Universidad Politécnica de Madrid, 28006 Madrid (Spain); Martínez, J.S. [Dpto. de Ingeníera Nuclear, Universidad Politécnica de Madrid, 28006 Madrid (Spain)

2015-01-15

Several approaches have been developed in last decades to tackle nuclear data uncertainty propagation problems of burn-up calculations. One approach proposed was the Hybrid Method, where uncertainties in nuclear data are propagated only on the depletion part of a burn-up problem. Because only depletion is addressed, only one-group cross sections are necessary, and hence, their collapsed one-group uncertainties. This approach has been applied successfully in several advanced reactor systems like EFIT (ADS-like reactor) or ESFR (Sodium fast reactor) to assess uncertainties on the isotopic composition. However, a comparison with using multi-group energy structures was not carried out, and has to be performed in order to analyse the limitations of using one-group uncertainties.

Nuclear Data Uncertainty Propagation in Depletion Calculations Using Cross Section Uncertainties in One-group or Multi-group

International Nuclear Information System (INIS)

Díez, C.J.; Cabellos, O.; Martínez, J.S.

2015-01-01

Several approaches have been developed in last decades to tackle nuclear data uncertainty propagation problems of burn-up calculations. One approach proposed was the Hybrid Method, where uncertainties in nuclear data are propagated only on the depletion part of a burn-up problem. Because only depletion is addressed, only one-group cross sections are necessary, and hence, their collapsed one-group uncertainties. This approach has been applied successfully in several advanced reactor systems like EFIT (ADS-like reactor) or ESFR (Sodium fast reactor) to assess uncertainties on the isotopic composition. However, a comparison with using multi-group energy structures was not carried out, and has to be performed in order to analyse the limitations of using one-group uncertainties

Nuclear Data Uncertainty Propagation in Depletion Calculations Using Cross Section Uncertainties in One-group or Multi-group

Science.gov (United States)

Díez, C. J.; Cabellos, O.; Martínez, J. S.

2015-01-01

Several approaches have been developed in last decades to tackle nuclear data uncertainty propagation problems of burn-up calculations. One approach proposed was the Hybrid Method, where uncertainties in nuclear data are propagated only on the depletion part of a burn-up problem. Because only depletion is addressed, only one-group cross sections are necessary, and hence, their collapsed one-group uncertainties. This approach has been applied successfully in several advanced reactor systems like EFIT (ADS-like reactor) or ESFR (Sodium fast reactor) to assess uncertainties on the isotopic composition. However, a comparison with using multi-group energy structures was not carried out, and has to be performed in order to analyse the limitations of using one-group uncertainties.

Improvement of uncertainty relations for mixed states

International Nuclear Information System (INIS)

Park, Yong Moon

2005-01-01

We study a possible improvement of uncertainty relations. The Heisenberg uncertainty relation employs commutator of a pair of conjugate observables to set the limit of quantum measurement of the observables. The Schroedinger uncertainty relation improves the Heisenberg uncertainty relation by adding the correlation in terms of anti-commutator. However both relations are insensitive whether the state used is pure or mixed. We improve the uncertainty relations by introducing additional terms which measure the mixtureness of the state. For the momentum and position operators as conjugate observables and for the thermal state of quantum harmonic oscillator, it turns out that the equalities in the improved uncertainty relations hold

Uncertainty in spatial planning proceedings

Directory of Open Access Journals (Sweden)

Aleš Mlakar

2009-01-01

Full Text Available Uncertainty is distinctive of spatial planning as it arises from the necessity to co-ordinate the various interests within the area, from the urgency of adopting spatial planning decisions, the complexity of the environment, physical space and society, addressing the uncertainty of the future and from the uncertainty of actually making the right decision. Response to uncertainty is a series of measures that mitigate the effects of uncertainty itself. These measures are based on two fundamental principles – standardization and optimization. The measures are related to knowledge enhancement and spatial planning comprehension, in the legal regulation of changes, in the existence of spatial planning as a means of different interests co-ordination, in the active planning and the constructive resolution of current spatial problems, in the integration of spatial planning and the environmental protection process, in the implementation of the analysis as the foundation of spatial planners activities, in the methods of thinking outside the parameters, in forming clear spatial concepts and in creating a transparent management spatial system and also in the enforcement the participatory processes.

Management of internal communication in times of uncertainty

International Nuclear Information System (INIS)

Fernandez de la Gala, F.

2014-01-01

Garona is having a strong media coverage since 2009. The continuity process is under great controversy that has generated increased uncertainty for workers and their families, affecting motivation. Although internal communication has sought to manage its effects on the structure of the company, the rate of spread of alien information has made this complex mission. The regulatory body has been interested in its potential impact on safety culture, making a significant difference compared to other industrial sectors. (Author)

Efficiency of analytical and sampling-based uncertainty propagation in intensity-modulated proton therapy

Science.gov (United States)

Wahl, N.; Hennig, P.; Wieser, H. P.; Bangert, M.

2017-07-01

The sensitivity of intensity-modulated proton therapy (IMPT) treatment plans to uncertainties can be quantified and mitigated with robust/min-max and stochastic/probabilistic treatment analysis and optimization techniques. Those methods usually rely on sparse random, importance, or worst-case sampling. Inevitably, this imposes a trade-off between computational speed and accuracy of the uncertainty propagation. Here, we investigate analytical probabilistic modeling (APM) as an alternative for uncertainty propagation and minimization in IMPT that does not rely on scenario sampling. APM propagates probability distributions over range and setup uncertainties via a Gaussian pencil-beam approximation into moments of the probability distributions over the resulting dose in closed form. It supports arbitrary correlation models and allows for efficient incorporation of fractionation effects regarding random and systematic errors. We evaluate the trade-off between run-time and accuracy of APM uncertainty computations on three patient datasets. Results are compared against reference computations facilitating importance and random sampling. Two approximation techniques to accelerate uncertainty propagation and minimization based on probabilistic treatment plan optimization are presented. Runtimes are measured on CPU and GPU platforms, dosimetric accuracy is quantified in comparison to a sampling-based benchmark (5000 random samples). APM accurately propagates range and setup uncertainties into dose uncertainties at competitive run-times (GPU ≤slant {5} min). The resulting standard deviation (expectation value) of dose show average global γ{3% / {3}~mm} pass rates between 94.2% and 99.9% (98.4% and 100.0%). All investigated importance sampling strategies provided less accuracy at higher run-times considering only a single fraction. Considering fractionation, APM uncertainty propagation and treatment plan optimization was proven to be possible at constant time complexity

Implications of Uncertainty in Fossil Fuel Emissions for Terrestrial Ecosystem Modeling

Science.gov (United States)

King, A. W.; Ricciuto, D. M.; Mao, J.; Andres, R. J.

2017-12-01

Given observations of the increase in atmospheric CO2, estimates of anthropogenic emissions and models of oceanic CO2 uptake, one can estimate net global CO2 exchange between the atmosphere and terrestrial ecosystems as the residual of the balanced global carbon budget. Estimates from the Global Carbon Project 2016 show that terrestrial ecosystems are a growing sink for atmospheric CO2 (averaging 2.12 Gt C y-1 for the period 1959-2015 with a growth rate of 0.03 Gt C y-1 per year) but with considerable year-to-year variability (standard deviation of 1.07 Gt C y-1). Within the uncertainty of the observations, emissions estimates and ocean modeling, this residual calculation is a robust estimate of a global terrestrial sink for CO2. A task of terrestrial ecosystem science is to explain the trend and variability in this estimate. However, "within the uncertainty" is an important caveat. The uncertainty (2σ; 95% confidence interval) in fossil fuel emissions is 8.4% (±0.8 Gt C in 2015). Combined with uncertainty in other carbon budget components, the 2σ uncertainty surrounding the global net terrestrial ecosystem CO2 exchange is ±1.6 Gt C y-1. Ignoring the uncertainty, the estimate of a general terrestrial sink includes 2 years (1987 and 1998) in which terrestrial ecosystems are a small source of CO2 to the atmosphere. However, with 2σ uncertainty, terrestrial ecosystems may have been a source in as many as 18 years. We examine how well global terrestrial biosphere models simulate the trend and interannual variability of the global-budget estimate of the terrestrial sink within the context of this uncertainty (e.g., which models fall outside the 2σ uncertainty and in what years). Models are generally capable of reproducing the trend in net terrestrial exchange, but are less able to capture interannual variability and often fall outside the 2σ uncertainty. The trend in the residual carbon budget estimate is primarily associated with the increase in atmospheric CO2

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

Effects of Uncertainties in Hydrological Modelling. A Case Study of a Mountainous Catchment in Southern Norway

Science.gov (United States)

Engeland, Kolbjorn; Steinsland, Ingelin

2016-04-01

The aim of this study is to investigate how the inclusion of uncertainties in inputs and observed streamflow influence the parameter estimation, streamflow predictions and model evaluation. In particular we wanted to answer the following research questions: • What is the effect of including a random error in the precipitation and temperature inputs? • What is the effect of decreased information about precipitation by excluding the nearest precipitation station? • What is the effect of the uncertainty in streamflow observations? • What is the effect of reduced information about the true streamflow by using a rating curve where the measurement of the highest and lowest streamflow is excluded when estimating the rating curve? To answer these questions, we designed a set of calibration experiments and evaluation strategies. We used the elevation distributed HBV model operating on daily time steps combined with a Bayesian formulation and the MCMC routine Dream for parameter inference. The uncertainties in inputs was represented by creating ensembles of precipitation and temperature. The precipitation ensemble were created using a meta-gaussian random field approach. The temperature ensembles were created using a 3D Bayesian kriging with random sampling of the temperature laps rate. The streamflow ensembles were generated by a Bayesian multi-segment rating curve model. Precipitation and temperatures were randomly sampled for every day, whereas the streamflow ensembles were generated from rating curve ensembles, and the same rating curve was always used for the whole time series in a calibration or evaluation run. We chose a catchment with a meteorological station measuring precipitation and temperature, and a rating curve of relatively high quality. This allowed us to investigate and further test the effect of having less information on precipitation and streamflow during model calibration, predictions and evaluation. The results showed that including uncertainty

Decommissioning funding: ethics, implementation, uncertainties

International Nuclear Information System (INIS)

2006-01-01

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

Uncertainty analysis of environmental models

International Nuclear Information System (INIS)

Monte, L.

1990-01-01

In the present paper an evaluation of the output uncertainty of an environmental model for assessing the transfer of 137 Cs and 131 I in the human food chain are carried out on the basis of a statistical analysis of data reported by the literature. The uncertainty analysis offers the oppotunity of obtaining some remarkable information about the uncertainty of models predicting the migration of non radioactive substances in the environment mainly in relation to the dry and wet deposition

Model Uncertainty for Bilinear Hysteretic Systems

DEFF Research Database (Denmark)

Sørensen, John Dalsgaard; Thoft-Christensen, Palle

1984-01-01

. The statistical uncertainty -due to lack of information can e.g. be taken into account by describing the variables by predictive density functions, Veneziano [2). In general, model uncertainty is the uncertainty connected with mathematical modelling of the physical reality. When structural reliability analysis...... is related to the concept of a failure surface (or limit state surface) in the n-dimensional basic variable space then model uncertainty is at least due to the neglected variables, the modelling of the failure surface and the computational technique used. A more precise definition is given in section 2...

The Uncertainties of Risk Management

DEFF Research Database (Denmark)

Vinnari, Eija; Skærbæk, Peter

2014-01-01

for expanding risk management. More generally, such uncertainties relate to the professional identities and responsibilities of operational managers as defined by the framing devices. Originality/value – The paper offers three contributions to the extant literature: first, it shows how risk management itself......Purpose – The purpose of this paper is to analyse the implementation of risk management as a tool for internal audit activities, focusing on unexpected effects or uncertainties generated during its application. Design/methodology/approach – Public and confidential documents as well as semi......-structured interviews are analysed through the lens of actor-network theory to identify the effects of risk management devices in a Finnish municipality. Findings – The authors found that risk management, rather than reducing uncertainty, itself created unexpected uncertainties that would otherwise not have emerged...

Accounting for uncertainty in marine reserve design.

Science.gov (United States)

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

2006-01-01

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

Uncertainty analysis of suppression pool heating during an ATWS in a BWR-5 plant

International Nuclear Information System (INIS)

Wulff, W.; Cheng, H.S.; Mallen, A.N.; Johnsen, G.W.; Lellouche, G.S.

1994-03-01

The uncertainty has been estimated of predicting the peak temperature in the suppression pool of a BWR power plant, which undergoes an NRC-postulated Anticipated Transient Without Scram (ATWS). The ATWS is initiated by recirculation-pump trips, and then leads to power and flow oscillations as they had occurred at the LaSalle-2 Power Station in March of 1988. After limit-cycle oscillations have been established, the turbines are tripped, but without MSIV closure, allowing steam discharge through the turbine bypass into the condenser. Postulated operator actions, namely to lower the reactor vessel pressure and the level elevation in the downcomer, are simulated by a robot model which accounts for operator uncertainty. All balance of plant and control systems modeling uncertainties were part of the statistical uncertainty analysis that was patterned after the Code Scaling, Applicability and Uncertainty (CSAU) evaluation methodology. The analysis showed that the predicted suppression-pool peak temperature of 329.3 K (133 degrees F) has a 95-percentile uncertainty of 14.4 K (26 degrees F), and that the size of this uncertainty bracket is dominated by the experimental uncertainty of measuring Safety and Relief Valve mass flow rates under critical-flow conditions. The analysis showed also that the probability of exceeding the suppression-pool temperature limit of 352.6 K (175 degrees F) is most likely zero (it is estimated as < 5-104). The square root of the sum of the squares of all the computed peak pool temperatures is 350.7 K (171.6 degrees F)

Integrating uncertainties for climate change mitigation

Science.gov (United States)

Rogelj, Joeri; McCollum, David; Reisinger, Andy; Meinshausen, Malte; Riahi, Keywan

2013-04-01

The target of keeping global average temperature increase to below 2°C has emerged in the international climate debate more than a decade ago. In response, the scientific community has tried to estimate the costs of reaching such a target through modelling and scenario analysis. Producing such estimates remains a challenge, particularly because of relatively well-known, but ill-quantified uncertainties, and owing to limited integration of scientific knowledge across disciplines. The integrated assessment community, on one side, has extensively assessed the influence of technological and socio-economic uncertainties on low-carbon scenarios and associated costs. The climate modelling community, on the other side, has worked on achieving an increasingly better understanding of the geophysical response of the Earth system to emissions of greenhouse gases (GHG). This geophysical response remains a key uncertainty for the cost of mitigation scenarios but has only been integrated with assessments of other uncertainties in a rudimentary manner, i.e., for equilibrium conditions. To bridge this gap between the two research communities, we generate distributions of the costs associated with limiting transient global temperature increase to below specific temperature limits, taking into account uncertainties in multiple dimensions: geophysical, technological, social and political. In other words, uncertainties resulting from our incomplete knowledge about how the climate system precisely reacts to GHG emissions (geophysical uncertainties), about how society will develop (social uncertainties and choices), which technologies will be available (technological uncertainty and choices), when we choose to start acting globally on climate change (political choices), and how much money we are or are not willing to spend to achieve climate change mitigation. We find that political choices that delay mitigation have the largest effect on the cost-risk distribution, followed by

Leak Rate Quantification Method for Gas Pressure Seals with Controlled Pressure Differential

Science.gov (United States)

Daniels, Christopher C.; Braun, Minel J.; Oravec, Heather A.; Mather, Janice L.; Taylor, Shawn C.

2015-01-01

An enhancement to the pressure decay leak rate method with mass point analysis solved deficiencies in the standard method. By adding a control system, a constant gas pressure differential across the test article was maintained. As a result, the desired pressure condition was met at the onset of the test, and the mass leak rate and measurement uncertainty were computed in real-time. The data acquisition and control system were programmed to automatically stop when specified criteria were met. Typically, the test was stopped when a specified level of measurement uncertainty was attained. Using silicone O-ring test articles, the new method was compared with the standard method that permitted the downstream pressure to be non-constant atmospheric pressure. The two methods recorded comparable leak rates, but the new method recorded leak rates with significantly lower measurement uncertainty, statistical variance, and test duration. Utilizing this new method in leak rate quantification, projects will reduce cost and schedule, improve test results, and ease interpretation between data sets.

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

International Nuclear Information System (INIS)

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

2006-01-01

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

Fuzzy Uncertainty Evaluation for Fault Tree Analysis

Energy Technology Data Exchange (ETDEWEB)

Kim, Ki Beom; Shim, Hyung Jin [Seoul National University, Seoul (Korea, Republic of); Jae, Moo Sung [Hanyang University, Seoul (Korea, Republic of)

2015-05-15

This traditional probabilistic approach can calculate relatively accurate results. However it requires a long time because of repetitive computation due to the MC method. In addition, when informative data for statistical analysis are not sufficient or some events are mainly caused by human error, the probabilistic approach may not be possible because uncertainties of these events are difficult to be expressed by probabilistic distributions. In order to reduce the computation time and quantify uncertainties of top events when basic events whose uncertainties are difficult to be expressed by probabilistic distributions exist, the fuzzy uncertainty propagation based on fuzzy set theory can be applied. In this paper, we develop a fuzzy uncertainty propagation code and apply the fault tree of the core damage accident after the large loss of coolant accident (LLOCA). The fuzzy uncertainty propagation code is implemented and tested for the fault tree of the radiation release accident. We apply this code to the fault tree of the core damage accident after the LLOCA in three cases and compare the results with those computed by the probabilistic uncertainty propagation using the MC method. The results obtained by the fuzzy uncertainty propagation can be calculated in relatively short time, covering the results obtained by the probabilistic uncertainty propagation.

The EURACOS activation experiments: preliminary uncertainty analysis

International Nuclear Information System (INIS)

Yeivin, Y.

1982-01-01

A sequence of counting rates of an irradiated sulphur pellet, r(tsub(i)), measured at different times after the end of the irradiation, are fitted to r(t)=Aexp(-lambda t)+B. A standard adjustment procedure is applied to determine the parameters A and B, their standard deviations and correlation, and chi square. It is demonstrated that if the counting-rate uncertainties are entirely due to the counting statistics, the experimental data are totally inconsistent with the ''theoretical'' model. However, assuming an additional systematic error of approximalety 1%, and eliminating a few ''bad'' data, produces a data set quite consistent with the model. The dependence of chi square on the assumed systematic error and the data elimination procedure are discussed in great detail. A review of the adjustment procedure is appended to the report

Icarus's discovery: Acting on global climate change in the face of uncertainty

International Nuclear Information System (INIS)

Brooks, D.G.; Maracas, K.B.; Hayslip, R.M.

1994-01-01

The mythological character Icarus had the misfortune of learning the consequences of his decision to fly too near the sun at the same time he employed his decision. Although Daedalus tried to reduce the uncertainties of his son's decision by warning Icarus of the possible outcome, Icarus had no empirical knowledge of what would actually happen until his waxen wings melted and he fell to the sea. Like Icarus, man has no empirical knowledge or conclusive evidence today of the possible effects of global climate change. And though the consequences of policy decisions toward global climate change may not be as catastrophic as falling into the sea, the social and economic impacts of those decisions will be substantial. There are broad uncertainties related to the scientific and ecological aspects of global climate change. But clearly the ''politics'' of global climate change issues are moving at a faster rate than the science. There is a public outcry for action now, in the face of uncertainty. This paper profiles a case study of a southwestern utility's use of multi-attribute preference theory to reduce uncertainties and analyze its options for addressing global climate change issues

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

Energy Technology Data Exchange (ETDEWEB)

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

2006-02-15

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

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

International Nuclear Information System (INIS)

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

2006-01-01

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

Uncertainties in forecasting the response of polar bears to global climate change

Science.gov (United States)

Douglas, David C.; Atwood, Todd C.; Butterworth, Andy

2017-01-01

Several sources of uncertainty affect how precisely the future status of polar bears (Ursus maritimus) can be forecasted. Foremost are unknowns about the future levels of global greenhouse gas emissions, which could range from an unabated increase to an aggressively mitigated reduction. Uncertainties also arise because different climate models project different amounts and rates of future warming (and sea ice loss)—even for the same emission scenario. There are also uncertainties about how global warming could affect the Arctic Ocean’s food web, so even if climate models project the presence of sea ice in the future, the availability of polar bear prey is not guaranteed. Under a worst-case emission scenario in which rates of greenhouse gas emissions continue to rise unabated to century’s end, the uncertainties about polar bear status center on a potential for extinction. If the species were to persist, it would likely be restricted to a high-latitude refugium in northern Canada and Greenland—assuming a food web also existed with enough accessible prey to fuel weight gains for surviving onshore during the most extreme years of summer ice melt. On the other hand, if emissions were to be aggressively mitigated at the levels proposed in the Paris Climate Agreement, healthy polar bear populations would probably continue to occupy all but the most southern areas of their contemporary summer range. While polar bears have survived previous warming phases—which indicate some resiliency to the loss of sea ice habitat—what is certain is that the present pace of warming is unprecedented and will increasingly expose polar bears to historically novel stressors.

Hump-shape Uncertainty, Agency Costs and Aggregate Fluctuations

OpenAIRE

Lee, Gabriel; Kevin, Salyer; Strobel, Johannes

2016-01-01

Previously measured uncertainty shocks using the U.S. data show a hump-shape time path: Uncertainty rises for two years before its decline. Current literature on the effects uncertainty on macroeconomics, including housing, has not accounted for this observation. Consequently, the literature on uncertainty and macroeconomics is divided on the effcts and the propagation mechanism of uncertainty on aggregate uctuations. This paper shows that when uncertainty rises and falls over time, th...

Dealing with exploration uncertainties

International Nuclear Information System (INIS)

Capen, E.

1992-01-01

Exploration for oil and gas should fulfill the most adventurous in their quest for excitement and surprise. This paper tries to cover that tall order. The authors will touch on the magnitude of the uncertainty (which is far greater than in most other businesses), the effects of not knowing target sizes very well, how to build uncertainty into analyses naturally, how to tie reserves and chance estimates to economics, and how to look at the portfolio effect of an exploration program. With no apologies, the authors will be using a different language for some readers - the language of uncertainty, which means probability and statistics. These tools allow one to combine largely subjective exploration information with the more analytical data from the engineering and economic side

Dynamic Uncertainty for Compensated Second-Order Systems

Directory of Open Access Journals (Sweden)

Clemens Elster

2010-08-01

Full Text Available The compensation of LTI systems and the evaluation of the according uncertainty is of growing interest in metrology. Uncertainty evaluation in metrology ought to follow specific guidelines, and recently two corresponding uncertainty evaluation schemes have been proposed for FIR and IIR filtering. We employ these schemes to compare an FIR and an IIR approach for compensating a second-order LTI system which has relevance in metrology. Our results suggest that the FIR approach is superior in the sense that it yields significantly smaller uncertainties when real-time evaluation of uncertainties is desired.

Race to improve student understanding of uncertainty: Using LEGO race cars in the physics lab

Science.gov (United States)

Parappilly, Maria; Hassam, Christopher; Woodman, Richard J.

2018-01-01

Laboratories using LEGO race cars were developed for students in an introductory physics topic with a high early drop-out rate. In a 2014 pilot study, the labs were offered to improve students' confidence with experiments and laboratory skills, especially uncertainty propagation. This intervention was extended into the intro level physics topic the next year, for comparison and evaluation. Considering the pilot study, we subsequently adapted the delivery of the LEGO labs for a large Engineering Mechanics cohort. A qualitative survey of the students was taken to gain insight into their perception of the incorporation of LEGO race cars into physics labs. For Engineering, the findings show that LEGO physics was instrumental in teaching students the measurement and uncertainty, improving their lab reporting skills, and was a key factor in reducing the early attrition rate. This paper briefly recalls the results of the pilot study, and how variations in the delivery yielded better learning outcomes. A novel method is proposed for how LEGO race cars in a physics lab can help students increase their understanding of uncertainty and motivate them towards physics practicals.

Parameter and model uncertainty in a life-table model for fine particles (PM2.5): a statistical modeling study.