Febriani, Reby; Yulida, Roza; ', Kausar
2014-01-01
This research aimed to determine the perception, interest, and the relationship between perception and interest the pineapple farmers on pineapple agroindustry in Village of Kualu Nenas Subdistrict Tambang Kampar Regency. The method taked of data used is a survey method. The population in this study is the pineapple farmers who are members of farmer groups combined (GaPokTan). Intake of respondents in this study conducted with purposive sampling with consideration only the cultivation of pine...
Analisis Agroindustri Nenas Ud Berkat Bersama Di Desa Kualu Nenas Kecamatan Tambang Kabupaten Kampar
Mufti, Mufti; Nizar, Rini; Nurwati, Niken
2017-01-01
Pineapple (Ananas comosus L) is a fruit crop coming from Brazil. Besides pineapple can be eaten directly can be further processed into chips pineapple, pineapple dodol, jam, syrup and others. In the village there Nenas Kualu agro-industrial raw material, namely pineapple pineapple chips, diamonds pineapple and pineapple dodol. Pineapple chips are most widely refined products developed by craftsmen in the village Kualu pineapple processing pineapple. Processing of agricultural or agro-industry...
ANALISIS AGROINDUSTRI NENAS UD BERKAT BERSAMA DI DESA KUALU NENAS KECAMATAN TAMBANG KABUPATEN KAMPAR
Mufti Mufti; Rini Nizar; Niken Nurwati
2017-01-01
Pineapple (Ananas comosus L) is a fruit crop coming from Brazil. Besides pineapple can be eaten directly can be further processed into chips pineapple, pineapple dodol, jam, syrup and others. In the village there Nenas Kualu agro-industrial raw material, namely pineapple pineapple chips, diamonds pineapple and pineapple dodol. Pineapple chips are most widely refined products developed by craftsmen in the village Kualu pineapple processing pineapple. Processing of agricultural or agro-industry...
NSGIC Regional | GIS Inventory — Address Points dataset current as of 2006. Address points were attributed according to NENA standards and field verfied between the dates of June 2008 thru August...
El cas estrany d'una nena amb tuberculosi renal
Martínez Roig, Antonio
2009-01-01
La tuberculosi és una afecció més pròpia de localitzar-se als pulmons, a través del contagi per via aèria, que no pas fora d'ells. La que es produeix als ronyons seria només un 3% i la infecció estaria vinculada a la disseminació per via sanguínia i limfàtica de la tuberculosi pulmonar. Si considerem que la tuberculosi es diagnostica principalment a l'adolescència, trobarem força peculiar el cas d'una nena que va desenvolupar una tuberculosi renal amb tretze mesos de vida. La nena patia una d...
ANALISIS AGROINDUSTRI NENAS UD BERKAT BERSAMA DI DESA KUALU NENAS KECAMATAN TAMBANG KABUPATEN KAMPAR
Mufti Mufti
2017-04-01
Full Text Available Pineapple (Ananas comosus L is a fruit crop coming from Brazil. Besides pineapple can be eaten directly can be further processed into chips pineapple, pineapple dodol, jam, syrup and others. In the village there Nenas Kualu agro-industrial raw material, namely pineapple pineapple chips, diamonds pineapple and pineapple dodol. Pineapple chips are most widely refined products developed by craftsmen in the village Kualu pineapple processing pineapple. Processing of agricultural or agro-industry is a subsystem of agribusiness very big role in increasing the added value of agricultural products. Employers will also seek to do business with a decent order to obtain the maximum revenue to improve their welfare. In connection with this condition, this study aims to conduct feasibility analysis, Break Even Point (BEP, and the added value that can be produced by the pineapple industry. The results showed that the Agro-Industry Pineapple "Thanks to the Joint Enterprises in May 2016 to produce pineapple chips of 651 Kg. With a production cost of Rp. A sum of 45,475,122, - and the revenue generated Rp. 13,114,878, -. Results BEP analysis shows that this business in the breaks even when producing pineapple chips 60 kg with admission of Rp. 5,371,598, -. If the expected profit of Rp. 20.000.000, -, sales of chips should reach 902 Kg. the added value generated by effort "Berkat Bersama" is Rp. 872, - /kg of fresh pineapple. Keywords: Business pineapples, business analysis, value-added
Sandro Chrystop Sinaga
2016-12-01
Full Text Available This study aims to identify marketing channels and market structure pineapple, pineapple analyzing market behavior and analyzing the performance of pineapple fruit market in the village of Kualu Nenas. The data collection method is a survey method. Determination by purposive sampling of respondents and the formula slovin on pineapple growers as much as 33 farmers. Determination of the number of traders, wholesalers and agents agroindustrial determined by census where traders, wholesalers and agents agroindustrial taken based on the accumulation of 33 farmers who sell pineapples to traffickers and agro industry in the village Kualu Nenas, there are 8 traders , 6 wholesalers, and 8 players in the industry. Descriptive analysis of data on the market structure and concentration ratio harfindahl index (HI, for the behavior of markets analyzed by correlation and elasticity of the transmission, and the appearance of markets analyzed by the equation margin trading system. The results showed the market structure market share, concentration ratios, and HI traders at 0.5469, 54.69%, and 0.2990, market share, concentration ratios, and HI wholesalers at 0.6878, 68.78%, and 0.4730, and market share, concentration ratios and HI agro-industry amounted to 0.5145, 51.45%, and 0.2647 of its market structure among the three is oligopsony. Market behavior indicates correlation values 0523 and 0515 transmission elasticity analysis. Appearance market views on marketing margin is relatively large and is dominated by the great results and uneven. Apart from it can be seen also from the uneven distribution margin, the share price received by farmers is still relatively low and the ratio of benefits and costs to farmers is still low. In addition, the bargaining power of farmers is weak because prices are determined unilaterally by traders, especially on the channel I and channel II while the third channel is relatively better because of the level of efficiency is lower
Epistemic uncertainties when estimating component failure rate
Jordan Cizelj, R.; Mavko, B.; Kljenak, I.
2000-01-01
A method for specific estimation of a component failure rate, based on specific quantitative and qualitative data other than component failures, was developed and is described in the proposed paper. The basis of the method is the Bayesian updating procedure. A prior distribution is selected from a generic database, whereas likelihood is built using fuzzy logic theory. With the proposed method, the component failure rate estimation is based on a much larger quantity of information compared to the presently used classical methods. Consequently, epistemic uncertainties, which are caused by lack of knowledge about a component or phenomenon are reduced. (author)
Exchange Rate Volatility, Inflation Uncertainty and Foreign Direct ...
This article examines the effect of exchange rate volatility and inflation uncertainty on foreign direct investment in Nigeria. The investigation covers the period between 1970 and 2005. Exchange rate volatility and inflation uncertainty were estimated using the GARCH model. Estimation results indicated that exchange rate ...
The impact of inflation uncertainty on interest rates
Cheong, Chongcheul; Kim, Gi-Hong; Podivinsky, Jan M.
2010-01-01
In this paper, the impact of inflation uncertainty on interest rates is investigated for the case of the U.S. three-month Treasury bill rate. We emphasize how consistentOLS estimation can be applied to an empirical equation which includes a proxy variable of inflation uncertainty measured by an ARCH-type model. A significant negative relationship between the two variables is provided. This evidence is contrasted with the view of the inflation risk premium in which inflation uncertainty positi...
Impacts of Korea's Exchange Rate Uncertainty on Exports
Kwon Sik Kim
2003-12-01
Full Text Available This paper examines the effects of two types of uncertainty related to the real effective exchange rate (REER in Korea for export trends. To decompose uncertainties into two types of component, I propose an advanced generalized Markov switching model, as developed by Hamilton (1989 and then expanded by Kim and Kim (1996. The proposed model is useful in uncovering two sources of uncertainty: the permanent component of REER and the purely transitory component. I think that the two types of uncertainties have a different effect on export trends in Korea. The transitory component of REER has no effect on the export trend at 5-percent significance, but the permanent component has an effect at this level. In addition, the degree of uncertainty, consisting of low, medium and high uncertainty in the permanent component, and low, medium and high uncertainty in transitory component of REER, also has different effects on export trends in Korea. Only high uncertainty in permanent components effects export trends. The results show that when the policy authority intends to prevent the shrinkage of exports due to the deepening of uncertainties in the foreign exchange market, the economic impacts of its intervention could appear differently according to the characteristics and degree of the uncertainties. Therefore, they imply that its economic measures, which could not grasp the sources of uncertainties properly, may even bring economic costs.
Model Uncertainty and Exchange Rate Forecasting
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
Model Uncertainty and Exchange Rate Forecasting
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
Exchange Rate Volatility, Inflation Uncertainty and Foreign Direct ...
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.
To reflect this uncertainty in the climate scenarios, the use of AOGCMs that explicitly simulate the carbon cycle and chemistry of all the substances are needed. The Hadley Centre has developed a version of the climate model that allows the effect of climate change on the carbon cycle and its feedback into climate, to be ...
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
Impact of measurement uncertainty from experimental load distribution factors on bridge load rating
Gangone, Michael V.; Whelan, Matthew J.
2018-03-01
Load rating and testing of highway bridges is important in determining the capacity of the structure. Experimental load rating utilizes strain transducers placed at critical locations of the superstructure to measure normal strains. These strains are then used in computing diagnostic performance measures (neutral axis of bending, load distribution factor) and ultimately a load rating. However, it has been shown that experimentally obtained strain measurements contain uncertainties associated with the accuracy and precision of the sensor and sensing system. These uncertainties propagate through to the diagnostic indicators that in turn transmit into the load rating calculation. This paper will analyze the effect that measurement uncertainties have on the experimental load rating results of a 3 span multi-girder/stringer steel and concrete bridge. The focus of this paper will be limited to the uncertainty associated with the experimental distribution factor estimate. For the testing discussed, strain readings were gathered at the midspan of each span of both exterior girders and the center girder. Test vehicles of known weight were positioned at specified locations on each span to generate maximum strain response for each of the five girders. The strain uncertainties were used in conjunction with a propagation formula developed by the authors to determine the standard uncertainty in the distribution factor estimates. This distribution factor uncertainty is then introduced into the load rating computation to determine the possible range of the load rating. The results show the importance of understanding measurement uncertainty in experimental load testing.
Covariance methodology applied to uncertainties in I-126 disintegration rate measurements
Fonseca, K.A.; Koskinas, M.F.; Dias, M.S.
1996-01-01
The covariance methodology applied to uncertainties in 126 I disintegration rate measurements is described. Two different coincidence systems were used due to the complex decay scheme of this radionuclide. The parameters involved in the determination of the disintegration rate in each experimental system present correlated components. In this case, the conventional statistical methods to determine the uncertainties (law of propagation) result in wrong values for the final uncertainty. Therefore, use of the methodology of the covariance matrix is necessary. The data from both systems were combined taking into account all possible correlations between the partial uncertainties. (orig.)
Lewandowsky, Stephan; Freeman, Mark C.; Mann, Michael E.
2017-09-01
There is broad consensus among economists that unmitigated climate change will ultimately have adverse global economic consequences, that the costs of inaction will likely outweigh the cost of taking action, and that social planners should therefore put a price on carbon. However, there is considerable debate and uncertainty about the appropriate value of the social discount rate, that is the extent to which future damages should be discounted relative to mitigation costs incurred now. We briefly review the ethical issues surrounding the social discount rate and then report a simulation experiment that constrains the value of the discount rate by considering 4 sources of uncertainty and ambiguity: Scientific uncertainty about the extent of future warming, social uncertainty about future population and future economic development, political uncertainty about future mitigation trajectories, and ethical ambiguity about how much the welfare of future generations should be valued today. We compute a certainty-equivalent declining discount rate that accommodates all those sources of uncertainty and ambiguity. The forward (instantaneous) discount rate converges to a value near 0% by century's end and the spot (horizon) discount rate drops below 2% by 2100 and drops below previous estimates by 2070.
Broadening failure rate distributions in PRA uncertainty analyses
Martz, H.F.
1984-01-01
Several recent nuclear power plant probabilistic risk assessments (PRAs) have utilized broadened Reactor Safety Study (RSS) component failure rate population variability curves to compensate for such things as expert overvaluation bias in the estimates upon which the curves are based. A simple two-components of variation empirical Bayes model is proposed for use in estimating the between-expert variability curve in the presence of such biases. Under certain conditions this curve is a population variability curve. Comparisons are made with the existing method. The popular procedure appears to be generally much more conservative than the empirical Bayes method in removing such biases. In one case the broadened curve based on the popular method is more than two orders of magnitude broader than the empirical Bayes curve. In another case it is found that the maximum justifiable degree of broadening of the RSS curve is to increase α from 5% to 12%, which is significantly less than 20% value recommended in the popular approach. 15 references, 1 figure, 5 tables
Fluid-flow-rate metrology: laboratory uncertainties and traceabilities
Mattingly, G. E.
1991-03-01
Increased concerns for improved fluid flowrate measurement are driving the fluid metering community-meter manufacturers and users alike-to search for better verification and documentation for their fluid measurements. These concerns affect both our domestic and international market places they permeate our technologies - aerospace chemical processes automotive bioengineering etc. They involve public health and safety and they impact our national defense. These concerns are based upon the rising value of fluid resources and products and the importance of critical material accountability. These values directly impact the accuracy needs of fluid buyers and sellers in custody transfers. These concerns impact the designers and operators of chemical process systems where control and productivity optimization depend critically upon measurement precision. Public health and safety depend upon the quality of numerous pollutant measurements - both liquid and gaseous. The performance testing of engines - both automotive and aircraft are critically based upon accurate fuel measurements - both liquid and oxidizer streams. Fluid flowrate measurements are established differently from counterparts in length and mass measurement systems because these have the benefits of " identity" standards. For rate measurement systems the metrology is based upon " derived standards" . These use facilities and transfer standards which are designed built characterized and used to constitute basic measurement capabilities and quantify performance - accuracy and precision. Because " identity standards" do not exist for flow measurements facsimiles or equivalents must
Impact of Pitot tube calibration on the uncertainty of water flow rate measurement
de Oliveira Buscarini, Icaro; Costa Barsaglini, Andre; Saiz Jabardo, Paulo Jose; Massami Taira, Nilson; Nader, Gilder
2015-10-01
Water utility companies often use Cole type Pitot tubes to map velocity profiles and thus measure flow rate. Frequent monitoring and measurement of flow rate is an important step in identifying leaks and other types of losses. In Brazil losses as high as 42% are common and in some places even higher values are found. When using Cole type Pitot tubes to measure the flow rate, the uncertainty of the calibration coefficient (Cd) is a major component of the overall flow rate measurement uncertainty. A common practice is to employ the usual value Cd = 0.869, in use since Cole proposed his Pitot tube in 1896. Analysis of 414 calibrations of Cole type Pitot tubes show that Cd varies considerably and values as high 0.020 for the expanded uncertainty are common. Combined with other uncertainty sources, the overall velocity measurement uncertainty is 0.02, increasing flowrate measurement uncertainty by 1.5% which, for the Sao Paulo metropolitan area (Brazil) corresponds to 3.5 × 107 m3/year.
Eleanor S Devenish Nelson
Full Text Available BACKGROUND: Demographic models are widely used in conservation and management, and their parameterisation often relies on data collected for other purposes. When underlying data lack clear indications of associated uncertainty, modellers often fail to account for that uncertainty in model outputs, such as estimates of population growth. METHODOLOGY/PRINCIPAL FINDINGS: We applied a likelihood approach to infer uncertainty retrospectively from point estimates of vital rates. Combining this with resampling techniques and projection modelling, we show that confidence intervals for population growth estimates are easy to derive. We used similar techniques to examine the effects of sample size on uncertainty. Our approach is illustrated using data on the red fox, Vulpes vulpes, a predator of ecological and cultural importance, and the most widespread extant terrestrial mammal. We show that uncertainty surrounding estimated population growth rates can be high, even for relatively well-studied populations. Halving that uncertainty typically requires a quadrupling of sampling effort. CONCLUSIONS/SIGNIFICANCE: Our results compel caution when comparing demographic trends between populations without accounting for uncertainty. Our methods will be widely applicable to demographic studies of many species.
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
B. Newsome
2017-12-01
Full Text Available Chemical rate constants determine the composition of the atmosphere and how this composition has changed over time. They are central to our understanding of climate change and air quality degradation. Atmospheric chemistry models, whether online or offline, box, regional or global, use these rate constants. Expert panels evaluate laboratory measurements, making recommendations for the rate constants that should be used. This results in very similar or identical rate constants being used by all models. The inherent uncertainties in these recommendations are, in general, therefore ignored. We explore the impact of these uncertainties on the composition of the troposphere using the GEOS-Chem chemistry transport model. Based on the Jet Propulsion Laboratory (JPL and International Union of Pure and Applied Chemistry (IUPAC evaluations we assess the influence of 50 mainly inorganic rate constants and 10 photolysis rates on tropospheric composition through the use of the GEOS-Chem chemistry transport model. We assess the impact on four standard metrics: annual mean tropospheric ozone burden, surface ozone and tropospheric OH concentrations, and tropospheric methane lifetime. Uncertainty in the rate constants for NO2 + OH →M HNO3 and O3 + NO → NO2 + O2 are the two largest sources of uncertainty in these metrics. The absolute magnitude of the change in the metrics is similar if rate constants are increased or decreased by their σ values. We investigate two methods of assessing these uncertainties, addition in quadrature and a Monte Carlo approach, and conclude they give similar outcomes. Combining the uncertainties across the 60 reactions gives overall uncertainties on the annual mean tropospheric ozone burden, surface ozone and tropospheric OH concentrations, and tropospheric methane lifetime of 10, 11, 16 and 16 %, respectively. These are larger than the spread between models in recent model intercomparisons. Remote
Smuggling, non-fundamental uncertainty, and parallel market exchange rate volatility
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...
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
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.
Bayesian analysis of stage-fall-discharge rating curves and their uncertainties
Mansanarez, Valentin; Le Coz, Jérôme; Renard, Benjamin; Lang, Michel; Pierrefeu, Gilles; Le Boursicaud, Raphaël; Pobanz, Karine
2016-04-01
Stage-fall-discharge (SFD) rating curves are traditionally used to compute streamflow records at sites where the energy slope of the flow is variable due to variable backwater effects. Building on existing Bayesian approaches, we introduce an original hydraulics-based method for developing SFD rating curves used at twin gauge stations and estimating their uncertainties. Conventional power functions for channel and section controls are used, and transition to a backwater-affected channel control is computed based on a continuity condition, solved either analytically or numerically. The difference between the reference levels at the two stations is estimated as another uncertain parameter of the SFD model. The method proposed in this presentation incorporates information from both the hydraulic knowledge (equations of channel or section controls) and the information available in the stage-fall-discharge observations (gauging data). The obtained total uncertainty combines the parametric uncertainty and the remnant uncertainty related to the model of rating curve. This method provides a direct estimation of the physical inputs of the rating curve (roughness, width, slope bed, distance between twin gauges, etc.). The performance of the new method is tested using an application case affected by the variable backwater of a run-of-the-river dam: the Rhône river at Valence, France. In particular, a sensitivity analysis to the prior information and to the gauging dataset is performed. At that site, the stage-fall-discharge domain is well documented with gaugings conducted over a range of backwater affected and unaffected conditions. The performance of the new model was deemed to be satisfactory. Notably, transition to uniform flow when the overall range of the auxiliary stage is gauged is correctly simulated. The resulting curves are in good agreement with the observations (gaugings) and their uncertainty envelopes are acceptable for computing streamflow records. Similar
Ionization balance for Ti and Cr ions: effects of uncertainty in dielectronic recombination rate
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
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.
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.
Uncertainty estimation with bias-correction for flow series based on rating curve
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.
Exchange rate uncertainty and deviations from Purchasing\\ud Power Parity: evidence from the G7 area
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.
Estimation of Uncertainty in Tracer Gas Measurement of Air Change Rates
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
MERGERS IN ΛCDM: UNCERTAINTIES IN THEORETICAL PREDICTIONS AND INTERPRETATIONS OF THE MERGER RATE
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
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.
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.
Build to order and entry/exit strategies under exchange rate uncertainty
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.
Uncertainties and quantification of common cause failure rates and probabilities for system analyses
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
Low-sampling-rate ultra-wideband channel estimation using a bounded-data-uncertainty approach
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.
SU-F-T-301: Planar Dose Pass Rate Inflation Due to the MapCHECK Measurement Uncertainty Function
Bailey, D; Spaans, J; Kumaraswamy, L; Podgorsak, M
2016-01-01
Purpose: To quantify the effect of the Measurement Uncertainty function on planar dosimetry pass rates, as analyzed with Sun Nuclear Corporation analytic software (“MapCHECK” or “SNC Patient”). This optional function is toggled on by default upon software installation, and automatically increases the user-defined dose percent difference (%Diff) tolerance for each planar dose comparison. Methods: Dose planes from 109 IMRT fields and 40 VMAT arcs were measured with the MapCHECK 2 diode array, and compared to calculated planes from a commercial treatment planning system. Pass rates were calculated within the SNC analytic software using varying calculation parameters, including Measurement Uncertainty on and off. By varying the %Diff criterion for each dose comparison performed with Measurement Uncertainty turned off, an effective %Diff criterion was defined for each field/arc corresponding to the pass rate achieved with MapCHECK Uncertainty turned on. Results: For 3%/3mm analysis, the Measurement Uncertainty function increases the user-defined %Diff by 0.8–1.1% average, depending on plan type and calculation technique, for an average pass rate increase of 1.0–3.5% (maximum +8.7%). For 2%, 2 mm analysis, the Measurement Uncertainty function increases the user-defined %Diff by 0.7–1.2% average, for an average pass rate increase of 3.5–8.1% (maximum +14.2%). The largest increases in pass rate are generally seen with poorly-matched planar dose comparisons; the MapCHECK Uncertainty effect is markedly smaller as pass rates approach 100%. Conclusion: The Measurement Uncertainty function may substantially inflate planar dose comparison pass rates for typical IMRT and VMAT planes. The types of uncertainties incorporated into the function (and their associated quantitative estimates) as described in the software user’s manual may not accurately estimate realistic measurement uncertainty for the user’s measurement conditions. Pass rates listed in published
SU-F-T-301: Planar Dose Pass Rate Inflation Due to the MapCHECK Measurement Uncertainty Function
Bailey, D [Northside Hospital Cancer Institute, Atlanta, GA (United States); Spaans, J; Kumaraswamy, L; Podgorsak, M [Roswell Park Cancer Institute, Buffalo, NY (United States)
2016-06-15
Purpose: To quantify the effect of the Measurement Uncertainty function on planar dosimetry pass rates, as analyzed with Sun Nuclear Corporation analytic software (“MapCHECK” or “SNC Patient”). This optional function is toggled on by default upon software installation, and automatically increases the user-defined dose percent difference (%Diff) tolerance for each planar dose comparison. Methods: Dose planes from 109 IMRT fields and 40 VMAT arcs were measured with the MapCHECK 2 diode array, and compared to calculated planes from a commercial treatment planning system. Pass rates were calculated within the SNC analytic software using varying calculation parameters, including Measurement Uncertainty on and off. By varying the %Diff criterion for each dose comparison performed with Measurement Uncertainty turned off, an effective %Diff criterion was defined for each field/arc corresponding to the pass rate achieved with MapCHECK Uncertainty turned on. Results: For 3%/3mm analysis, the Measurement Uncertainty function increases the user-defined %Diff by 0.8–1.1% average, depending on plan type and calculation technique, for an average pass rate increase of 1.0–3.5% (maximum +8.7%). For 2%, 2 mm analysis, the Measurement Uncertainty function increases the user-defined %Diff by 0.7–1.2% average, for an average pass rate increase of 3.5–8.1% (maximum +14.2%). The largest increases in pass rate are generally seen with poorly-matched planar dose comparisons; the MapCHECK Uncertainty effect is markedly smaller as pass rates approach 100%. Conclusion: The Measurement Uncertainty function may substantially inflate planar dose comparison pass rates for typical IMRT and VMAT planes. The types of uncertainties incorporated into the function (and their associated quantitative estimates) as described in the software user’s manual may not accurately estimate realistic measurement uncertainty for the user’s measurement conditions. Pass rates listed in published
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.
A sensitivity study of s-process: the impact of uncertainties from nuclear reaction rates
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%.
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.
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
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.
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
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
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)
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)
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.
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.
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).
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
On the estimation of failure rates for living PSAs in the presence of model uncertainty
Arsenis, S.P.
1994-01-01
The estimation of failure rates of heterogeneous Poisson components from data on times operated to failures is reviewed. Particular emphasis is given to the lack of knowledge on the form of the mixing distribution or population variability curve. A new nonparametric epirical Bayes estimation is proposed which generalizes the estimator of Robbins for different times of observations for the components. The behavior of the estimator is discussed by reference to two samples typically drawn from the CEDB, a component event database designed and operated by the Ispra JRC
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
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)
Martz, H.F.; Beckman, R.J.
1981-12-01
Probabilistic risk analyses are used to assess the risks inherent in the operation of existing and proposed nuclear power reactors. In performing such risk analyses the failure rates of various components which are used in a variety of reactor systems must be estimated. These failure rate estimates serve as input to fault trees and event trees used in the analyses. Component failure rate estimation is often based on relevant field failure data from different reliability data sources such as LERs, NPRDS, and the In-Plant Data Program. Various statistical data analysis and estimation methods have been proposed over the years to provide the required estimates of the component failure rates. This report discusses the basis and extent to which statistical methods can be used to obtain component failure rate estimates. The report is expository in nature and focuses on the general philosophical basis for such statistical methods. Various terms and concepts are defined and illustrated by means of numerous simple examples
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
THE INFLUENCE OF UNCERTAINTIES IN THE 15O(α, γ)19Ne REACTION RATE ON MODELS OF TYPE I X-RAY BURSTS
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.
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.
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.
Graham, I.J.
1996-01-01
Cosmogenic nuclides, produced in-situ in rocks by the action of cosmic rays on target nuclei, are increasingly being employed by earth scientists in a wide variety of applications. For example, surface exposure dating is used to determine erosion rates, the age of debris flows, alluvial fans, volcanic eruptions, meteoritic impact craters, and glacial deposits, and the timing of recent movement along faults and tectonic uplift. The technique can thus play a vital role in the study of potential hazards from geological processes, by establishing recurrence intervals between them, and establish chronologies and periodicities for major paleoclimatic events. Before surface exposure dating methods using cosmogenic isotopes can be applied even more widely, production rates of the main nuclides of interest must be better known, and their temporal and spatial variabilities determined. This paper summarises the present state of knowledge on production rates of the currently most useful nuclides ( 10 Be, 26 Al, 36 Cl, 14 C, 3 He and 21 Ne), discusses the main areas of concern, and makes suggestions for future improvement. (author). 83 refs., 7 tabs., 11 figs
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.
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.
Darghouth, Naim Richard
three types of retail rates (a flat rate, a time-of-use rate, and real-time pricing) from these wholesale price profiles, I examine bill savings from PV generation for the ten wholesale market scenarios under net metering and an alternative to net metering where hourly excess PV generation is compensated at the wholesale price. Most generally, I challenge the common assertion that PV compensation is likely to stay constant (or rise) due to constant (or rising) retail rates, and find that future electricity market scenarios can drive substantial changes in residential retail rates and that these changes, in concert with variations in retail rate structures and PV compensation mechanisms, interact to place substantial uncertainty on the future value of bill savings from residential PV.
Uncertainty in hydrological signatures
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
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.
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.
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
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...
Duerdoth, Ian
2009-01-01
The subject of uncertainties (sometimes called errors) is traditionally taught (to first-year science undergraduates) towards the end of a course on statistics that defines probability as the limit of many trials, and discusses probability distribution functions and the Gaussian distribution. We show how to introduce students to the concepts of…
Heydorn, Kaj; Anglov, Thomas
2002-01-01
Methods recommended by the International Standardization Organisation and Eurachem are not satisfactory for the correct estimation of calibration uncertainty. A novel approach is introduced and tested on actual calibration data for the determination of Pb by ICP-AES. The improved calibration...
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.
Mashouf, S; Merino, T; Ravi, A; Morton, G; Song, W [Sunnybrook Health Sciences Center, Odette Cancer Centre, Toronto, ON (Canada); University of Toronto, Dept. of Radiation Oncology, Toronto, ON (Canada); Safigholi, H; Soliman, A [Sunnybrook Research Institute, Toronto, ON (Canada)
2016-06-15
Purpose: There is strong evidence relating post-implant dosimetry for low-dose-rate (LDR) prostate seed brachytherapy to local control rates. The delineation of the prostate on CT images, however, represents a challenge due to the lack of soft tissue contrast in order to identify the prostate borders. This study aims at quantifying the sensitivity of clinically relevant dosimetric parameters to uncertainty in the contouring of prostate. Methods: CT images, post-op plans and contours of a cohort of patients (n=43) (low risk=55.8%, intermediate risk=39.5%, high risk=4.7%), who had received prostate seed brachytherapy, were imported into MIM Symphony treatment planning system. The prostate contours in post-implant CT images were expanded/contracted uniformly for margins of ±1.00 mm, ±2.00 mm, ±3.00 mm, ±4.00 mm and ±5.00 mm. The values for V100 and D90 were extracted from Dose Volume Histograms for each contour and compared. Results: Significant changes were observed in the values of D90 and V100 as well as the number of suboptimal plans for expansion or contraction margins of only few millimeters. Evaluation of coverage based on D90 was found to be less sensitive to expansion errors compared to V100. D90 led to a lower number of implants incorrectly identified with insufficient coverage for expanded contours which increases the accuracy of post-implant QA using CT images compared to V100. Conclusion: In order to establish a successful post implant QA for LDR prostate seed brachytherapy, it is necessary to identify the low and high thresholds of important dose metrics of the target volume such as D90 and V100. Since these parameters are sensitive to target volume definition, accurate identification of prostate borders would help to improve accuracy and predictive value of the post-implant QA process. In this respect, use of imaging modalities such as MRI where prostate is well delineated should prove useful.
Mashouf, S; Merino, T; Ravi, A; Morton, G; Song, W; Safigholi, H; Soliman, A
2016-01-01
Purpose: There is strong evidence relating post-implant dosimetry for low-dose-rate (LDR) prostate seed brachytherapy to local control rates. The delineation of the prostate on CT images, however, represents a challenge due to the lack of soft tissue contrast in order to identify the prostate borders. This study aims at quantifying the sensitivity of clinically relevant dosimetric parameters to uncertainty in the contouring of prostate. Methods: CT images, post-op plans and contours of a cohort of patients (n=43) (low risk=55.8%, intermediate risk=39.5%, high risk=4.7%), who had received prostate seed brachytherapy, were imported into MIM Symphony treatment planning system. The prostate contours in post-implant CT images were expanded/contracted uniformly for margins of ±1.00 mm, ±2.00 mm, ±3.00 mm, ±4.00 mm and ±5.00 mm. The values for V100 and D90 were extracted from Dose Volume Histograms for each contour and compared. Results: Significant changes were observed in the values of D90 and V100 as well as the number of suboptimal plans for expansion or contraction margins of only few millimeters. Evaluation of coverage based on D90 was found to be less sensitive to expansion errors compared to V100. D90 led to a lower number of implants incorrectly identified with insufficient coverage for expanded contours which increases the accuracy of post-implant QA using CT images compared to V100. Conclusion: In order to establish a successful post implant QA for LDR prostate seed brachytherapy, it is necessary to identify the low and high thresholds of important dose metrics of the target volume such as D90 and V100. Since these parameters are sensitive to target volume definition, accurate identification of prostate borders would help to improve accuracy and predictive value of the post-implant QA process. In this respect, use of imaging modalities such as MRI where prostate is well delineated should prove useful.
Nguyen, Daniel Xuyen
This paper presents a model of trade that explains why firms wait to export and why many exporters fail. Firms face uncertain demands that are only realized after the firm enters the destination. The model retools the timing of uncertainty resolution found in productivity heterogeneity models....... This retooling addresses several shortcomings. First, the imperfect correlation of demands reconciles the sales variation observed in and across destinations. Second, since demands for the firm's output are correlated across destinations, a firm can use previously realized demands to forecast unknown demands...... in untested destinations. The option to forecast demands causes firms to delay exporting in order to gather more information about foreign demand. Third, since uncertainty is resolved after entry, many firms enter a destination and then exit after learning that they cannot profit. This prediction reconciles...
Uncertainty, joint uncertainty, and the quantum uncertainty principle
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)
Zou, Xiao-Duan; Li, Jian-Yang; Clark, Beth Ellen; Golish, Dathon
2018-01-01
The OSIRIS-REx spacecraft, launched in September, 2016, will study the asteroid Bennu and return a sample from its surface to Earth in 2023. Bennu is a near-Earth carbonaceous asteroid which will provide insight into the formation and evolution of the solar system. OSIRIS-REx will first approach Bennu in August 2018 and will study the asteroid for approximately two years before sampling. OSIRIS-REx will develop its photometric model (including Lommel-Seelinger, ROLO, McEwen, Minnaert and Akimov) of Bennu with OCAM and OVIRS during the Detailed Survey mission phase. The model developed during this phase will be used to photometrically correct the OCAM and OVIRS data.Here we present the analysis of the error for the photometric corrections. Based on our testing data sets, we find:1. The model uncertainties is only correct when we use the covariance matrix to calculate, because the parameters are highly correlated.2. No evidence of domination of any parameter in each model.3. And both model error and the data error contribute to the final correction error comparably.4. We tested the uncertainty module on fake and real data sets, and find that model performance depends on the data coverage and data quality. These tests gave us a better understanding of how different model behave in different case.5. L-S model is more reliable than others. Maybe because the simulated data are based on L-S model. However, the test on real data (SPDIF) does show slight advantage of L-S, too. ROLO is not reliable to use when calculating bond albedo. The uncertainty of McEwen model is big in most cases. Akimov performs unphysical on SOPIE 1 data.6. Better use L-S as our default choice, this conclusion is based mainly on our test on SOPIE data and IPDIF.
Thomas, R.E.
1982-03-01
An evaluation is made of the suitability of analytical and statistical sampling methods for making uncertainty analyses. The adjoint method is found to be well-suited for obtaining sensitivity coefficients for computer programs involving large numbers of equations and input parameters. For this purpose the Latin Hypercube Sampling method is found to be inferior to conventional experimental designs. The Latin hypercube method can be used to estimate output probability density functions, but requires supplementary rank transformations followed by stepwise regression to obtain uncertainty information on individual input parameters. A simple Cork and Bottle problem is used to illustrate the efficiency of the adjoint method relative to certain statistical sampling methods. For linear models of the form Ax=b it is shown that a complete adjoint sensitivity analysis can be made without formulating and solving the adjoint problem. This can be done either by using a special type of statistical sampling or by reformulating the primal problem and using suitable linear programming software
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.)
Flood modelling : Parameterisation and inflow uncertainty
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
Deterministic uncertainty analysis
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
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)
Austin, Sam M. [National Superconducting Cyclotron Laboratory, Michigan State University, 640 South Shaw Lane, East Lansing, MI 48824-1321 (United States); West, Christopher; Heger, Alexander, E-mail: austin@nscl.msu.edu, E-mail: christopher.west@metrostate.edu, E-mail: Alexander.Heger@Monash.edu [Joint Institute for Nuclear Astrophysics—Center for the Evolution of the Elements, Michigan State University, East Lansing, MI 48824-1321 (United States)
2017-04-10
We have used effective reaction rates (ERRs) for the helium burning reactions to predict the yield of the gamma-emitting nuclei {sup 26}Al, {sup 44}Ti, and {sup 60}Fe in core-collapse supernovae (SNe). The variations in the predicted yields for values of the reaction rates allowed by the ERR are much smaller than obtained previously, and smaller than other uncertainties. A “filter” for SN nucleosynthesis yields based on pre-SN structure was used to estimate the effect of failed SNe on the initial mass function averaged yields; this substantially reduced the yields of all these isotopes, but the predicted yield ratio {sup 60}Fe/{sup 26}Al was little affected. The robustness of this ratio is promising for comparison with data, but it is larger than observed in nature; possible causes for this discrepancy are discussed.
The uncertainties in estimating measurement uncertainties
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
Uncertainty in social dilemmas
Kwaadsteniet, Erik Willem de
2007-01-01
This dissertation focuses on social dilemmas, and more specifically, on environmental uncertainty in these dilemmas. Real-life social dilemma situations are often characterized by uncertainty. For example, fishermen mostly do not know the exact size of the fish population (i.e., resource size uncertainty). Several researchers have therefore asked themselves the question as to how such uncertainty influences people’s choice behavior. These researchers have repeatedly concluded that uncertainty...
Instrument uncertainty predictions
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
Decision making under uncertainty
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
Investment Timing and Capacity Choice under Uncertainty
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.
Estimates of Uncertainty around the RBA's Forecasts
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.
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)
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 and Cognitive Control
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.
Capital flight and the uncertainty of government policies
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.
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.)
Model uncertainty and probability
Parry, G.W.
1994-01-01
This paper discusses the issue of model uncertainty. The use of probability as a measure of an analyst's uncertainty as well as a means of describing random processes has caused some confusion, even though the two uses are representing different types of uncertainty with respect to modeling a system. The importance of maintaining the distinction between the two types is illustrated with a simple example
Uncertainty in artificial intelligence
Kanal, LN
1986-01-01
How to deal with uncertainty is a subject of much controversy in Artificial Intelligence. This volume brings together a wide range of perspectives on uncertainty, many of the contributors being the principal proponents in the controversy.Some of the notable issues which emerge from these papers revolve around an interval-based calculus of uncertainty, the Dempster-Shafer Theory, and probability as the best numeric model for uncertainty. There remain strong dissenting opinions not only about probability but even about the utility of any numeric method in this context.
Uncertainties in hydrogen combustion
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
Towards a different attitude to uncertainty
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.
Risk, unexpected uncertainty, and estimation uncertainty: Bayesian learning in unstable settings.
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.
Uncertainty in social dilemmas
Kwaadsteniet, Erik Willem de
2007-01-01
This dissertation focuses on social dilemmas, and more specifically, on environmental uncertainty in these dilemmas. Real-life social dilemma situations are often characterized by uncertainty. For example, fishermen mostly do not know the exact size of the fish population (i.e., resource size
Uncertainty and Climate Change
Berliner, L. Mark
2003-01-01
Anthropogenic, or human-induced, climate change is a critical issue in science and in the affairs of humankind. Though the target of substantial research, the conclusions of climate change studies remain subject to numerous uncertainties. This article presents a very brief review of the basic arguments regarding anthropogenic climate change with particular emphasis on uncertainty.
Deterministic uncertainty analysis
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
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
Conditional uncertainty principle
Gour, Gilad; Grudka, Andrzej; Horodecki, Michał; Kłobus, Waldemar; Łodyga, Justyna; Narasimhachar, Varun
2018-04-01
We develop a general operational framework that formalizes the concept of conditional uncertainty in a measure-independent fashion. Our formalism is built upon a mathematical relation which we call conditional majorization. We define conditional majorization and, for the case of classical memory, we provide its thorough characterization in terms of monotones, i.e., functions that preserve the partial order under conditional majorization. We demonstrate the application of this framework by deriving two types of memory-assisted uncertainty relations, (1) a monotone-based conditional uncertainty relation and (2) a universal measure-independent conditional uncertainty relation, both of which set a lower bound on the minimal uncertainty that Bob has about Alice's pair of incompatible measurements, conditioned on arbitrary measurement that Bob makes on his own system. We next compare the obtained relations with their existing entropic counterparts and find that they are at least independent.
Physical Uncertainty Bounds (PUB)
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.
Measurement uncertainty and probability
Willink, Robin
2013-01-01
A measurement result is incomplete without a statement of its 'uncertainty' or 'margin of error'. But what does this statement actually tell us? By examining the practical meaning of probability, this book discusses what is meant by a '95 percent interval of measurement uncertainty', and how such an interval can be calculated. The book argues that the concept of an unknown 'target value' is essential if probability is to be used as a tool for evaluating measurement uncertainty. It uses statistical concepts, such as a conditional confidence interval, to present 'extended' classical methods for evaluating measurement uncertainty. The use of the Monte Carlo principle for the simulation of experiments is described. Useful for researchers and graduate students, the book also discusses other philosophies relating to the evaluation of measurement uncertainty. It employs clear notation and language to avoid the confusion that exists in this controversial field of science.
Uncertainty Propagation in OMFIT
Smith, Sterling; Meneghini, Orso; Sung, Choongki
2017-10-01
A rigorous comparison of power balance fluxes and turbulent model fluxes requires the propagation of uncertainties in the kinetic profiles and their derivatives. Making extensive use of the python uncertainties package, the OMFIT framework has been used to propagate covariant uncertainties to provide an uncertainty in the power balance calculation from the ONETWO code, as well as through the turbulent fluxes calculated by the TGLF code. The covariant uncertainties arise from fitting 1D (constant on flux surface) density and temperature profiles and associated random errors with parameterized functions such as a modified tanh. The power balance and model fluxes can then be compared with quantification of the uncertainties. No effort is made at propagating systematic errors. A case study will be shown for the effects of resonant magnetic perturbations on the kinetic profiles and fluxes at the top of the pedestal. A separate attempt at modeling the random errors with Monte Carlo sampling will be compared to the method of propagating the fitting function parameter covariant uncertainties. Work supported by US DOE under DE-FC02-04ER54698, DE-FG2-95ER-54309, DE-SC 0012656.
Chemical model reduction under uncertainty
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.
Verification of uncertainty budgets
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...
Evaluating prediction uncertainty
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
Uncertainties and climatic change
De Gier, A.M.; Opschoor, J.B.; Van de Donk, W.B.H.J.; Hooimeijer, P.; Jepma, J.; Lelieveld, J.; Oerlemans, J.; Petersen, A.
2008-01-01
Which processes in the climate system are misunderstood? How are scientists dealing with uncertainty about climate change? What will be done with the conclusions of the recently published synthesis report of the IPCC? These and other questions were answered during the meeting 'Uncertainties and climate change' that was held on Monday 26 November 2007 at the KNAW in Amsterdam. This report is a compilation of all the presentations and provides some conclusions resulting from the discussions during this meeting. [mk] [nl
Lemaire, Maurice
2014-01-01
Science is a quest for certainty, but lack of certainty is the driving force behind all of its endeavors. This book, specifically, examines the uncertainty of technological and industrial science. Uncertainty and Mechanics studies the concepts of mechanical design in an uncertain setting and explains engineering techniques for inventing cost-effective products. Though it references practical applications, this is a book about ideas and potential advances in mechanical science.
Uncertainty: lotteries and risk
Ávalos, Eloy
2011-01-01
In this paper we develop the theory of uncertainty in a context where the risks assumed by the individual are measurable and manageable. We primarily use the definition of lottery to formulate the axioms of the individual's preferences, and its representation through the utility function von Neumann - Morgenstern. We study the expected utility theorem and its properties, the paradoxes of choice under uncertainty and finally the measures of risk aversion with monetary lotteries.
Uncertainty calculations made easier
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)
Justification for recommended uncertainties
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
Treatment of uncertainties in the geologic disposal of radioactive waste
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
Uncertainty analysis for secondary energy distributions
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
Uncertainty in hydrological signatures for gauged and ungauged catchments
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.
Dealing with exploration uncertainties
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
Uncertainty Propagation in Monte Carlo Depletion Analysis
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)
Uncertainty in artificial intelligence
Levitt, TS; Lemmer, JF; Shachter, RD
1990-01-01
Clearly illustrated in this volume is the current relationship between Uncertainty and AI.It has been said that research in AI revolves around five basic questions asked relative to some particular domain: What knowledge is required? How can this knowledge be acquired? How can it be represented in a system? How should this knowledge be manipulated in order to provide intelligent behavior? How can the behavior be explained? In this volume, all of these questions are addressed. From the perspective of the relationship of uncertainty to the basic questions of AI, the book divides naturally i
Sensitivity and uncertainty analysis
Cacuci, Dan G; Navon, Ionel Michael
2005-01-01
As computer-assisted modeling and analysis of physical processes have continued to grow and diversify, sensitivity and uncertainty analyses have become indispensable scientific tools. Sensitivity and Uncertainty Analysis. Volume I: Theory focused on the mathematical underpinnings of two important methods for such analyses: the Adjoint Sensitivity Analysis Procedure and the Global Adjoint Sensitivity Analysis Procedure. This volume concentrates on the practical aspects of performing these analyses for large-scale systems. The applications addressed include two-phase flow problems, a radiative c
Predictive uncertainty in auditory sequence processing
Niels Chr. eHansen
2014-09-01
Full Text Available Previous studies of auditory expectation have focused on the expectedness perceived by listeners retrospectively in response to events. In contrast, this research examines predictive uncertainty - a property of listeners’ prospective state of expectation prior to the onset of an event. We examine the information-theoretic concept of Shannon entropy as a model of predictive uncertainty in music cognition. This is motivated by the Statistical Learning Hypothesis, which proposes that schematic expectations reflect probabilistic relationships between sensory events learned implicitly through exposure.Using probability estimates from an unsupervised, variable-order Markov model, 12 melodic contexts high in entropy and 12 melodic contexts low in entropy were selected from two musical repertoires differing in structural complexity (simple and complex. Musicians and non-musicians listened to the stimuli and provided explicit judgments of perceived uncertainty (explicit uncertainty. We also examined an indirect measure of uncertainty computed as the entropy of expectedness distributions obtained using a classical probe-tone paradigm where listeners rated the perceived expectedness of the final note in a melodic sequence (inferred uncertainty. Finally, we simulate listeners’ perception of expectedness and uncertainty using computational models of auditory expectation. A detailed model comparison indicates which model parameters maximize fit to the data and how they compare to existing models in the literature.The results show that listeners experience greater uncertainty in high-entropy musical contexts than low-entropy contexts. This effect is particularly apparent for inferred uncertainty and is stronger in musicians than non-musicians. Consistent with the Statistical Learning Hypothesis, the results suggest that increased domain-relevant training is associated with an increasingly accurate cognitive model of probabilistic structure in music.
Predictive uncertainty in auditory sequence processing.
Hansen, Niels Chr; Pearce, Marcus T
2014-01-01
Previous studies of auditory expectation have focused on the expectedness perceived by listeners retrospectively in response to events. In contrast, this research examines predictive uncertainty-a property of listeners' prospective state of expectation prior to the onset of an event. We examine the information-theoretic concept of Shannon entropy as a model of predictive uncertainty in music cognition. This is motivated by the Statistical Learning Hypothesis, which proposes that schematic expectations reflect probabilistic relationships between sensory events learned implicitly through exposure. Using probability estimates from an unsupervised, variable-order Markov model, 12 melodic contexts high in entropy and 12 melodic contexts low in entropy were selected from two musical repertoires differing in structural complexity (simple and complex). Musicians and non-musicians listened to the stimuli and provided explicit judgments of perceived uncertainty (explicit uncertainty). We also examined an indirect measure of uncertainty computed as the entropy of expectedness distributions obtained using a classical probe-tone paradigm where listeners rated the perceived expectedness of the final note in a melodic sequence (inferred uncertainty). Finally, we simulate listeners' perception of expectedness and uncertainty using computational models of auditory expectation. A detailed model comparison indicates which model parameters maximize fit to the data and how they compare to existing models in the literature. The results show that listeners experience greater uncertainty in high-entropy musical contexts than low-entropy contexts. This effect is particularly apparent for inferred uncertainty and is stronger in musicians than non-musicians. Consistent with the Statistical Learning Hypothesis, the results suggest that increased domain-relevant training is associated with an increasingly accurate cognitive model of probabilistic structure in music.
Uncertainty Analyses and Strategy
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
Uncertainties in repository modeling
Wilson, J.R.
1996-12-31
The distant future is ver difficult to predict. Unfortunately, our regulators are being enchouraged to extend ther regulatory period form the standard 10,000 years to 1 million years. Such overconfidence is not justified due to uncertainties in dating, calibration, and modeling.
Uncertainties in repository modeling
Wilson, J.R.
1996-01-01
The distant future is ver difficult to predict. Unfortunately, our regulators are being enchouraged to extend ther regulatory period form the standard 10,000 years to 1 million years. Such overconfidence is not justified due to uncertainties in dating, calibration, and modeling
Haefele, W.; Renn, O.; Erdmann, G.
1990-01-01
The notion of 'risk' is discussed in its social and technological contexts, leading to an investigation of the terms factuality, hypotheticality, uncertainty, and vagueness, and to the problems of acceptance and acceptability especially in the context of political decision finding. (DG) [de
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.
ICYESS 2013: Understanding and Interpreting Uncertainty
Rauser, F.; Niederdrenk, L.; Schemann, V.; Schmidt, A.; Suesser, D.; Sonntag, S.
2013-12-01
We will report the outcomes and highlights of the Interdisciplinary Conference of Young Earth System Scientists (ICYESS) on Understanding and Interpreting Uncertainty in September 2013, Hamburg, Germany. This conference is aimed at early career scientists (Masters to Postdocs) from a large variety of scientific disciplines and backgrounds (natural, social and political sciences) and will enable 3 days of discussions on a variety of uncertainty-related aspects: 1) How do we deal with implicit and explicit uncertainty in our daily scientific work? What is uncertain for us, and for which reasons? 2) How can we communicate these uncertainties to other disciplines? E.g., is uncertainty in cloud parameterization and respectively equilibrium climate sensitivity a concept that is understood equally well in natural and social sciences that deal with Earth System questions? Or vice versa, is, e.g., normative uncertainty as in choosing a discount rate relevant for natural scientists? How can those uncertainties be reconciled? 3) How can science communicate this uncertainty to the public? Is it useful at all? How are the different possible measures of uncertainty understood in different realms of public discourse? Basically, we want to learn from all disciplines that work together in the broad Earth System Science community how to understand and interpret uncertainty - and then transfer this understanding to the problem of how to communicate with the public, or its different layers / agents. ICYESS is structured in a way that participation is only possible via presentation, so every participant will give their own professional input into how the respective disciplines deal with uncertainty. Additionally, a large focus is put onto communication techniques; there are no 'standard presentations' in ICYESS. Keynote lectures by renowned scientists and discussions will lead to a deeper interdisciplinary understanding of what we do not really know, and how to deal with it. Many
Uncertainty as Knowledge: Constraints on Policy Choices Provided by Analysis of Uncertainty
Lewandowsky, S.; Risbey, J.; Smithson, M.; Newell, B. R.
2012-12-01
Uncertainty forms an integral part of climate science, and it is often cited in connection with arguments against mitigative action. We argue that an analysis of uncertainty must consider existing knowledge as well as uncertainty, and the two must be evaluated with respect to the outcomes and risks associated with possible policy options. Although risk judgments are inherently subjective, an analysis of the role of uncertainty within the climate system yields two constraints that are robust to a broad range of assumptions. Those constraints are that (a) greater uncertainty about the climate system is necessarily associated with greater expected damages from warming, and (b) greater uncertainty translates into a greater risk of the failure of mitigation efforts. These ordinal constraints are unaffected by subjective or cultural risk-perception factors, they are independent of the discount rate, and they are independent of the magnitude of the estimate for climate sensitivity. The constraints mean that any appeal to uncertainty must imply a stronger, rather than weaker, need to cut greenhouse gas emissions than in the absence of uncertainty.
Understanding Interest Rate Volatility
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...
Assessing flood forecast uncertainty with fuzzy arithmetic
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 uncertainties in the calibration of radiation personal monitor with Cesium-137 source
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)
Uncertainty in adaptive capacity
Neil Adger, W.; Vincent, K.
2005-01-01
The capacity to adapt is a critical element of the process of adaptation: it is the vector of resources that represent the asset base from which adaptation actions can be made. Adaptive capacity can in theory be identified and measured at various scales, from the individual to the nation. The assessment of uncertainty within such measures comes from the contested knowledge domain and theories surrounding the nature of the determinants of adaptive capacity and the human action of adaptation. While generic adaptive capacity at the national level, for example, is often postulated as being dependent on health, governance and political rights, and literacy, and economic well-being, the determinants of these variables at national levels are not widely understood. We outline the nature of this uncertainty for the major elements of adaptive capacity and illustrate these issues with the example of a social vulnerability index for countries in Africa. (authors)
Laval, Katia; Laval, Guy
2013-01-01
Like meteorology, climatology is not an exact science: climate change forecasts necessarily include a share of uncertainty. It is precisely this uncertainty which is brandished and exploited by the opponents to the global warming theory to put into question the estimations of its future consequences. Is it legitimate to predict the future using the past climate data (well documented up to 100000 years BP) or the climates of other planets, taking into account the impreciseness of the measurements and the intrinsic complexity of the Earth's machinery? How is it possible to model a so huge and interwoven system for which any exact description has become impossible? Why water and precipitations play such an important role in local and global forecasts, and how should they be treated? This book written by two physicists answers with simpleness these delicate questions in order to give anyone the possibility to build his own opinion about global warming and the need to act rapidly
Martens, Hans.
1991-01-01
The subject of this thesis is the uncertainty principle (UP). The UP is one of the most characteristic points of differences between quantum and classical mechanics. The starting point of this thesis is the work of Niels Bohr. Besides the discussion the work is also analyzed. For the discussion of the different aspects of the UP the formalism of Davies and Ludwig is used instead of the more commonly used formalism of Neumann and Dirac. (author). 214 refs.; 23 figs
Uncertainty in artificial intelligence
Shachter, RD; Henrion, M; Lemmer, JF
1990-01-01
This volume, like its predecessors, reflects the cutting edge of research on the automation of reasoning under uncertainty.A more pragmatic emphasis is evident, for although some papers address fundamental issues, the majority address practical issues. Topics include the relations between alternative formalisms (including possibilistic reasoning), Dempster-Shafer belief functions, non-monotonic reasoning, Bayesian and decision theoretic schemes, and new inference techniques for belief nets. New techniques are applied to important problems in medicine, vision, robotics, and natural language und
Decision Making Under Uncertainty
2010-11-01
A sound approach to rational decision making requires a decision maker to establish decision objectives, identify alternatives, and evaluate those...often violate the axioms of rationality when making decisions under uncertainty. The systematic description of such observations may lead to the...which leads to “anchoring” on the initial value. The fact that individuals have been shown to deviate from rationality when making decisions
Economic uncertainty principle?
Alexander Harin
2006-01-01
The economic principle of (hidden) uncertainty is presented. New probability formulas are offered. Examples of solutions of three types of fundamental problems are reviewed.; Principe d'incertitude économique? Le principe économique d'incertitude (cachée) est présenté. De nouvelles formules de chances sont offertes. Les exemples de solutions des trois types de problèmes fondamentaux sont reconsidérés.
Citizen Candidates Under Uncertainty
Eguia, Jon X.
2005-01-01
In this paper we make two contributions to the growing literature on "citizen-candidate" models of representative democracy. First, we add uncertainty about the total vote count. We show that in a society with a large electorate, where the outcome of the election is uncertain and where winning candidates receive a large reward from holding office, there will be a two-candidate equilibrium and no equilibria with a single candidate. Second, we introduce a new concept of equilibrium, which we te...
Calibration Under Uncertainty.
Swiler, Laura Painton; Trucano, Timothy Guy
2005-03-01
This report is a white paper summarizing the literature and different approaches to the problem of calibrating computer model parameters in the face of model uncertainty. Model calibration is often formulated as finding the parameters that minimize the squared difference between the model-computed data (the predicted data) and the actual experimental data. This approach does not allow for explicit treatment of uncertainty or error in the model itself: the model is considered the %22true%22 deterministic representation of reality. While this approach does have utility, it is far from an accurate mathematical treatment of the true model calibration problem in which both the computed data and experimental data have error bars. This year, we examined methods to perform calibration accounting for the error in both the computer model and the data, as well as improving our understanding of its meaning for model predictability. We call this approach Calibration under Uncertainty (CUU). This talk presents our current thinking on CUU. We outline some current approaches in the literature, and discuss the Bayesian approach to CUU in detail.
Participation under Uncertainty
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 analysis techniques
Marivoet, J.; Saltelli, A.; Cadelli, N.
1987-01-01
The origin of the uncertainty affecting Performance Assessments, as well as their propagation to dose and risk results is discussed. The analysis is focused essentially on the uncertainties introduced by the input parameters, the values of which may range over some orders of magnitude and may be given as probability distribution function. The paper briefly reviews the existing sampling techniques used for Monte Carlo simulations and the methods for characterizing the output curves, determining their convergence and confidence limits. Annual doses, expectation values of the doses and risks are computed for a particular case of a possible repository in clay, in order to illustrate the significance of such output characteristics as the mean, the logarithmic mean and the median as well as their ratios. The report concludes that provisionally, due to its better robustness, such estimation as the 90th percentile may be substituted to the arithmetic mean for comparison of the estimated doses with acceptance criteria. In any case, the results obtained through Uncertainty Analyses must be interpreted with caution as long as input data distribution functions are not derived from experiments reasonably reproducing the situation in a well characterized repository and site
Corporate income taxation uncertainty and foreign direct investment
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...
Methodologies of Uncertainty Propagation Calculation
Chojnacki, Eric
2002-01-01
After recalling the theoretical principle and the practical difficulties of the methodologies of uncertainty propagation calculation, the author discussed how to propagate input uncertainties. He said there were two kinds of input uncertainty: - variability: uncertainty due to heterogeneity, - lack of knowledge: uncertainty due to ignorance. It was therefore necessary to use two different propagation methods. He demonstrated this in a simple example which he generalised, treating the variability uncertainty by the probability theory and the lack of knowledge uncertainty by the fuzzy theory. He cautioned, however, against the systematic use of probability theory which may lead to unjustifiable and illegitimate precise answers. Mr Chojnacki's conclusions were that the importance of distinguishing variability and lack of knowledge increased as the problem was getting more and more complex in terms of number of parameters or time steps, and that it was necessary to develop uncertainty propagation methodologies combining probability theory and fuzzy theory
LOFT uncertainty-analysis methodology
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
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
Uncertainty in Forest Net Present Value Estimations
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
Monte Carlo eigenfunction strategies and uncertainties
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.)
Do Orthopaedic Surgeons Acknowledge Uncertainty?
Teunis, Teun; Janssen, Stein; Guitton, Thierry G.; Ring, David; Parisien, Robert
2016-01-01
Much of the decision-making in orthopaedics rests on uncertain evidence. Uncertainty is therefore part of our normal daily practice, and yet physician uncertainty regarding treatment could diminish patients' health. It is not known if physician uncertainty is a function of the evidence alone or if
Uncertainties in the Anti-neutrino Production at Nuclear Reactors
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.
Greasley, David; Madsen, Jakob B.
2006-01-01
A severe collapse of fixed capital formation distinguished the onset of the Great Depression from other investment downturns between the world wars. Using a model estimated for the years 1890-2000, we show that the expected profitability of capital measured by Tobin's q, and the uncertainty...... surrounding expected profits indicated by share price volatility, were the chief influences on investment levels, and that heightened share price volatility played the dominant role in the crucial investment collapse in 1930. Investment did not simply follow the downward course of income at the onset...
Optimization under Uncertainty
Lopez, Rafael H.
2016-01-06
The goal of this poster is to present the main approaches to optimization of engineering systems in the presence of uncertainties. We begin by giving an insight about robust optimization. Next, we detail how to deal with probabilistic constraints in optimization, the so called the reliability based design. Subsequently, we present the risk optimization approach, which includes the expected costs of failure in the objective function. After that the basic description of each approach is given, the projects developed by CORE are presented. Finally, the main current topic of research of CORE is described.
Optimizing production under uncertainty
Rasmussen, Svend
This Working Paper derives criteria for optimal production under uncertainty based on the state-contingent approach (Chambers and Quiggin, 2000), and discusses po-tential problems involved in applying the state-contingent approach in a normative context. The analytical approach uses the concept...... of state-contingent production functions and a definition of inputs including both sort of input, activity and alloca-tion technology. It also analyses production decisions where production is combined with trading in state-contingent claims such as insurance contracts. The final part discusses...
Commonplaces and social uncertainty
Lassen, Inger
2008-01-01
This article explores the concept of uncertainty in four focus group discussions about genetically modified food. In the discussions, members of the general public interact with food biotechnology scientists while negotiating their attitudes towards genetic engineering. Their discussions offer...... an example of risk discourse in which the use of commonplaces seems to be a central feature (Myers 2004: 81). My analyses support earlier findings that commonplaces serve important interactional purposes (Barton 1999) and that they are used for mitigating disagreement, for closing topics and for facilitating...
Kadane, Joseph B
2011-01-01
An intuitive and mathematical introduction to subjective probability and Bayesian statistics. An accessible, comprehensive guide to the theory of Bayesian statistics, Principles of Uncertainty presents the subjective Bayesian approach, which has played a pivotal role in game theory, economics, and the recent boom in Markov Chain Monte Carlo methods. Both rigorous and friendly, the book contains: Introductory chapters examining each new concept or assumption Just-in-time mathematics -- the presentation of ideas just before they are applied Summary and exercises at the end of each chapter Discus
Mathematical Analysis of Uncertainty
Angel GARRIDO
2016-01-01
Full Text Available Classical Logic showed early its insufficiencies for solving AI problems. The introduction of Fuzzy Logic aims at this problem. There have been research in the conventional Rough direction alone or in the Fuzzy direction alone, and more recently, attempts to combine both into Fuzzy Rough Sets or Rough Fuzzy Sets. We analyse some new and powerful tools in the study of Uncertainty, as the Probabilistic Graphical Models, Chain Graphs, Bayesian Networks, and Markov Networks, integrating our knowledge of graphs and probability.
Uncertainty in reactive transport geochemical modelling
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)
Capital flight and the uncertainty of government policies
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
An evaluation of uncertainties in radioecological models
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
Investment, regulation, and uncertainty
Smyth, Stuart J; McDonald, Jillian; Falck-Zepeda, Jose
2014-01-01
As with any technological innovation, time refines the technology, improving upon the original version of the innovative product. The initial GM crops had single traits for either herbicide tolerance or insect resistance. Current varieties have both of these traits stacked together and in many cases other abiotic and biotic traits have also been stacked. This innovation requires investment. While this is relatively straight forward, certain conditions need to exist such that investments can be facilitated. The principle requirement for investment is that regulatory frameworks render consistent and timely decisions. If the certainty of regulatory outcomes weakens, the potential for changes in investment patterns increases. This article provides a summary background to the leading plant breeding technologies that are either currently being used to develop new crop varieties or are in the pipeline to be applied to plant breeding within the next few years. Challenges for existing regulatory systems are highlighted. Utilizing an option value approach from investment literature, an assessment of uncertainty regarding the regulatory approval for these varying techniques is undertaken. This research highlights which technology development options have the greatest degree of uncertainty and hence, which ones might be expected to see an investment decline. PMID:24499745
Probabilistic Mass Growth Uncertainties
Plumer, Eric; Elliott, Darren
2013-01-01
Mass has been widely used as a variable input parameter for Cost Estimating Relationships (CER) for space systems. As these space systems progress from early concept studies and drawing boards to the launch pad, their masses tend to grow substantially, hence adversely affecting a primary input to most modeling CERs. Modeling and predicting mass uncertainty, based on historical and analogous data, is therefore critical and is an integral part of modeling cost risk. This paper presents the results of a NASA on-going effort to publish mass growth datasheet for adjusting single-point Technical Baseline Estimates (TBE) of masses of space instruments as well as spacecraft, for both earth orbiting and deep space missions at various stages of a project's lifecycle. This paper will also discusses the long term strategy of NASA Headquarters in publishing similar results, using a variety of cost driving metrics, on an annual basis. This paper provides quantitative results that show decreasing mass growth uncertainties as mass estimate maturity increases. This paper's analysis is based on historical data obtained from the NASA Cost Analysis Data Requirements (CADRe) database.
Embracing uncertainty in applied ecology.
Milner-Gulland, E J; Shea, K
2017-12-01
Applied ecologists often face uncertainty that hinders effective decision-making.Common traps that may catch the unwary are: ignoring uncertainty, acknowledging uncertainty but ploughing on, focussing on trivial uncertainties, believing your models, and unclear objectives.We integrate research insights and examples from a wide range of applied ecological fields to illustrate advances that are generally underused, but could facilitate ecologists' ability to plan and execute research to support management.Recommended approaches to avoid uncertainty traps are: embracing models, using decision theory, using models more effectively, thinking experimentally, and being realistic about uncertainty. Synthesis and applications . Applied ecologists can become more effective at informing management by using approaches that explicitly take account of uncertainty.
Oil price uncertainty in Canada
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 margins and uncertainties: Alternative representations of epistemic uncertainty
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.
The cost of uncertainty in capacity expansion problems
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)
Heisenberg's principle of uncertainty and the uncertainty relations
Redei, Miklos
1987-01-01
The usual verbal form of the Heisenberg uncertainty principle and the usual mathematical formulation (the so-called uncertainty theorem) are not equivalent. The meaning of the concept 'uncertainty' is not unambiguous and different interpretations are used in the literature. Recently a renewed interest has appeared to reinterpret and reformulate the precise meaning of Heisenberg's principle and to find adequate mathematical form. The suggested new theorems are surveyed and critically analyzed. (D.Gy.) 20 refs
Petzinger, Tom
I am trying to make money in the biotech industry from complexity science. And I am doing it with inspiration that I picked up on the edge of Appalachia spending time with June Holley and ACEnet when I was a Wall Street Journal reporter. I took some of those ideas to Pittsburgh, in biotechnology, in a completely private setting with an economic development focus, but also with a mission t o return profit to private capital. And we are doing that. I submit as a hypothesis, something we are figuring out in the post- industrial era, that business evolves. It is not the definition of business, but business critically involves the design of systems in which uncertainty is treated as a certainty. That is what I have seen and what I have tried to put into practice.
Peters, H.P.; Hennen, L.
1990-01-01
The authors report on the results of three representative surveys that made a closer inquiry into perceptions and valuations of information and information sources concering Chernobyl. If turns out that the information sources are generally considered little trustworthy. This was generally attributable to the interpretation of the events being tied to attitudes in the atmonic energy issue. The greatest credit was given to television broadcasting. The authors summarize their discourse as follows: There is good reason to interpret the widespread uncertainty after Chernobyl as proof of the fact that large parts of the population are prepared and willing to assume a critical stance towards information and prefer to draw their information from various sources representing different positions. (orig.) [de
2012-03-01
ISO / IEC 17025 Inspection Bodies – ISO / IEC 17020 RMPs – ISO Guide 34 (Reference...certify to : ISO 9001 (QMS), ISO 14001 (EMS), TS 16949 (US Automotive) etc. 2 3 DoD QSM 4.2 standard ISO / IEC 17025 :2005 Each has uncertainty...IPV6, NLLAP, NEFAP TRAINING Programs Certification Bodies – ISO / IEC 17021 Accreditation for Management System
Traceability and Measurement Uncertainty
Tosello, Guido; De Chiffre, Leonardo
2004-01-01
. The project partnership aims (composed by 7 partners in 5 countries, thus covering a real European spread in high tech production technology) to develop and implement an advanced e-learning system that integrates contributions from quite different disciplines into a user-centred approach that strictly....... Machine tool testing 9. The role of manufacturing metrology for QM 10. Inspection planning 11. Quality management of measurements incl. Documentation 12. Advanced manufacturing measurement technology The present report (which represents the section 2 - Traceability and Measurement Uncertainty – of the e-learning......This report is made as a part of the project ‘Metro-E-Learn: European e-Learning in Manufacturing Metrology’, an EU project under the program SOCRATES MINERVA (ODL and ICT in Education), Contract No: 101434-CP-1-2002-1-DE-MINERVA, coordinated by Friedrich-Alexander-University Erlangen...
Sustainability and uncertainty
Jensen, Karsten Klint
2007-01-01
The widely used concept of sustainability is seldom precisely defined, and its clarification involves making up one's mind about a range of difficult questions. One line of research (bottom-up) takes sustaining a system over time as its starting point and then infers prescriptions from...... this requirement. Another line (top-down) takes an economical interpretation of the Brundtland Commission's suggestion that the present generation's needsatisfaction should not compromise the need-satisfaction of future generations as its starting point. It then measures sustainability at the level of society...... a clarified ethical goal, disagreements can arise. At present we do not know what substitutions will be possible in the future. This uncertainty clearly affects the prescriptions that follow from the measure of sustainability. Consequently, decisions about how to make future agriculture sustainable...
An uncertainty inventory demonstration - a primary step in uncertainty quantification
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.
Essays on model uncertainty in financial models
Li, Jing
2018-01-01
This dissertation studies model uncertainty, particularly in financial models. It consists of two empirical chapters and one theoretical chapter. The first empirical chapter (Chapter 2) classifies model uncertainty into parameter uncertainty and misspecification uncertainty. It investigates the
A new uncertainty importance measure
Borgonovo, E.
2007-01-01
Uncertainty in parameters is present in many risk assessment problems and leads to uncertainty in model predictions. In this work, we introduce a global sensitivity indicator which looks at the influence of input uncertainty on the entire output distribution without reference to a specific moment of the output (moment independence) and which can be defined also in the presence of correlations among the parameters. We discuss its mathematical properties and highlight the differences between the present indicator, variance-based uncertainty importance measures and a moment independent sensitivity indicator previously introduced in the literature. Numerical results are discussed with application to the probabilistic risk assessment model on which Iman [A matrix-based approach to uncertainty and sensitivity analysis for fault trees. Risk Anal 1987;7(1):22-33] first introduced uncertainty importance measures
Uncertainty Management and Sensitivity Analysis
Rosenbaum, Ralph K.; Georgiadis, Stylianos; Fantke, Peter
2018-01-01
Uncertainty is always there and LCA is no exception to that. The presence of uncertainties of different types and from numerous sources in LCA results is a fact, but managing them allows to quantify and improve the precision of a study and the robustness of its conclusions. LCA practice sometimes...... suffers from an imbalanced perception of uncertainties, justifying modelling choices and omissions. Identifying prevalent misconceptions around uncertainties in LCA is a central goal of this chapter, aiming to establish a positive approach focusing on the advantages of uncertainty management. The main...... objectives of this chapter are to learn how to deal with uncertainty in the context of LCA, how to quantify it, interpret and use it, and how to communicate it. The subject is approached more holistically than just focusing on relevant statistical methods or purely mathematical aspects. This chapter...
Additivity of entropic uncertainty relations
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.
Decommissioning funding: ethics, implementation, uncertainties
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)
Chemical model reduction under uncertainty
Najm, Habib; Galassi, R. Malpica; Valorani, M.
2016-01-01
We outline a strategy for chemical kinetic model reduction under uncertainty. We present highlights of our existing deterministic model reduction strategy, and describe the extension of the formulation to include parametric uncertainty in the detailed mechanism. We discuss the utility of this construction, as applied to hydrocarbon fuel-air kinetics, and the associated use of uncertainty-aware measures of error between predictions from detailed and simplified models.
Chemical model reduction under uncertainty
Najm, Habib
2016-01-05
We outline a strategy for chemical kinetic model reduction under uncertainty. We present highlights of our existing deterministic model reduction strategy, and describe the extension of the formulation to include parametric uncertainty in the detailed mechanism. We discuss the utility of this construction, as applied to hydrocarbon fuel-air kinetics, and the associated use of uncertainty-aware measures of error between predictions from detailed and simplified models.
The Uncertainty of Measurement Results
Ambrus, A. [Hungarian Food Safety Office, Budapest (Hungary)
2009-07-15
Factors affecting the uncertainty of measurement are explained, basic statistical formulae given, and the theoretical concept explained in the context of pesticide formulation analysis. Practical guidance is provided on how to determine individual uncertainty components within an analytical procedure. An extended and comprehensive table containing the relevant mathematical/statistical expressions elucidates the relevant underlying principles. Appendix I provides a practical elaborated example on measurement uncertainty estimation, above all utilizing experimental repeatability and reproducibility laboratory data. (author)
Uncertainty analysis of environmental models
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
Uncertainty quantification in resonance absorption
Williams, M.M.R.
2012-01-01
We assess the uncertainty in the resonance escape probability due to uncertainty in the neutron and radiation line widths for the first 21 resonances in 232 Th as given by . Simulation, quadrature and polynomial chaos methods are used and the resonance data are assumed to obey a beta distribution. We find the uncertainty in the total resonance escape probability to be the equivalent, in reactivity, of 75–130 pcm. Also shown are pdfs of the resonance escape probability for each resonance and the variation of the uncertainty with temperature. The viability of the polynomial chaos expansion method is clearly demonstrated.
Reliability analysis under epistemic uncertainty
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
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
Climate Certainties and Uncertainties
Morel, Pierre
2012-01-01
In issue 380 of Futuribles in December 2011, Antonin Pottier analysed in detail the workings of what is today termed 'climate scepticism' - namely the propensity of certain individuals to contest the reality of climate change on the basis of pseudo-scientific arguments. He emphasized particularly that what fuels the debate on climate change is, largely, the degree of uncertainty inherent in the consequences to be anticipated from observation of the facts, not the description of the facts itself. In his view, the main aim of climate sceptics is to block the political measures for combating climate change. However, since they do not admit to this political posture, they choose instead to deny the scientific reality. This month, Futuribles complements this socio-psychological analysis of climate-sceptical discourse with an - in this case, wholly scientific - analysis of what we know (or do not know) about climate change on our planet. Pierre Morel gives a detailed account of the state of our knowledge in the climate field and what we are able to predict in the medium/long-term. After reminding us of the influence of atmospheric meteorological processes on the climate, he specifies the extent of global warming observed since 1850 and the main origin of that warming, as revealed by the current state of knowledge: the increase in the concentration of greenhouse gases. He then describes the changes in meteorological regimes (showing also the limits of climate simulation models), the modifications of hydrological regimes, and also the prospects for rises in sea levels. He also specifies the mechanisms that may potentially amplify all these phenomena and the climate disasters that might ensue. Lastly, he shows what are the scientific data that cannot be disregarded, the consequences of which are now inescapable (melting of the ice-caps, rises in sea level etc.), the only remaining uncertainty in this connection being the date at which these things will happen. 'In this
Sketching Uncertainty into Simulations.
Ribicic, H; Waser, J; Gurbat, R; Sadransky, B; Groller, M E
2012-12-01
In a variety of application areas, the use of simulation steering in decision making is limited at best. Research focusing on this problem suggests that most user interfaces are too complex for the end user. Our goal is to let users create and investigate multiple, alternative scenarios without the need for special simulation expertise. To simplify the specification of parameters, we move from a traditional manipulation of numbers to a sketch-based input approach. Users steer both numeric parameters and parameters with a spatial correspondence by sketching a change onto the rendering. Special visualizations provide immediate visual feedback on how the sketches are transformed into boundary conditions of the simulation models. Since uncertainty with respect to many intertwined parameters plays an important role in planning, we also allow the user to intuitively setup complete value ranges, which are then automatically transformed into ensemble simulations. The interface and the underlying system were developed in collaboration with experts in the field of flood management. The real-world data they have provided has allowed us to construct scenarios used to evaluate the system. These were presented to a variety of flood response personnel, and their feedback is discussed in detail in the paper. The interface was found to be intuitive and relevant, although a certain amount of training might be necessary.
Uncertainty vs. Information (Invited)
Nearing, Grey
2017-04-01
Information theory is the branch of logic that describes how rational epistemic states evolve in the presence of empirical data (Knuth, 2005), and any logic of science is incomplete without such a theory. Developing a formal philosophy of science that recognizes this fact results in essentially trivial solutions to several longstanding problems are generally considered intractable, including: • Alleviating the need for any likelihood function or error model. • Derivation of purely logical falsification criteria for hypothesis testing. • Specification of a general quantitative method for process-level model diagnostics. More generally, I make the following arguments: 1. Model evaluation should not proceed by quantifying and/or reducing error or uncertainty, and instead should be approached as a problem of ensuring that our models contain as much information as our experimental data. I propose that the latter is the only question a scientist actually has the ability to ask. 2. Instead of building geophysical models as solutions to differential equations that represent conservation laws, we should build models as maximum entropy distributions constrained by conservation symmetries. This will allow us to derive predictive probabilities directly from first principles. Knuth, K. H. (2005) 'Lattice duality: The origin of probability and entropy', Neurocomputing, 67, pp. 245-274.
Pandemic influenza: certain uncertainties
Morens, David M.; Taubenberger, Jeffery K.
2011-01-01
SUMMARY For at least five centuries, major epidemics and pandemics of influenza have occurred unexpectedly and at irregular intervals. Despite the modern notion that pandemic influenza is a distinct phenomenon obeying such constant (if incompletely understood) rules such as dramatic genetic change, cyclicity, “wave” patterning, virus replacement, and predictable epidemic behavior, much evidence suggests the opposite. Although there is much that we know about pandemic influenza, there appears to be much more that we do not know. Pandemics arise as a result of various genetic mechanisms, have no predictable patterns of mortality among different age groups, and vary greatly in how and when they arise and recur. Some are followed by new pandemics, whereas others fade gradually or abruptly into long-term endemicity. Human influenza pandemics have been caused by viruses that evolved singly or in co-circulation with other pandemic virus descendants and often have involved significant transmission between, or establishment of, viral reservoirs within other animal hosts. In recent decades, pandemic influenza has continued to produce numerous unanticipated events that expose fundamental gaps in scientific knowledge. Influenza pandemics appear to be not a single phenomenon but a heterogeneous collection of viral evolutionary events whose similarities are overshadowed by important differences, the determinants of which remain poorly understood. These uncertainties make it difficult to predict influenza pandemics and, therefore, to adequately plan to prevent them. PMID:21706672
Maugis, Pierre-André G
2018-07-01
Big data-the idea that an always-larger volume of information is being constantly recorded-suggests that new problems can now be subjected to scientific scrutiny. However, can classical statistical methods be used directly on big data? We analyze the problem by looking at two known pitfalls of big datasets. First, that they are biased, in the sense that they do not offer a complete view of the populations under consideration. Second, that they present a weak but pervasive level of dependence between all their components. In both cases we observe that the uncertainty of the conclusion obtained by statistical methods is increased when used on big data, either because of a systematic error (bias), or because of a larger degree of randomness (increased variance). We argue that the key challenge raised by big data is not only how to use big data to tackle new problems, but to develop tools and methods able to rigorously articulate the new risks therein. Copyright © 2016. Published by Elsevier Ltd.
Uncertainty enabled Sensor Observation Services
Cornford, Dan; Williams, Matthew; Bastin, Lucy
2010-05-01
Almost all observations of reality are contaminated with errors, which introduce uncertainties into the actual observation result. Such uncertainty is often held to be a data quality issue, and quantification of this uncertainty is essential for the principled exploitation of the observations. Many existing systems treat data quality in a relatively ad-hoc manner, however if the observation uncertainty is a reliable estimate of the error on the observation with respect to reality then knowledge of this uncertainty enables optimal exploitation of the observations in further processes, or decision making. We would argue that the most natural formalism for expressing uncertainty is Bayesian probability theory. In this work we show how the Open Geospatial Consortium Sensor Observation Service can be implemented to enable the support of explicit uncertainty about observations. We show how the UncertML candidate standard is used to provide a rich and flexible representation of uncertainty in this context. We illustrate this on a data set of user contributed weather data where the INTAMAP interpolation Web Processing Service is used to help estimate the uncertainty on the observations of unknown quality, using observations with known uncertainty properties. We then go on to discuss the implications of uncertainty for a range of existing Open Geospatial Consortium standards including SWE common and Observations and Measurements. We discuss the difficult decisions in the design of the UncertML schema and its relation and usage within existing standards and show various options. We conclude with some indications of the likely future directions for UncertML in the context of Open Geospatial Consortium services.
A commentary on model uncertainty
Apostolakis, G.
1994-01-01
A framework is proposed for the identification of model and parameter uncertainties in risk assessment models. Two cases are distinguished; in the first case, a set of mutually exclusive and exhaustive hypotheses (models) can be formulated, while, in the second, only one reference model is available. The relevance of this formulation to decision making and the communication of uncertainties is discussed
Mama Software Features: Uncertainty Testing
Ruggiero, Christy E. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Porter, Reid B. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2014-05-30
This document reviews how the uncertainty in the calculations is being determined with test image data. The results of this testing give an ‘initial uncertainty’ number than can be used to estimate the ‘back end’ uncertainty in digital image quantification in images. Statisticians are refining these numbers as part of a UQ effort.
Designing for Uncertainty: Three Approaches
Bennett, Scott
2007-01-01
Higher education wishes to get long life and good returns on its investment in learning spaces. Doing this has become difficult because rapid changes in information technology have created fundamental uncertainties about the future in which capital investments must deliver value. Three approaches to designing for this uncertainty are described…
Uncertainties in container failure time predictions
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
Uncertainty Evaluation of Best Estimate Calculation Results
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)
Nuclear Physical Uncertainties in Modeling X-Ray Bursts
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.
Impact of dose-distribution uncertainties on rectal ntcp modeling I: Uncertainty estimates
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
Uncertainties in Nuclear Proliferation Modeling
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
Measurement uncertainty: Friend or foe?
Infusino, Ilenia; Panteghini, Mauro
2018-02-02
The definition and enforcement of a reference measurement system, based on the implementation of metrological traceability of patients' results to higher order reference methods and materials, together with a clinically acceptable level of measurement uncertainty, are fundamental requirements to produce accurate and equivalent laboratory results. The uncertainty associated with each step of the traceability chain should be governed to obtain a final combined uncertainty on clinical samples fulfilling the requested performance specifications. It is important that end-users (i.e., clinical laboratory) may know and verify how in vitro diagnostics (IVD) manufacturers have implemented the traceability of their calibrators and estimated the corresponding uncertainty. However, full information about traceability and combined uncertainty of calibrators is currently very difficult to obtain. Laboratory professionals should investigate the need to reduce the uncertainty of the higher order metrological references and/or to increase the precision of commercial measuring systems. Accordingly, the measurement uncertainty should not be considered a parameter to be calculated by clinical laboratories just to fulfil the accreditation standards, but it must become a key quality indicator to describe both the performance of an IVD measuring system and the laboratory itself. Copyright © 2018 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.
Model uncertainty in safety assessment
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
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.).
Managing Uncertainty for an Integrated Fishery
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.
Assessing uncertainty and risk in exploited marine populations
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
Model uncertainty: Probabilities for models?
Winkler, R.L.
1994-01-01
Like any other type of uncertainty, model uncertainty should be treated in terms of probabilities. The question is how to do this. The most commonly-used approach has a drawback related to the interpretation of the probabilities assigned to the models. If we step back and look at the big picture, asking what the appropriate focus of the model uncertainty question should be in the context of risk and decision analysis, we see that a different probabilistic approach makes more sense, although it raise some implementation questions. Current work that is underway to address these questions looks very promising
Uncertainties related to the fault tree reliability data
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
Parametric uncertainty modeling for robust control
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...
Decision-making under great uncertainty
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)
Structural and parameteric uncertainty quantification in cloud microphysics parameterization schemes
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.
Evaluation of uncertainty and detection limits in radioactivity measurements
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
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
Uncertainty analysis of power monitoring transit time ultrasonic flow meters
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)
Macro Expectations, Aggregate Uncertainty, and Expected Term Premia
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...
Application of uncertainty analysis in conceptual fusion reactor design
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
The Uncertainties of Risk Management
Vinnari, Eija; Skærbæk, Peter
2014-01-01
for expanding risk management. More generally, such uncertainties relate to the professional identities and responsibilities of operational managers as defined by the framing devices. Originality/value – The paper offers three contributions to the extant literature: first, it shows how risk management itself......Purpose – The purpose of this paper is to analyse the implementation of risk management as a tool for internal audit activities, focusing on unexpected effects or uncertainties generated during its application. Design/methodology/approach – Public and confidential documents as well as semi......-structured interviews are analysed through the lens of actor-network theory to identify the effects of risk management devices in a Finnish municipality. Findings – The authors found that risk management, rather than reducing uncertainty, itself created unexpected uncertainties that would otherwise not have emerged...
Climate Projections and Uncertainty Communication.
Joslyn, Susan L; LeClerc, Jared E
2016-01-01
Lingering skepticism about climate change might be due in part to the way climate projections are perceived by members of the public. Variability between scientists' estimates might give the impression that scientists disagree about the fact of climate change rather than about details concerning the extent or timing. Providing uncertainty estimates might clarify that the variability is due in part to quantifiable uncertainty inherent in the prediction process, thereby increasing people's trust in climate projections. This hypothesis was tested in two experiments. Results suggest that including uncertainty estimates along with climate projections leads to an increase in participants' trust in the information. Analyses explored the roles of time, place, demographic differences (e.g., age, gender, education level, political party affiliation), and initial belief in climate change. Implications are discussed in terms of the potential benefit of adding uncertainty estimates to public climate projections. Copyright © 2015 Cognitive Science Society, Inc.
Relational uncertainty in service dyads
Kreye, Melanie
2017-01-01
in service dyads and how they resolve it through suitable organisational responses to increase the level of service quality. Design/methodology/approach: We apply the overall logic of Organisational Information-Processing Theory (OIPT) and present empirical insights from two industrial case studies collected...... the relational uncertainty increased the functional quality while resolving the partner’s organisational uncertainty increased the technical quality of the delivered service. Originality: We make two contributions. First, we introduce relational uncertainty to the OM literature as the inability to predict...... and explain the actions of a partnering organisation due to a lack of knowledge about their abilities and intentions. Second, we present suitable organisational responses to relational uncertainty and their effect on service quality....
Advanced LOCA code uncertainty assessment
Wickett, A.J.; Neill, A.P.
1990-11-01
This report describes a pilot study that identified, quantified and combined uncertainties for the LOBI BL-02 3% small break test. A ''dials'' version of TRAC-PF1/MOD1, called TRAC-F, was used. (author)
How to live with uncertainties?
Michel, R.
2012-01-01
In a short introduction, the problem of uncertainty as a general consequence of incomplete information as well as the approach to quantify uncertainty in metrology are addressed. A little history of the more than 30 years of the working group AK SIGMA is followed by an appraisal of its up-to-now achievements. Then, the potential future of the AK SIGMA is discussed based on its actual tasks and on open scientific questions and future topics. (orig.)
Some remarks on modeling uncertainties
Ronen, Y.
1983-01-01
Several topics related to the question of modeling uncertainties are considered. The first topic is related to the use of the generalized bias operator method for modeling uncertainties. The method is expanded to a more general form of operators. The generalized bias operator is also used in the inverse problem and applied to determine the anisotropic scattering law. The last topic discussed is related to the question of the limit to accuracy and how to establish its value. (orig.) [de
Uncertainty analysis in safety assessment
Lemos, Francisco Luiz de; Sullivan, Terry
1997-01-01
Nuclear waste disposal is a very complex subject which requires the study of many different fields of science, like hydro geology, meteorology, geochemistry, etc. In addition, the waste disposal facilities are designed to last for a very long period of time. Both of these conditions make safety assessment projections filled with uncertainty. This paper addresses approaches for treatment of uncertainties in the safety assessment modeling due to the variability of data and some current approaches used to deal with this problem. (author)
Propagation of dynamic measurement uncertainty
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
Optimal Taxation under Income Uncertainty
Xianhua Dai
2011-01-01
Optimal taxation under income uncertainty has been extensively developed in expected utility theory, but it is still open for inseparable utility function between income and effort. As an alternative of decision-making under uncertainty, prospect theory (Kahneman and Tversky (1979), Tversky and Kahneman (1992)) has been obtained empirical support, for example, Kahneman and Tversky (1979), and Camerer and Lowenstein (2003). It is beginning to explore optimal taxation in the context of prospect...
New Perspectives on Policy Uncertainty
Hlatshwayo, Sandile
2017-01-01
In recent years, the ubiquitous and intensifying nature of economic policy uncertainty has made it a popular explanation for weak economic performance in developed and developing markets alike. The primary channel for this effect is decreased and delayed investment as firms adopt a ``wait and see'' approach to irreversible investments (Bernanke, 1983; Dixit and Pindyck, 1994). Deep empirical examination of policy uncertainty's impact is rare because of the difficulty associated in measuring i...
Pharmacological Fingerprints of Contextual Uncertainty.
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.
Zhang, W.; Zaehringer, M.; Ungar, K.; Hoffman, I.
2008-01-01
In this paper, the uncertainties of gamma-ray small peak analysis have been examined. As the intensity of a gamma-ray peak approaches its detection decision limit, derived parameters such as centroid channel energy, peak area, peak area uncertainty, baseline determination, and peak significance are statistically sensitive. The intercomparison exercise organized by the CTBTO provided an excellent opportunity for this to be studied. Near background levels, the false-positive and false-negative peak identification frequencies in artificial test spectra have been compared to statistically predictable limiting values. In addition, naturally occurring radon progeny were used to compare observed variance against nominal uncertainties. The results infer that the applied fit algorithms do not always represent the best estimator. Understanding the statistically predicted peak-finding limit is important for data evaluation and analysis assessment. Furthermore, these results are useful to optimize analytical procedures to achieve the best results
A Bayesian approach to model uncertainty
Buslik, A.
1994-01-01
A Bayesian approach to model uncertainty is taken. For the case of a finite number of alternative models, the model uncertainty is equivalent to parameter uncertainty. A derivation based on Savage's partition problem is given
The NASA Langley Multidisciplinary Uncertainty Quantification Challenge
Crespo, Luis G.; Kenny, Sean P.; Giesy, Daniel P.
2014-01-01
This paper presents the formulation of an uncertainty quantification challenge problem consisting of five subproblems. These problems focus on key aspects of uncertainty characterization, sensitivity analysis, uncertainty propagation, extreme-case analysis, and robust design.
Do Orthopaedic Surgeons Acknowledge Uncertainty?
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
RUMINATIONS ON NDA MEASUREMENT UNCERTAINTY COMPARED TO DA UNCERTAINTY
Salaymeh, S.; Ashley, W.; Jeffcoat, R.
2010-06-17
It is difficult to overestimate the importance that physical measurements performed with nondestructive assay instruments play throughout the nuclear fuel cycle. They underpin decision making in many areas and support: criticality safety, radiation protection, process control, safeguards, facility compliance, and waste measurements. No physical measurement is complete or indeed meaningful, without a defensible and appropriate accompanying statement of uncertainties and how they combine to define the confidence in the results. The uncertainty budget should also be broken down in sufficient detail suitable for subsequent uses to which the nondestructive assay (NDA) results will be applied. Creating an uncertainty budget and estimating the total measurement uncertainty can often be an involved process, especially for non routine situations. This is because data interpretation often involves complex algorithms and logic combined in a highly intertwined way. The methods often call on a multitude of input data subject to human oversight. These characteristics can be confusing and pose a barrier to developing and understanding between experts and data consumers. ASTM subcommittee C26-10 recognized this problem in the context of how to summarize and express precision and bias performance across the range of standards and guides it maintains. In order to create a unified approach consistent with modern practice and embracing the continuous improvement philosophy a consensus arose to prepare a procedure covering the estimation and reporting of uncertainties in non destructive assay of nuclear materials. This paper outlines the needs analysis, objectives and on-going development efforts. In addition to emphasizing some of the unique challenges and opportunities facing the NDA community we hope this article will encourage dialog and sharing of best practice and furthermore motivate developers to revisit the treatment of measurement uncertainty.
Ruminations On NDA Measurement Uncertainty Compared TO DA Uncertainty
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.
Understanding Interest Rate Volatility
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...
Critical loads - assessment of uncertainty
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
Subspace-based Inverse Uncertainty Quantification for Nuclear Data Assessment
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 Quantification in Numerical Aerodynamics
Litvinenko, Alexander
2017-05-16
We consider uncertainty quantification problem in aerodynamic simulations. We identify input uncertainties, classify them, suggest an appropriate statistical model and, finally, estimate propagation of these uncertainties into the solution (pressure, velocity and density fields as well as the lift and drag coefficients). The deterministic problem under consideration is a compressible transonic Reynolds-averaged Navier-Strokes flow around an airfoil with random/uncertain data. Input uncertainties include: uncertain angle of attack, the Mach number, random perturbations in the airfoil geometry, mesh, shock location, turbulence model and parameters of this turbulence model. This problem requires efficient numerical/statistical methods since it is computationally expensive, especially for the uncertainties caused by random geometry variations which involve a large number of variables. In numerical section we compares five methods, including quasi-Monte Carlo quadrature, polynomial chaos with coefficients determined by sparse quadrature and gradient-enhanced version of Kriging, radial basis functions and point collocation polynomial chaos, in their efficiency in estimating statistics of aerodynamic performance upon random perturbation to the airfoil geometry [D.Liu et al \\'17]. For modeling we used the TAU code, developed in DLR, Germany.
Uncertainty in spatial planning proceedings
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.
Uncertainty modeling and decision support
Yager, Ronald R.
2004-01-01
We first formulate the problem of decision making under uncertainty. The importance of the representation of our knowledge about the uncertainty in formulating a decision process is pointed out. We begin with a brief discussion of the case of probabilistic uncertainty. Next, in considerable detail, we discuss the case of decision making under ignorance. For this case the fundamental role of the attitude of the decision maker is noted and its subjective nature is emphasized. Next the case in which a Dempster-Shafer belief structure is used to model our knowledge of the uncertainty is considered. Here we also emphasize the subjective choices the decision maker must make in formulating a decision function. The case in which the uncertainty is represented by a fuzzy measure (monotonic set function) is then investigated. We then return to the Dempster-Shafer belief structure and show its relationship to the fuzzy measure. This relationship allows us to get a deeper understanding of the formulation the decision function used Dempster- Shafer framework. We discuss how this deeper understanding allows a decision analyst to better make the subjective choices needed in the formulation of the decision function
Big bang nucleosynthesis - Predictions and uncertainties
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
Uncertainty quantification for PZT bimorph actuators
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.
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...
Theoretical uncertainties of the Type Ia supernova rate
Claeys, J.S.W.; Pols, O.R.; Izzard, R.G.; Vink, J.; Verbunt, F.W.M.
2014-01-01
It is thought that Type Ia supernovae (SNe Ia) are explosions of carbon-oxygen white dwarfs (CO WDs). Two main evolutionary channels are proposed for the WD to reach the critical density required for a thermonuclear explosion: the single degenerate (SD) scenario, in which a CO WD accretes from a
On the uncertainty principle. V
Halpern, O.
1976-01-01
The treatment of ideal experiments connected with the uncertainty principle is continued. The author analyzes successively measurements of momentum and position, and discusses the common reason why the results in all cases differ from the conventional ones. A similar difference exists for the measurement of field strengths. The interpretation given by Weizsaecker, who tried to interpret Bohr's complementarity principle by introducing a multi-valued logic is analyzed. The treatment of the uncertainty principle ΔE Δt is deferred to a later paper as is the interpretation of the method of variation of constants. Every ideal experiment discussed shows various lower limits for the value of the uncertainty product which limits depend on the experimental arrangement and are always (considerably) larger than h. (Auth.)
Davis, C.B.
1987-08-01
The uncertainties of calculations of loss-of-feedwater transients at Davis-Besse Unit 1 were determined to address concerns of the US Nuclear Regulatory Commission relative to the effectiveness of feed and bleed cooling. Davis-Besse Unit 1 is a pressurized water reactor of the raised-loop Babcock and Wilcox design. A detailed, quality-assured RELAP5/MOD2 model of Davis-Besse was developed at the Idaho National Engineering Laboratory. The model was used to perform an analysis of the loss-of-feedwater transient that occurred at Davis-Besse on June 9, 1985. A loss-of-feedwater transient followed by feed and bleed cooling was also calculated. The evaluation of uncertainty was based on the comparisons of calculations and data, comparisons of different calculations of the same transient, sensitivity calculations, and the propagation of the estimated uncertainty in initial and boundary conditions to the final calculated results
Decommissioning Funding: Ethics, Implementation, Uncertainties
2007-01-01
This status report on decommissioning funding: ethics, implementation, uncertainties is based on a review of recent literature and materials presented at NEA meetings in 2003 and 2004, and particularly at a topical session organised in November 2004 on funding issues associated with the decommissioning of nuclear power facilities. The report also draws on the experience of the NEA Working Party on Decommissioning and Dismantling (WPDD). This report offers, in a concise form, an overview of relevant considerations on decommissioning funding mechanisms with regard to ethics, implementation and uncertainties. Underlying ethical principles found in international agreements are identified, and factors influencing the accumulation and management of funds for decommissioning nuclear facilities are discussed together with the main sources of uncertainties of funding systems
Correlated uncertainties in integral data
McCracken, A.K.
1978-01-01
The use of correlated uncertainties in calculational data is shown in cases investigated to lead to a reduction in the uncertainty of calculated quantities of importance to reactor design. It is stressed however that such reductions are likely to be important in a minority of cases of practical interest. The effect of uncertainties in detector cross-sections is considered and is seen to be, in some cases, of equal importance to that in the data used in calculations. Numerical investigations have been limited by the sparse information available on data correlations; some comparisons made of these data reveal quite large inconsistencies for both detector cross-sections and cross-section of interest for reactor calculations
Uncertainty and Sensitivity Analyses Plan
Simpson, J.C.; Ramsdell, J.V. Jr.
1993-04-01
Hanford Environmental Dose Reconstruction (HEDR) Project staff are developing mathematical models to be used to estimate the radiation dose that individuals may have received as a result of emissions since 1944 from the US Department of Energy's (DOE) Hanford Site near Richland, Washington. An uncertainty and sensitivity analyses plan is essential to understand and interpret the predictions from these mathematical models. This is especially true in the case of the HEDR models where the values of many parameters are unknown. This plan gives a thorough documentation of the uncertainty and hierarchical sensitivity analysis methods recommended for use on all HEDR mathematical models. The documentation includes both technical definitions and examples. In addition, an extensive demonstration of the uncertainty and sensitivity analysis process is provided using actual results from the Hanford Environmental Dose Reconstruction Integrated Codes (HEDRIC). This demonstration shows how the approaches used in the recommended plan can be adapted for all dose predictions in the HEDR Project
Uncertainties in fatal cancer risk estimates used in radiation protection
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.)
Bayesian analysis for uncertainty estimation of a canopy transpiration model
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.
Summary of existing uncertainty methods
Glaeser, Horst
2013-01-01
A summary of existing and most used uncertainty methods is presented, and the main features are compared. One of these methods is the order statistics method based on Wilks' formula. It is applied in safety research as well as in licensing. This method has been first proposed by GRS for use in deterministic safety analysis, and is now used by many organisations world-wide. Its advantage is that the number of potential uncertain input and output parameters is not limited to a small number. Such a limitation was necessary for the first demonstration of the Code Scaling Applicability Uncertainty Method (CSAU) by the United States Regulatory Commission (USNRC). They did not apply Wilks' formula in their statistical method propagating input uncertainties to obtain the uncertainty of a single output variable, like peak cladding temperature. A Phenomena Identification and Ranking Table (PIRT) was set up in order to limit the number of uncertain input parameters, and consequently, the number of calculations to be performed. Another purpose of such a PIRT process is to identify the most important physical phenomena which a computer code should be suitable to calculate. The validation of the code should be focused on the identified phenomena. Response surfaces are used in some applications replacing the computer code for performing a high number of calculations. The second well known uncertainty method is the Uncertainty Methodology Based on Accuracy Extrapolation (UMAE) and the follow-up method 'Code with the Capability of Internal Assessment of Uncertainty (CIAU)' developed by the University Pisa. Unlike the statistical approaches, the CIAU does compare experimental data with calculation results. It does not consider uncertain input parameters. Therefore, the CIAU is highly dependent on the experimental database. The accuracy gained from the comparison between experimental data and calculated results are extrapolated to obtain the uncertainty of the system code predictions
Uncertainty analysis in safety assessment
Lemos, Francisco Luiz de [Centro de Desenvolvimento da Tecnologia Nuclear (CDTN), Belo Horizonte, MG (Brazil); Sullivan, Terry [Brookhaven National Lab., Upton, NY (United States)
1997-12-31
Nuclear waste disposal is a very complex subject which requires the study of many different fields of science, like hydro geology, meteorology, geochemistry, etc. In addition, the waste disposal facilities are designed to last for a very long period of time. Both of these conditions make safety assessment projections filled with uncertainty. This paper addresses approaches for treatment of uncertainties in the safety assessment modeling due to the variability of data and some current approaches used to deal with this problem. (author) 13 refs.; e-mail: lemos at bnl.gov; sulliva1 at bnl.gov
Awe, uncertainty, and agency detection.
Valdesolo, Piercarlo; Graham, Jesse
2014-01-01
Across five studies, we found that awe increases both supernatural belief (Studies 1, 2, and 5) and intentional-pattern perception (Studies 3 and 4)-two phenomena that have been linked to agency detection, or the tendency to interpret events as the consequence of intentional and purpose-driven agents. Effects were both directly and conceptually replicated, and mediational analyses revealed that these effects were driven by the influence of awe on tolerance for uncertainty. Experiences of awe decreased tolerance for uncertainty, which, in turn, increased the tendency to believe in nonhuman agents and to perceive human agency in random events.
Linear Programming Problems for Generalized Uncertainty
Thipwiwatpotjana, Phantipa
2010-01-01
Uncertainty occurs when there is more than one realization that can represent an information. This dissertation concerns merely discrete realizations of an uncertainty. Different interpretations of an uncertainty and their relationships are addressed when the uncertainty is not a probability of each realization. A well known model that can handle…
Radon measurements: the sources of uncertainties
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, probability and information-gaps
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
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.
Chapter 3: Traceability and uncertainty
McEwen, Malcolm
2014-01-01
Chapter 3 presents: an introduction; Traceability (measurement standard, role of the Bureau International des Poids et Mesures, Secondary Standards Laboratories, documentary standards and traceability as process review); Uncertainty (Example 1 - Measurement, M raw (SSD), Example 2 - Calibration data, N D.w 60 Co, kQ, Example 3 - Correction factor, P TP ) and Conclusion
Competitive Capacity Investment under Uncertainty
X. Li (Xishu); R.A. Zuidwijk (Rob); M.B.M. de Koster (René); R. Dekker (Rommert)
2016-01-01
textabstractWe consider a long-term capacity investment problem in a competitive market under demand uncertainty. Two firms move sequentially in the competition and a firm’s capacity decision interacts with the other firm’s current and future capacity. Throughout the investment race, a firm can
Uncertainty quantification and error analysis
Higdon, Dave M [Los Alamos National Laboratory; Anderson, Mark C [Los Alamos National Laboratory; Habib, Salman [Los Alamos National Laboratory; Klein, Richard [Los Alamos National Laboratory; Berliner, Mark [OHIO STATE UNIV.; Covey, Curt [LLNL; Ghattas, Omar [UNIV OF TEXAS; Graziani, Carlo [UNIV OF CHICAGO; Seager, Mark [LLNL; Sefcik, Joseph [LLNL; Stark, Philip [UC/BERKELEY; Stewart, James [SNL
2010-01-01
UQ studies all sources of error and uncertainty, including: systematic and stochastic measurement error; ignorance; limitations of theoretical models; limitations of numerical representations of those models; limitations on the accuracy and reliability of computations, approximations, and algorithms; and human error. A more precise definition for UQ is suggested below.
Uncertainties in radioecological assessment models
Hoffman, F.O.; Miller, C.W.; Ng, Y.C.
1983-01-01
Environmental radiological assessments rely heavily on the use of mathematical models. The predictions of these models are inherently uncertain because models are inexact representations of real systems. The major sources of this uncertainty are related to bias in model formulation and imprecision in parameter estimation. The magnitude of uncertainty is a function of the questions asked of the model and the specific radionuclides and exposure pathways of dominant importance. It is concluded that models developed as research tools should be distinguished from models developed for assessment applications. Furthermore, increased model complexity does not necessarily guarantee increased accuracy. To improve the realism of assessment modeling, stochastic procedures are recommended that translate uncertain parameter estimates into a distribution of predicted values. These procedures also permit the importance of model parameters to be ranked according to their relative contribution to the overall predicted uncertainty. Although confidence in model predictions can be improved through site-specific parameter estimation and increased model validation, health risk factors and internal dosimetry models will probably remain important contributors to the amount of uncertainty that is irreducible. 41 references, 4 figures, 4 tables
Numerical modeling of economic uncertainty
Schjær-Jacobsen, Hans
2007-01-01
Representation and modeling of economic uncertainty is addressed by different modeling methods, namely stochastic variables and probabilities, interval analysis, and fuzzy numbers, in particular triple estimates. Focusing on discounted cash flow analysis numerical results are presented, comparisons...... are made between alternative modeling methods, and characteristics of the methods are discussed....
Uncertainty covariances in robotics applications
Smith, D.L.
1984-01-01
The application of uncertainty covariance matrices in the analysis of robot trajectory errors is explored. First, relevant statistical concepts are reviewed briefly. Then, a simple, hypothetical robot model is considered to illustrate methods for error propagation and performance test data evaluation. The importance of including error correlations is emphasized
Regulating renewable resources under uncertainty
Hansen, Lars Gårn
) that a pro-quota result under uncertainty about prices and marginal costs is unlikely, requiring that the resource growth function is highly concave locally around the optimum and, 3) that quotas are always preferred if uncertainly about underlying structural economic parameters dominates. These results...... showing that quotas are preferred in a number of situations qualify the pro fee message dominating prior studies....
Home; Journals; Resonance – Journal of Science Education; Volume 4; Issue 2. Uncertainty in the Real World - Fuzzy Sets. Satish Kumar. General Article Volume 4 Issue 2 February 1999 pp 37-47. Fulltext. Click here to view fulltext PDF. Permanent link: https://www.ias.ac.in/article/fulltext/reso/004/02/0037-0047 ...
Uncertainty of dustfall monitoring results
Martin A. van Nierop
2017-06-01
Full Text Available Fugitive dust has the ability to cause a nuisance and pollute the ambient environment, particularly from human activities including construction and industrial sites and mining operations. As such, dustfall monitoring has occurred for many decades in South Africa; little has been published on the repeatability, uncertainty, accuracy and precision of dustfall monitoring. Repeatability assesses the consistency associated with the results of a particular measurement under the same conditions; the consistency of the laboratory is assessed to determine the uncertainty associated with dustfall monitoring conducted by the laboratory. The aim of this study was to improve the understanding of the uncertainty in dustfall monitoring; thereby improving the confidence in dustfall monitoring. Uncertainty of dustfall monitoring was assessed through a 12-month study of 12 sites that were located on the boundary of the study area. Each site contained a directional dustfall sampler, which was modified by removing the rotating lid, with four buckets (A, B, C and D installed. Having four buckets on one stand allows for each bucket to be exposed to the same conditions, for the same period of time; therefore, should have equal amounts of dust deposited in these buckets. The difference in the weight (mg of the dust recorded from each bucket at each respective site was determined using the American Society for Testing and Materials method D1739 (ASTM D1739. The variability of the dust would provide the confidence level of dustfall monitoring when reporting to clients.
Knowledge Uncertainty and Composed Classifier
Klimešová, Dana; Ocelíková, E.
2007-01-01
Roč. 1, č. 2 (2007), s. 101-105 ISSN 1998-0140 Institutional research plan: CEZ:AV0Z10750506 Keywords : Boosting architecture * contextual modelling * composed classifier * knowledge management, * knowledge * uncertainty Subject RIV: IN - Informatics, Computer Science
Uncertainty propagation in nuclear forensics
Pommé, S.; Jerome, S.M.; Venchiarutti, C.
2014-01-01
Uncertainty propagation formulae are presented for age dating in support of nuclear forensics. The age of radioactive material in this context refers to the time elapsed since a particular radionuclide was chemically separated from its decay product(s). The decay of the parent radionuclide and ingrowth of the daughter nuclide are governed by statistical decay laws. Mathematical equations allow calculation of the age of specific nuclear material through the atom ratio between parent and daughter nuclides, or through the activity ratio provided that the daughter nuclide is also unstable. The derivation of the uncertainty formulae of the age may present some difficulty to the user community and so the exact solutions, some approximations, a graphical representation and their interpretation are presented in this work. Typical nuclides of interest are actinides in the context of non-proliferation commitments. The uncertainty analysis is applied to a set of important parent–daughter pairs and the need for more precise half-life data is examined. - Highlights: • Uncertainty propagation formulae for age dating with nuclear chronometers. • Applied to parent–daughter pairs used in nuclear forensics. • Investigated need for better half-life data
WASH-1400: quantifying the uncertainties
Erdmann, R.C.; Leverenz, F.L. Jr.; Lellouche, G.S.
1981-01-01
The purpose of this paper is to focus on the limitations of the WASH-1400 analysis in estimating the risk from light water reactors (LWRs). This assessment attempts to modify the quantification of the uncertainty in and estimate of risk as presented by the RSS (reactor safety study). 8 refs
Model uncertainty in growth empirics
Prüfer, P.
2008-01-01
This thesis applies so-called Bayesian model averaging (BMA) to three different economic questions substantially exposed to model uncertainty. Chapter 2 addresses a major issue of modern development economics: the analysis of the determinants of pro-poor growth (PPG), which seeks to combine high
Uncertainty governance: an integrated framework for managing and communicating uncertainties
Umeki, H.; Naito, M.; Takase, H.
2004-01-01
Treatment of uncertainty, or in other words, reasoning with imperfect information is widely recognised as being of great importance within performance assessment (PA) of the geological disposal mainly because of the time scale of interest and spatial heterogeneity that geological environment exhibits. A wide range of formal methods have been proposed for the optimal processing of incomplete information. Many of these methods rely on the use of numerical information, the frequency based concept of probability in particular, to handle the imperfections. However, taking quantitative information as a base for models that solve the problem of handling imperfect information merely creates another problem, i.e., how to provide the quantitative information. In many situations this second problem proves more resistant to solution, and in recent years several authors have looked at a particularly ingenious way in accordance with the rules of well-founded methods such as Bayesian probability theory, possibility theory, and the Dempster-Shafer theory of evidence. Those methods, while drawing inspiration from quantitative methods, do not require the kind of complete numerical information required by quantitative methods. Instead they provide information that, though less precise than that provided by quantitative techniques, is often, if not sufficient, the best that could be achieved. Rather than searching for the best method for handling all imperfect information, our strategy for uncertainty management, that is recognition and evaluation of uncertainties associated with PA followed by planning and implementation of measures to reduce them, is to use whichever method best fits the problem at hand. Such an eclectic position leads naturally to integration of the different formalisms. While uncertainty management based on the combination of semi-quantitative methods forms an important part of our framework for uncertainty governance, it only solves half of the problem
Uncertainty Quantification for Ice Sheet Science and Sea Level Projections
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.
Water supply infrastructure planning under multiple uncertainties: A differentiated approach
Fletcher, S.; Strzepek, K.
2017-12-01
Many water planners face increased pressure on water supply systems from increasing demands from population and economic growth in combination with uncertain water supply. Supply uncertainty arises from short-term climate variability and long-term climate change as well as uncertainty in groundwater availability. Social and economic uncertainties - such as sectoral competition for water, food and energy security, urbanization, and environmental protection - compound physical uncertainty. Further, the varying risk aversion of stakeholders and water managers makes it difficult to assess the necessity of expensive infrastructure investments to reduce risk. We categorize these uncertainties on two dimensions: whether they can be updated over time by collecting additional information, and whether the uncertainties can be described probabilistically or are "deep" uncertainties whose likelihood is unknown. Based on this, we apply a decision framework that combines simulation for probabilistic uncertainty, scenario analysis for deep uncertainty, and multi-stage decision analysis for uncertainties that are reduced over time with additional information. In light of these uncertainties and the investment costs of large infrastructure, we propose the assessment of staged, modular infrastructure and information updating as a hedge against risk. We apply this framework to cases in Melbourne, Australia and Riyadh, Saudi Arabia. Melbourne is a surface water system facing uncertain population growth and variable rainfall and runoff. A severe drought from 1997 to 2009 prompted investment in a 150 MCM/y reverse osmosis desalination plan with a capital cost of 3.5 billion. Our analysis shows that flexible design in which a smaller portion of capacity is developed initially with the option to add modular capacity in the future can mitigate uncertainty and reduce the expected lifetime costs by up to 1 billion. In Riyadh, urban water use relies on fossil groundwater aquifers and
Uncertainty and validation. Effect of model complexity on uncertainty estimates
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
Investment under Uncertainty and Financial Crisis
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....
The EURACOS activation experiments: preliminary uncertainty analysis
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
Stereo-particle image velocimetry uncertainty quantification
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
Experimental uncertainty estimation and statistics for data having interval uncertainty.
Kreinovich, Vladik (Applied Biomathematics, Setauket, New York); Oberkampf, William Louis (Applied Biomathematics, Setauket, New York); Ginzburg, Lev (Applied Biomathematics, Setauket, New York); Ferson, Scott (Applied Biomathematics, Setauket, New York); Hajagos, Janos (Applied Biomathematics, Setauket, New York)
2007-05-01
This report addresses the characterization of measurements that include epistemic uncertainties in the form of intervals. It reviews the application of basic descriptive statistics to data sets which contain intervals rather than exclusively point estimates. It describes algorithms to compute various means, the median and other percentiles, variance, interquartile range, moments, confidence limits, and other important statistics and summarizes the computability of these statistics as a function of sample size and characteristics of the intervals in the data (degree of overlap, size and regularity of widths, etc.). It also reviews the prospects for analyzing such data sets with the methods of inferential statistics such as outlier detection and regressions. The report explores the tradeoff between measurement precision and sample size in statistical results that are sensitive to both. It also argues that an approach based on interval statistics could be a reasonable alternative to current standard methods for evaluating, expressing and propagating measurement uncertainties.
Uncertainty and validation. Effect of model complexity on uncertainty estimates
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
Quantifying chemical uncertainties in simulations of the ISM
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.
Compilation of information on uncertainties involved in deposition modeling
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
SENSIT: a cross-section and design sensitivity and uncertainty analysis code
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
Applied research in uncertainty modeling and analysis
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...
Estimates of bias and uncertainty in recorded external dose
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
Uncertainty of the calibration factor
1995-01-01
According to present definitions, an error is the difference between a measured value and the ''true'' value. Thus an error has both a numerical value and a sign. In contrast, the uncertainly associated with a measurement is a parameter that characterizes the dispersion of the values ''that could reasonably be attributed to the measurand''. This parameter is normally an estimated standard deviation. An uncertainty, therefore, has no known sign and is usually assumed to be symmetrical. It is a measure of our lack of exact knowledge, after all recognized ''systematic'' effects have been eliminated by applying appropriate corrections. If errors were known exactly, the true value could be determined and there would be no problem left. In reality, errors are estimated in the best possible way and corrections made for them. Therefore, after application of all known corrections, errors need no further consideration (their expectation value being zero) and the only quantities of interest are uncertainties. 3 refs, 2 figs
Quantifying the uncertainty in heritability.
Furlotte, Nicholas A; Heckerman, David; Lippert, Christoph
2014-05-01
The use of mixed models to determine narrow-sense heritability and related quantities such as SNP heritability has received much recent attention. Less attention has been paid to the inherent variability in these estimates. One approach for quantifying variability in estimates of heritability is a frequentist approach, in which heritability is estimated using maximum likelihood and its variance is quantified through an asymptotic normal approximation. An alternative approach is to quantify the uncertainty in heritability through its Bayesian posterior distribution. In this paper, we develop the latter approach, make it computationally efficient and compare it to the frequentist approach. We show theoretically that, for a sufficiently large sample size and intermediate values of heritability, the two approaches provide similar results. Using the Atherosclerosis Risk in Communities cohort, we show empirically that the two approaches can give different results and that the variance/uncertainty can remain large.
Uncertainty in hydrological change modelling
Seaby, Lauren Paige
applied at the grid scale. Flux and state hydrological outputs which integrate responses over time and space showed more sensitivity to precipitation mean spatial biases and less so on extremes. In the investigated catchments, the projected change of groundwater levels and basin discharge between current......Hydrological change modelling methodologies generally use climate models outputs to force hydrological simulations under changed conditions. There are nested sources of uncertainty throughout this methodology, including choice of climate model and subsequent bias correction methods. This Ph.......D. study evaluates the uncertainty of the impact of climate change in hydrological simulations given multiple climate models and bias correction methods of varying complexity. Three distribution based scaling methods (DBS) were developed and benchmarked against a more simplistic and commonly used delta...
Visualizing Summary Statistics and Uncertainty
Potter, K.
2010-08-12
The graphical depiction of uncertainty information is emerging as a problem of great importance. Scientific data sets are not considered complete without indications of error, accuracy, or levels of confidence. The visual portrayal of this information is a challenging task. This work takes inspiration from graphical data analysis to create visual representations that show not only the data value, but also important characteristics of the data including uncertainty. The canonical box plot is reexamined and a new hybrid summary plot is presented that incorporates a collection of descriptive statistics to highlight salient features of the data. Additionally, we present an extension of the summary plot to two dimensional distributions. Finally, a use-case of these new plots is presented, demonstrating their ability to present high-level overviews as well as detailed insight into the salient features of the underlying data distribution. © 2010 The Eurographics Association and Blackwell Publishing Ltd.
Visualizing Summary Statistics and Uncertainty
Potter, K.; Kniss, J.; Riesenfeld, R.; Johnson, C.R.
2010-01-01
The graphical depiction of uncertainty information is emerging as a problem of great importance. Scientific data sets are not considered complete without indications of error, accuracy, or levels of confidence. The visual portrayal of this information is a challenging task. This work takes inspiration from graphical data analysis to create visual representations that show not only the data value, but also important characteristics of the data including uncertainty. The canonical box plot is reexamined and a new hybrid summary plot is presented that incorporates a collection of descriptive statistics to highlight salient features of the data. Additionally, we present an extension of the summary plot to two dimensional distributions. Finally, a use-case of these new plots is presented, demonstrating their ability to present high-level overviews as well as detailed insight into the salient features of the underlying data distribution. © 2010 The Eurographics Association and Blackwell Publishing Ltd.
Statistical uncertainties and unrecognized relationships
Rankin, J.P.
1985-01-01
Hidden relationships in specific designs directly contribute to inaccuracies in reliability assessments. Uncertainty factors at the system level may sometimes be applied in attempts to compensate for the impact of such unrecognized relationships. Often uncertainty bands are used to relegate unknowns to a miscellaneous category of low-probability occurrences. However, experience and modern analytical methods indicate that perhaps the dominant, most probable and significant events are sometimes overlooked in statistical reliability assurances. The author discusses the utility of two unique methods of identifying the otherwise often unforeseeable system interdependencies for statistical evaluations. These methods are sneak circuit analysis and a checklist form of common cause failure analysis. Unless these techniques (or a suitable equivalent) are also employed along with the more widely-known assurance tools, high reliability of complex systems may not be adequately assured. This concern is indicated by specific illustrations. 8 references, 5 figures
The uncertainty budget in pharmaceutical industry
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...
Improvement of uncertainty relations for mixed states
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
Adjoint-Based Uncertainty Quantification with MCNP
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.
Conditional Betas and Investor Uncertainty
Fernando D. Chague
2013-01-01
We derive theoretical expressions for market betas from a rational expectation equilibrium model where the representative investor does not observe if the economy is in a recession or an expansion. Market betas in this economy are time-varying and related to investor uncertainty about the state of the economy. The dynamics of betas will also vary across assets according to the assets' cash-flow structure. In a calibration exercise, we show that value and growth firms have cash-flow structures...
Aggregate Uncertainty, Money and Banking
Hongfei Sun
2006-01-01
This paper studies the problem of monitoring the monitor in a model of money and banking with aggregate uncertainty. It shows that when inside money is required as a means of bank loan repayment, a market of inside money is entailed at the repayment stage and generates information-revealing prices that perfectly discipline the bank. The incentive problem of a bank is costlessly overcome simply by involving inside money in repayment. Inside money distinguishes itself from outside money by its ...
Decision Under Uncertainty in Diagnosis
Kalme, Charles I.
2013-01-01
This paper describes the incorporation of uncertainty in diagnostic reasoning based on the set covering model of Reggia et. al. extended to what in the Artificial Intelligence dichotomy between deep and compiled (shallow, surface) knowledge based diagnosis may be viewed as the generic form at the compiled end of the spectrum. A major undercurrent in this is advocating the need for a strong underlying model and an integrated set of support tools for carrying such a model in order to deal with ...
Uncertainty analysis for hot channel
Panka, I.; Kereszturi, A.
2006-01-01
The fulfillment of the safety analysis acceptance criteria is usually evaluated by separate hot channel calculations using the results of neutronic or/and thermo hydraulic system calculations. In case of an ATWS event (inadvertent withdrawal of control assembly), according to the analysis, a number of fuel rods are experiencing DNB for a longer time and must be regarded as failed. Their number must be determined for a further evaluation of the radiological consequences. In the deterministic approach, the global power history must be multiplied by different hot channel factors (kx) taking into account the radial power peaking factors for each fuel pin. If DNB occurs it is necessary to perform a few number of hot channel calculations to determine the limiting kx leading just to DNB and fuel failure (the conservative DNBR limit is 1.33). Knowing the pin power distribution from the core design calculation, the number of failed fuel pins can be calculated. The above procedure can be performed by conservative assumptions (e.g. conservative input parameters in the hot channel calculations), as well. In case of hot channel uncertainty analysis, the relevant input parameters (k x, mass flow, inlet temperature of the coolant, pin average burnup, initial gap size, selection of power history influencing the gap conductance value) of hot channel calculations and the DNBR limit are varied considering the respective uncertainties. An uncertainty analysis methodology was elaborated combining the response surface method with the one sided tolerance limit method of Wilks. The results of deterministic and uncertainty hot channel calculations are compared regarding to the number of failed fuel rods, max. temperature of the clad surface and max. temperature of the fuel (Authors)
Forecast Accuracy Uncertainty and Momentum
Bing Han; Dong Hong; Mitch Warachka
2009-01-01
We demonstrate that stock price momentum and earnings momentum can result from uncertainty surrounding the accuracy of cash flow forecasts. Our model has multiple information sources issuing cash flow forecasts for a stock. The investor combines these forecasts into an aggregate cash flow estimate that has minimal mean-squared forecast error. This aggregate estimate weights each cash flow forecast by the estimated accuracy of its issuer, which is obtained from their past forecast errors. Mome...
Microeconomic Uncertainty and Macroeconomic Indeterminacy
Fagnart, Jean-François; Pierrard, Olivier; Sneessens, Henri
2005-01-01
The paper proposes a stylized intertemporal macroeconomic model wherein the combination of decentralized trading and microeconomic uncertainty (taking the form of privately observed and uninsured idiosyncratic shocks) creates an information problem between agents and generates indeterminacy of the macroeconomic equilibrium. For a given value of the economic fundamentals, the economy admits a continuum of equilibria that can be indexed by the sales expectations of firms at the time of investme...
LOFT differential pressure uncertainty analysis
Evans, R.P.; Biladeau, G.L.; Quinn, P.A.
1977-03-01
A performance analysis of the LOFT differential pressure (ΔP) measurement is presented. Along with completed descriptions of test programs and theoretical studies that have been conducted on the ΔP, specific sources of measurement uncertainty are identified, quantified, and combined to provide an assessment of the ability of this measurement to satisfy the SDD 1.4.1C (June 1975) requirement of measurement of differential pressure
Knowledge, decision making, and uncertainty
Fox, J.
1986-01-01
Artificial intelligence (AI) systems depend heavily upon the ability to make decisions. Decisions require knowledge, yet there is no knowledge-based theory of decision making. To the extent that AI uses a theory of decision-making it adopts components of the traditional statistical view in which choices are made by maximizing some function of the probabilities of decision options. A knowledge-based scheme for reasoning about uncertainty is proposed, which extends the traditional framework but is compatible with it
Accommodating Uncertainty in Prior Distributions
Picard, Richard Roy [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Vander Wiel, Scott Alan [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
2017-01-19
A fundamental premise of Bayesian methodology is that a priori information is accurately summarized by a single, precisely de ned prior distribution. In many cases, especially involving informative priors, this premise is false, and the (mis)application of Bayes methods produces posterior quantities whose apparent precisions are highly misleading. We examine the implications of uncertainty in prior distributions, and present graphical methods for dealing with them.
Managing project risks and uncertainties
Mike Mentis
2015-01-01
Full Text Available This article considers threats to a project slipping on budget, schedule and fit-for-purpose. Threat is used here as the collective for risks (quantifiable bad things that can happen and uncertainties (poorly or not quantifiable bad possible events. Based on experience with projects in developing countries this review considers that (a project slippage is due to uncertainties rather than risks, (b while eventuation of some bad things is beyond control, managed execution and oversight are still the primary means to keeping within budget, on time and fit-for-purpose, (c improving project delivery is less about bigger and more complex and more about coordinated focus, effectiveness and developing thought-out heuristics, and (d projects take longer and cost more partly because threat identification is inaccurate, the scope of identified threats is too narrow, and the threat assessment product is not integrated into overall project decision-making and execution. Almost by definition, what is poorly known is likely to cause problems. Yet it is not just the unquantifiability and intangibility of uncertainties causing project slippage, but that they are insufficiently taken into account in project planning and execution that cause budget and time overruns. Improving project performance requires purpose-driven and managed deployment of scarce seasoned professionals. This can be aided with independent oversight by deeply experienced panelists who contribute technical insights and can potentially show that diligence is seen to be done.
Uncertainty in river discharge observations: a quantitative analysis
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.
Characterizing Epistemic Uncertainty for Launch Vehicle Designs
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.
Petroleum taxation under uncertainty - contingent claims
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
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
Probabilistic Radiological Performance Assessment Modeling and Uncertainty
Tauxe, J.
2004-12-01
A generic probabilistic radiological Performance Assessment (PA) model is presented. The model, built using the GoldSim systems simulation software platform, concerns contaminant transport and dose estimation in support of decision making with uncertainty. Both the U.S. Nuclear Regulatory Commission (NRC) and the U.S. Department of Energy (DOE) require assessments of potential future risk to human receptors of disposal of LLW. Commercially operated LLW disposal facilities are licensed by the NRC (or agreement states), and the DOE operates such facilities for disposal of DOE-generated LLW. The type of PA model presented is probabilistic in nature, and hence reflects the current state of knowledge about the site by using probability distributions to capture what is expected (central tendency or average) and the uncertainty (e.g., standard deviation) associated with input parameters, and propagating through the model to arrive at output distributions that reflect expected performance and the overall uncertainty in the system. Estimates of contaminant release rates, concentrations in environmental media, and resulting doses to human receptors well into the future are made by running the model in Monte Carlo fashion, with each realization representing a possible combination of input parameter values. Statistical summaries of the results can be compared to regulatory performance objectives, and decision makers are better informed of the inherently uncertain aspects of the model which supports their decision-making. While this information may make some regulators uncomfortable, they must realize that uncertainties which were hidden in a deterministic analysis are revealed in a probabilistic analysis, and the chance of making a correct decision is now known rather than hoped for. The model includes many typical features and processes that would be part of a PA, but is entirely fictitious. This does not represent any particular site and is meant to be a generic example. A
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
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.
Uncertainty quantification for environmental models
Hill, Mary C.; Lu, Dan; Kavetski, Dmitri; Clark, Martyn P.; Ye, Ming
2012-01-01
Environmental models are used to evaluate the fate of fertilizers in agricultural settings (including soil denitrification), the degradation of hydrocarbons at spill sites, and water supply for people and ecosystems in small to large basins and cities—to mention but a few applications of these models. They also play a role in understanding and diagnosing potential environmental impacts of global climate change. The models are typically mildly to extremely nonlinear. The persistent demand for enhanced dynamics and resolution to improve model realism [17] means that lengthy individual model execution times will remain common, notwithstanding continued enhancements in computer power. In addition, high-dimensional parameter spaces are often defined, which increases the number of model runs required to quantify uncertainty [2]. Some environmental modeling projects have access to extensive funding and computational resources; many do not. The many recent studies of uncertainty quantification in environmental model predictions have focused on uncertainties related to data error and sparsity of data, expert judgment expressed mathematically through prior information, poorly known parameter values, and model structure (see, for example, [1,7,9,10,13,18]). Approaches for quantifying uncertainty include frequentist (potentially with prior information [7,9]), Bayesian [13,18,19], and likelihood-based. A few of the numerous methods, including some sensitivity and inverse methods with consequences for understanding and quantifying uncertainty, are as follows: Bayesian hierarchical modeling and Bayesian model averaging; single-objective optimization with error-based weighting [7] and multi-objective optimization [3]; methods based on local derivatives [2,7,10]; screening methods like OAT (one at a time) and the method of Morris [14]; FAST (Fourier amplitude sensitivity testing) [14]; the Sobol' method [14]; randomized maximum likelihood [10]; Markov chain Monte Carlo (MCMC) [10
Uncertainty analysis of the FRAP code
Peck, S.O.
1978-01-01
A user oriented, automated uncertainty analysis capability has been built into the FRAP code (Fuel Rod Analysis Program) and applied to a PWR fuel rod undergoing a LOCA. The method of uncertainty analysis is the Response Surface Method (RSM). (author)
Two multi-dimensional uncertainty relations
Skala, L; Kapsa, V
2008-01-01
Two multi-dimensional uncertainty relations, one related to the probability density and the other one related to the probability density current, are derived and discussed. Both relations are stronger than the usual uncertainty relations for the coordinates and momentum
Change and uncertainty in quantum systems
Franson, J.D.
1996-01-01
A simple inequality shows that any change in the expectation value of an observable quantity must be associated with some degree of uncertainty. This inequality is often more restrictive than the Heisenberg uncertainty principle. copyright 1996 The American Physical Society
Measure of uncertainty in regional grade variability
Tutmez, B.; Kaymak, U.; Melin, P.; Castillo, O.; Gomez Ramirez, E.; Kacprzyk, J.; Pedrycz, W.
2007-01-01
Because the geological events are neither homogeneous nor isotropic, the geological investigations are characterized by particularly high uncertainties. This paper presents a hybrid methodology for measuring of uncertainty in regional grade variability. In order to evaluate the fuzziness in grade
Uncertainty and its propagation in dynamics models
Devooght, J.
1994-01-01
The purpose of this paper is to bring together some characteristics due to uncertainty when we deal with dynamic models and therefore to propagation of uncertainty. The respective role of uncertainty and inaccuracy is examined. A mathematical formalism based on Chapman-Kolmogorov equation allows to define a open-quotes subdynamicsclose quotes where the evolution equation takes the uncertainty into account. The problem of choosing or combining models is examined through a loss function associated to a decision
Some illustrative examples of model uncertainty
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 Uncertainty Multiplier and Business Cycles
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 ...
Measurement uncertainty budget of an interferometric flow velocity sensor
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 Characterization of Reactor Vessel Fracture Toughness
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)
Uncertainty in prediction and in inference
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
Entropic uncertainty relations-a survey
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.
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
Uncertainty and validation. Effect of user interpretation on uncertainty estimates
Kirchner, G.; Peterson, R.
1996-11-01
Uncertainty in predictions of environmental transfer models arises from, among other sources, the adequacy of the conceptual model, the approximations made in coding the conceptual model, the quality of the input data, the uncertainty in parameter values, and the assumptions made by the user. In recent years efforts to quantify the confidence that can be placed in predictions have been increasing, but have concentrated on a statistical propagation of the influence of parameter uncertainties on the calculational results. The primary objective of this Working Group of BIOMOVS II was to test user's influence on model predictions on a more systematic basis than has been done before. The main goals were as follows: To compare differences between predictions from different people all using the same model and the same scenario description with the statistical uncertainties calculated by the model. To investigate the main reasons for different interpretations by users. To create a better awareness of the potential influence of the user on the modeling results. Terrestrial food chain models driven by deposition of radionuclides from the atmosphere were used. Three codes were obtained and run with three scenarios by a maximum of 10 users. A number of conclusions can be drawn some of which are general and independent of the type of models and processes studied, while others are restricted to the few processes that were addressed directly: For any set of predictions, the variation in best estimates was greater than one order of magnitude. Often the range increased from deposition to pasture to milk probably due to additional transfer processes. The 95% confidence intervals about the predictions calculated from the parameter distributions prepared by the participants did not always overlap the observations; similarly, sometimes the confidence intervals on the predictions did not overlap. Often the 95% confidence intervals of individual predictions were smaller than the
Uncertainty and validation. Effect of user interpretation on uncertainty estimates
Kirchner, G. [Univ. of Bremen (Germany); Peterson, R. [AECL, Chalk River, ON (Canada)] [and others
1996-11-01
Uncertainty in predictions of environmental transfer models arises from, among other sources, the adequacy of the conceptual model, the approximations made in coding the conceptual model, the quality of the input data, the uncertainty in parameter values, and the assumptions made by the user. In recent years efforts to quantify the confidence that can be placed in predictions have been increasing, but have concentrated on a statistical propagation of the influence of parameter uncertainties on the calculational results. The primary objective of this Working Group of BIOMOVS II was to test user's influence on model predictions on a more systematic basis than has been done before. The main goals were as follows: To compare differences between predictions from different people all using the same model and the same scenario description with the statistical uncertainties calculated by the model. To investigate the main reasons for different interpretations by users. To create a better awareness of the potential influence of the user on the modeling results. Terrestrial food chain models driven by deposition of radionuclides from the atmosphere were used. Three codes were obtained and run with three scenarios by a maximum of 10 users. A number of conclusions can be drawn some of which are general and independent of the type of models and processes studied, while others are restricted to the few processes that were addressed directly: For any set of predictions, the variation in best estimates was greater than one order of magnitude. Often the range increased from deposition to pasture to milk probably due to additional transfer processes. The 95% confidence intervals about the predictions calculated from the parameter distributions prepared by the participants did not always overlap the observations; similarly, sometimes the confidence intervals on the predictions did not overlap. Often the 95% confidence intervals of individual predictions were smaller than the
Failure probability under parameter uncertainty.
Gerrard, R; Tsanakas, A
2011-05-01
In many problems of risk analysis, failure is equivalent to the event of a random risk factor exceeding a given threshold. Failure probabilities can be controlled if a decisionmaker is able to set the threshold at an appropriate level. This abstract situation applies, for example, to environmental risks with infrastructure controls; to supply chain risks with inventory controls; and to insurance solvency risks with capital controls. However, uncertainty around the distribution of the risk factor implies that parameter error will be present and the measures taken to control failure probabilities may not be effective. We show that parameter uncertainty increases the probability (understood as expected frequency) of failures. For a large class of loss distributions, arising from increasing transformations of location-scale families (including the log-normal, Weibull, and Pareto distributions), the article shows that failure probabilities can be exactly calculated, as they are independent of the true (but unknown) parameters. Hence it is possible to obtain an explicit measure of the effect of parameter uncertainty on failure probability. Failure probability can be controlled in two different ways: (1) by reducing the nominal required failure probability, depending on the size of the available data set, and (2) by modifying of the distribution itself that is used to calculate the risk control. Approach (1) corresponds to a frequentist/regulatory view of probability, while approach (2) is consistent with a Bayesian/personalistic view. We furthermore show that the two approaches are consistent in achieving the required failure probability. Finally, we briefly discuss the effects of data pooling and its systemic risk implications. © 2010 Society for Risk Analysis.
Quantum Uncertainty and Fundamental Interactions
Tosto S.
2013-04-01
Full Text Available The paper proposes a simplified theoretical approach to infer some essential concepts on the fundamental interactions between charged particles and their relative strengths at comparable energies by exploiting the quantum uncertainty only. The worth of the present approach relies on the way of obtaining the results, rather than on the results themselves: concepts today acknowledged as fingerprints of the electroweak and strong interactions appear indeed rooted in the same theoretical frame including also the basic principles of special and general relativity along with the gravity force.
Uncertainty analysis in seismic tomography
Owoc, Bartosz; Majdański, Mariusz
2017-04-01
Velocity field from seismic travel time tomography depends on several factors like regularization, inversion path, model parameterization etc. The result also strongly depends on an initial velocity model and precision of travel times picking. In this research we test dependence on starting model in layered tomography and compare it with effect of picking precision. Moreover, in our analysis for manual travel times picking the uncertainty distribution is asymmetric. This effect is shifting the results toward faster velocities. For calculation we are using JIVE3D travel time tomographic code. We used data from geo-engineering and industrial scale investigations, which were collected by our team from IG PAS.
Modelling of Transport Projects Uncertainties
Salling, Kim Bang; Leleur, Steen
2009-01-01
This paper proposes a new way of handling the uncertainties present in transport decision making based on infrastructure appraisals. The paper suggests to combine the principle of Optimism Bias, which depicts the historical tendency of overestimating transport related benefits and underestimating...... to supplement Optimism Bias and the associated Reference Class Forecasting (RCF) technique with a new technique that makes use of a scenario-grid. We tentatively introduce and refer to this as Reference Scenario Forecasting (RSF). The final RSF output from the CBA-DK model consists of a set of scenario......-based graphs which function as risk-related decision support for the appraised transport infrastructure project....
Medical Need, Equality, and Uncertainty.
Horne, L Chad
2016-10-01
Many hold that distributing healthcare according to medical need is a requirement of equality. Most egalitarians believe, however, that people ought to be equal on the whole, by some overall measure of well-being or life-prospects; it would be a massive coincidence if distributing healthcare according to medical need turned out to be an effective way of promoting equality overall. I argue that distributing healthcare according to medical need is important for reducing individuals' uncertainty surrounding their future medical needs. In other words, distributing healthcare according to medical need is a natural feature of healthcare insurance; it is about indemnity, not equality. © 2016 John Wiley & Sons Ltd.
Reactor pressure vessels safety and reliability - certainty and uncertainty
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
Decision analysis of shoreline protection under climate change uncertainty
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.
Sources of uncertainties in modelling black carbon at the global scale
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
Fahrizal Fahrizal
2014-10-01
Full Text Available Cacao (Theobroma cacao is one of the product commodities in Aceh and its production continues to increase every year. Parts of cocoa that have economic value are the seed, while the skin that is a waste of processing cocoa beans is often not utilized. Cocoa skin can cause environmental pollution problems. One way of handling waste is to extract cocoa skin becomes pectin. Known in the food industry pectin compounds is very important adjuvant because it is able to increase the viscosity of the fluid and form a gel with sugar and acid. The aim of this research was to determine the effect of pectin addition from cacoa skin waste on the quality of pineapple jam. There are four levels of the pectin addition in this study; 0, 0.5, 1.0 and 1.5%. Then the resulted pineapple jam was analysed; moisture content, total of dissolved solids, acidity, a smear of jam and hedonic sensory evaluation for appearance, aroma, flavor, texture and all vallue. The addition of pectin from cocoa waste have effects on moisture content, total of dissolved solids, pH value and a smear of jam of pineapple jam. In general, panelists like pineapple jam with the addition of 1% pectin from cocoa skin waste
Pengaruh Perbandingan Labu Siam dengan Nenas dan Penambahan Gula Terhadap Mutu Selai Oles
Sitio, Dapot Parulian
2016-01-01
The research was conducted to determine the effect of ratio of chayote with pineapple and addition of sugar on quality of jam. This research was using a factorial completely randomized design with two factors: ratio of chayote with pineapple (N) : 90%:10%, 80%:20%, 70%:30%, 60%:40%, and sugar (G): 35%, 45%, 55%, 65%. Parameters observed were water content, ash content, vitamin C content, total acid, pH, total soluble solid, sensory test of color, flavor, taste and value skor of...
The economic implications of carbon cycle uncertainty
Smith, Steven J.; Edmonds, James A.
2006-01-01
This paper examines the implications of uncertainty in the carbon cycle for the cost of stabilizing carbon dioxide concentrations. Using a state of the art integrated assessment model, we find that uncertainty in our understanding of the carbon cycle has significant implications for the costs of a climate stabilization policy, with cost differences denominated in trillions of dollars. Uncertainty in the carbon cycle is equivalent to a change in concentration target of up to 100 ppmv. The impact of carbon cycle uncertainties are smaller than those for climate sensitivity, and broadly comparable to the effect of uncertainty in technology availability
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)
Risk uncertainty analysis methods for NUREG-1150
Benjamin, A.S.; Boyd, G.J.
1987-01-01
Evaluation and display of risk uncertainties for NUREG-1150 constitute a principal focus of the Severe Accident Risk Rebaselining/Risk Reduction Program (SARRP). Some of the principal objectives of the uncertainty evaluation are: (1) to provide a quantitative estimate that reflects, for those areas considered, a credible and realistic range of uncertainty in risk; (2) to rank the various sources of uncertainty with respect to their importance for various measures of risk; and (3) to characterize the state of understanding of each aspect of the risk assessment for which major uncertainties exist. This paper describes the methods developed to fulfill these objectives
Uncertainty Communication. Issues and good practice
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
Fuel cycle cost uncertainty from nuclear fuel cycle comparison
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 Relations and Possible Experience
Gregg Jaeger
2016-06-01
Full Text Available The uncertainty principle can be understood as a condition of joint indeterminacy of classes of properties in quantum theory. The mathematical expressions most closely associated with this principle have been the uncertainty relations, various inequalities exemplified by the well known expression regarding position and momentum introduced by Heisenberg. Here, recent work involving a new sort of “logical” indeterminacy principle and associated relations introduced by Pitowsky, expressable directly in terms of probabilities of outcomes of measurements of sharp quantum observables, is reviewed and its quantum nature is discussed. These novel relations are derivable from Boolean “conditions of possible experience” of the quantum realm and have been considered both as fundamentally logical and as fundamentally geometrical. This work focuses on the relationship of indeterminacy to the propositions regarding the values of discrete, sharp observables of quantum systems. Here, reasons for favoring each of these two positions are considered. Finally, with an eye toward future research related to indeterminacy relations, further novel approaches grounded in category theory and intended to capture and reconceptualize the complementarity characteristics of quantum propositions are discussed in relation to the former.
Inverse Problems and Uncertainty Quantification
Litvinenko, Alexander
2014-01-06
In a Bayesian setting, inverse problems and uncertainty quantification (UQ) - the propagation of uncertainty through a computational (forward) modelare strongly connected. In the form of conditional expectation the Bayesian update becomes computationally attractive. This is especially the case as together with a functional or spectral approach for the forward UQ there is no need for time- consuming and slowly convergent Monte Carlo sampling. The developed sampling- free non-linear Bayesian update is derived from the variational problem associated with conditional expectation. This formulation in general calls for further discretisa- tion to make the computation possible, and we choose a polynomial approximation. After giving details on the actual computation in the framework of functional or spectral approximations, we demonstrate the workings of the algorithm on a number of examples of increasing complexity. At last, we compare the linear and quadratic Bayesian update on the small but taxing example of the chaotic Lorenz 84 model, where we experiment with the influence of different observation or measurement operators on the update.
Uncertainties in the proton lifetime
Ellis, J.; Nanopoulos, D.V.; Rudaz, S.; Gaillard, M.K.
1980-04-01
We discuss the masses of the leptoquark bosons m(x) and the proton lifetime in Grand Unified Theories based principally on SU(5). It is emphasized that estimates of m(x) based on the QCD coupling and the fine structure constant are probably more reliable than those using the experimental value of sin 2 theta(w). Uncertainties in the QCD Λ parameter and the correct value of α are discussed. We estimate higher order effects on the evolution of coupling constants in a momentum space renormalization scheme. It is shown that increasing the number of generations of fermions beyond the minimal three increases m(X) by almost a factor of 2 per generation. Additional uncertainties exist for each generation of technifermions that may exist. We discuss and discount the possibility that proton decay could be 'Cabibbo-rotated' away, and a speculation that Lorentz invariance may be violated in proton decay at a detectable level. We estimate that in the absence of any substantial new physics beyond that in the minimal SU(5) model the proton lifetimes is 8 x 10 30+-2 years
Inverse Problems and Uncertainty Quantification
Litvinenko, Alexander; Matthies, Hermann G.
2014-01-01
In a Bayesian setting, inverse problems and uncertainty quantification (UQ) - the propagation of uncertainty through a computational (forward) modelare strongly connected. In the form of conditional expectation the Bayesian update becomes computationally attractive. This is especially the case as together with a functional or spectral approach for the forward UQ there is no need for time- consuming and slowly convergent Monte Carlo sampling. The developed sampling- free non-linear Bayesian update is derived from the variational problem associated with conditional expectation. This formulation in general calls for further discretisa- tion to make the computation possible, and we choose a polynomial approximation. After giving details on the actual computation in the framework of functional or spectral approximations, we demonstrate the workings of the algorithm on a number of examples of increasing complexity. At last, we compare the linear and quadratic Bayesian update on the small but taxing example of the chaotic Lorenz 84 model, where we experiment with the influence of different observation or measurement operators on the update.
Inverse problems and uncertainty quantification
Litvinenko, Alexander
2013-12-18
In a Bayesian setting, inverse problems and uncertainty quantification (UQ)— the propagation of uncertainty through a computational (forward) model—are strongly connected. In the form of conditional expectation the Bayesian update becomes computationally attractive. This is especially the case as together with a functional or spectral approach for the forward UQ there is no need for time- consuming and slowly convergent Monte Carlo sampling. The developed sampling- free non-linear Bayesian update is derived from the variational problem associated with conditional expectation. This formulation in general calls for further discretisa- tion to make the computation possible, and we choose a polynomial approximation. After giving details on the actual computation in the framework of functional or spectral approximations, we demonstrate the workings of the algorithm on a number of examples of increasing complexity. At last, we compare the linear and quadratic Bayesian update on the small but taxing example of the chaotic Lorenz 84 model, where we experiment with the influence of different observation or measurement operators on the update.
Inflation and Inflation Uncertainty Revisited: Evidence from Egypt
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.
Uncertainty and sensitivity analysis of the nuclear fuel thermal behavior
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.
Needs of the CSAU uncertainty method
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)
Decision-Making under Criteria Uncertainty
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.
Uncertainty in geological and hydrogeological data
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.
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
Local conditions and uncertainty bands for Semiscale Test S-02-9
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%
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.
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.
Helium Mass Spectrometer Leak Detection: A Method to Quantify Total Measurement Uncertainty
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.
Comparison of the uncertainties of several European low-dose calibration facilities
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.
Addressing uncertainties in the ERICA Integrated Approach
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
Reusable launch vehicle model uncertainties impact analysis
Chen, Jiaye; Mu, Rongjun; Zhang, Xin; Deng, Yanpeng
2018-03-01
Reusable launch vehicle(RLV) has the typical characteristics of complex aerodynamic shape and propulsion system coupling, and the flight environment is highly complicated and intensely changeable. So its model has large uncertainty, which makes the nominal system quite different from the real system. Therefore, studying the influences caused by the uncertainties on the stability of the control system is of great significance for the controller design. In order to improve the performance of RLV, this paper proposes the approach of analyzing the influence of the model uncertainties. According to the typical RLV, the coupling dynamic and kinematics models are built. Then different factors that cause uncertainties during building the model are analyzed and summed up. After that, the model uncertainties are expressed according to the additive uncertainty model. Choosing the uncertainties matrix's maximum singular values as the boundary model, and selecting the uncertainties matrix's norm to show t how much the uncertainty factors influence is on the stability of the control system . The simulation results illustrate that the inertial factors have the largest influence on the stability of the system, and it is necessary and important to take the model uncertainties into consideration before the designing the controller of this kind of aircraft( like RLV, etc).
Evaluation of incremental reactivity and its uncertainty in Southern California.
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.
Image restoration, uncertainty, and information.
Yu, F T
1969-01-01
Some of the physical interpretations about image restoration are discussed. From the theory of information the unrealizability of an inverse filter can be explained by degradation of information, which is due to distortion on the recorded image. The image restoration is a time and space problem, which can be recognized from the theory of relativity (the problem of image restoration is related to Heisenberg's uncertainty principle in quantum mechanics). A detailed discussion of the relationship between information and energy is given. Two general results may be stated: (1) the restoration of the image from the distorted signal is possible only if it satisfies the detectability condition. However, the restored image, at the best, can only approach to the maximum allowable time criterion. (2) The restoration of an image by superimposing the distorted signal (due to smearing) is a physically unrealizable method. However, this restoration procedure may be achieved by the expenditure of an infinite amount of energy.
Modelling of Transport Projects Uncertainties
Salling, Kim Bang; Leleur, Steen
2012-01-01
This paper proposes a new way of handling the uncertainties present in transport decision making based on infrastructure appraisals. The paper suggests to combine the principle of Optimism Bias, which depicts the historical tendency of overestimating transport related benefits and underestimating...... to supplement Optimism Bias and the associated Reference Class Forecasting (RCF) technique with a new technique that makes use of a scenario-grid. We tentatively introduce and refer to this as Reference Scenario Forecasting (RSF). The final RSF output from the CBA-DK model consists of a set of scenario......-based graphs which functions as risk-related decision support for the appraised transport infrastructure project. The presentation of RSF is demonstrated by using an appraisal case concerning a new airfield in the capital of Greenland, Nuuk....
Attitudes, beliefs, uncertainty and risk
Greenhalgh, Geoffrey [Down Park Place, Crawley Down (United Kingdom)
2001-07-01
There is now unmistakable evidence of a widening split within the Western industrial nations arising from conflicting views of society; for and against change. The argument is over the benefits of 'progress' and growth. On one side are those who seek more jobs, more production and consumption, higher standards of living, an ever-increasing GNP with an increasing globalisation of production and welcome the advances of science and technology confident that any temporary problems that arise can be solved by further technological development - possible energy shortages as a growing population increases energy usage can be met by nuclear power development; food shortages by the increased yields of GM crops. In opposition are those who put the quality of life before GNP, advocate a more frugal life-style, reducing needs and energy consumption, and, pointing to the harm caused by increasing pollution, press for cleaner air and water standards. They seek to reduce the pressure of an ever-increasing population and above all to preserve the natural environment. This view is associated with a growing uncertainty as the established order is challenged with the rise in status of 'alternative' science and medicine. This paper argues that these conflicting views reflect instinctive attitudes. These in turn draw support from beliefs selected from those which uncertainty offers. Where there is scope for argument over the truth or validity of a 'fact', the choice of which of the disputed views to believe will be determined by a value judgement. This applies to all controversial social and political issues. Nuclear waste disposal and biotechnology are but two particular examples in the technological field; joining the EMU is a current political controversy where value judgements based on attitudes determine beliefs. When, or if, a controversy is finally resolved the judgement arrived at will be justified by the belief that the consequences of the course chosen will be more favourable
Attitudes, beliefs, uncertainty and risk
Greenhalgh, Geoffrey [Down Park Place, Crawley Down (United Kingdom)
2001-07-01
There is now unmistakable evidence of a widening split within the Western industrial nations arising from conflicting views of society; for and against change. The argument is over the benefits of 'progress' and growth. On one side are those who seek more jobs, more production and consumption, higher standards of living, an ever-increasing GNP with an increasing globalisation of production and welcome the advances of science and technology confident that any temporary problems that arise can be solved by further technological development - possible energy shortages as a growing population increases energy usage can be met by nuclear power development; food shortages by the increased yields of GM crops. In opposition are those who put the quality of life before GNP, advocate a more frugal life-style, reducing needs and energy consumption, and, pointing to the harm caused by increasing pollution, press for cleaner air and water standards. They seek to reduce the pressure of an ever-increasing population and above all to preserve the natural environment. This view is associated with a growing uncertainty as the established order is challenged with the rise in status of 'alternative' science and medicine. This paper argues that these conflicting views reflect instinctive attitudes. These in turn draw support from beliefs selected from those which uncertainty offers. Where there is scope for argument over the truth or validity of a 'fact', the choice of which of the disputed views to believe will be determined by a value judgement. This applies to all controversial social and political issues. Nuclear waste disposal and biotechnology are but two particular examples in the technological field; joining the EMU is a current political controversy where value judgements based on attitudes determine beliefs. When, or if, a controversy is finally resolved the judgement arrived at will be justified by the belief that the consequences of the course
Attitudes, beliefs, uncertainty and risk
Greenhalgh, Geoffrey
2001-01-01
There is now unmistakable evidence of a widening split within the Western industrial nations arising from conflicting views of society; for and against change. The argument is over the benefits of 'progress' and growth. On one side are those who seek more jobs, more production and consumption, higher standards of living, an ever-increasing GNP with an increasing globalisation of production and welcome the advances of science and technology confident that any temporary problems that arise can be solved by further technological development - possible energy shortages as a growing population increases energy usage can be met by nuclear power development; food shortages by the increased yields of GM crops. In opposition are those who put the quality of life before GNP, advocate a more frugal life-style, reducing needs and energy consumption, and, pointing to the harm caused by increasing pollution, press for cleaner air and water standards. They seek to reduce the pressure of an ever-increasing population and above all to preserve the natural environment. This view is associated with a growing uncertainty as the established order is challenged with the rise in status of 'alternative' science and medicine. This paper argues that these conflicting views reflect instinctive attitudes. These in turn draw support from beliefs selected from those which uncertainty offers. Where there is scope for argument over the truth or validity of a 'fact', the choice of which of the disputed views to believe will be determined by a value judgement. This applies to all controversial social and political issues. Nuclear waste disposal and biotechnology are but two particular examples in the technological field; joining the EMU is a current political controversy where value judgements based on attitudes determine beliefs. When, or if, a controversy is finally resolved the judgement arrived at will be justified by the belief that the consequences of the course chosen will be more favourable
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...
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.
Optimal natural resources management under uncertainty with catastrophic risk
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
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
Phenomenon of Uncertainty as a Subjective Experience
Lifintseva A.A.
2018-04-01
Full Text Available The phenomenon of uncertainty in illness of patients is discussed and analyzed in this article. Uncertainty in illness is a condition that accompanies the patient from the moment of appearance of the first somatic symptoms of the disease and could be strengthened or weakened thanks to many psychosocial factors. The level of uncertainty is related to the level of stress, emotional disadaptation, affective states, coping strategies, mechanisms of psychological defense, etc. Uncertainty can perform destructive functions, acting as a trigger for stressful conditions and launching negative emotional experiences. As a positive function of uncertainty, one can note a possible positive interpretation of the patient's disease. In addition, the state of uncertainty allows the patient to activate the resources of coping with the disease, among which the leading role belongs to social support.
Visual Semiotics & Uncertainty Visualization: An Empirical Study.
MacEachren, A M; Roth, R E; O'Brien, J; Li, B; Swingley, D; Gahegan, M
2012-12-01
This paper presents two linked empirical studies focused on uncertainty visualization. The experiments are framed from two conceptual perspectives. First, a typology of uncertainty is used to delineate kinds of uncertainty matched with space, time, and attribute components of data. Second, concepts from visual semiotics are applied to characterize the kind of visual signification that is appropriate for representing those different categories of uncertainty. This framework guided the two experiments reported here. The first addresses representation intuitiveness, considering both visual variables and iconicity of representation. The second addresses relative performance of the most intuitive abstract and iconic representations of uncertainty on a map reading task. Combined results suggest initial guidelines for representing uncertainty and discussion focuses on practical applicability of results.
Uncertainty quantification theory, implementation, and applications
Smith, Ralph C
2014-01-01
The field of uncertainty quantification is evolving rapidly because of increasing emphasis on models that require quantified uncertainties for large-scale applications, novel algorithm development, and new computational architectures that facilitate implementation of these algorithms. Uncertainty Quantification: Theory, Implementation, and Applications provides readers with the basic concepts, theory, and algorithms necessary to quantify input and response uncertainties for simulation models arising in a broad range of disciplines. The book begins with a detailed discussion of applications where uncertainty quantification is critical for both scientific understanding and policy. It then covers concepts from probability and statistics, parameter selection techniques, frequentist and Bayesian model calibration, propagation of uncertainties, quantification of model discrepancy, surrogate model construction, and local and global sensitivity analysis. The author maintains a complementary web page where readers ca...
Report on the uncertainty methods study
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
Incorporating Forecast Uncertainty in Utility Control Center
Makarov, Yuri V.; Etingov, Pavel V.; Ma, Jian
2014-07-09
Uncertainties in forecasting the output of intermittent resources such as wind and solar generation, as well as system loads are not adequately reflected in existing industry-grade tools used for transmission system management, generation commitment, dispatch and market operation. There are other sources of uncertainty such as uninstructed deviations of conventional generators from their dispatch set points, generator forced outages and failures to start up, load drops, losses of major transmission facilities and frequency variation. These uncertainties can cause deviations from the system balance, which sometimes require inefficient and costly last minute solutions in the near real-time timeframe. This Chapter considers sources of uncertainty and variability, overall system uncertainty model, a possible plan for transition from deterministic to probabilistic methods in planning and operations, and two examples of uncertainty-based fools for grid operations.This chapter is based on work conducted at the Pacific Northwest National Laboratory (PNNL)
Evacuation decision-making: process and uncertainty
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
Chemical kinetic model uncertainty minimization through laminar flame speed measurements
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
Coping With Uncertainty in International Business
Briance Mascarenhas
1982-01-01
International business, as compared with domestic business, is usually characterized by increased uncertainty. A study of 10 multinational companies uncovered several methods of coping with uncertainty. This paper focuses on 2 methods which may not be apparent control and flexibility. A framework of analysis suggesting appropriate methods for coping with uncertainty is also developed.© 1982 JIBS. Journal of International Business Studies (1982) 13, 87–98
Extremum uncertainty product and sum states
Mehta, C L; Kumar, S [Indian Inst. of Tech., New Delhi. Dept. of Physics
1978-01-01
The extremum product states and sum states of the uncertainties in non-commuting observables have been examined. These are illustrated by two specific examples of harmonic oscillator and the angular momentum states. It shows that the coherent states of the harmonic oscillator are characterized by the minimum uncertainty sum <(..delta..q)/sup 2/>+<(..delta..p)/sup 2/>. The extremum values of the sums and products of the uncertainties of the components of the angular momentum are also obtained.
Inventories and sales uncertainty\\ud
Caglayan, M.; Maioli, S.; Mateut, S.
2011-01-01
We investigate the empirical linkages between sales uncertainty and firms´ inventory investment behavior while controlling for firms´ financial strength. Using large panels of manufacturing firms from several European countries we find that higher sales uncertainty leads to larger stocks of inventories. We also identify an indirect effect of sales uncertainty on inventory accumulation through the financial strength of firms. Our results provide evidence that financial strength mitigates the a...
Research of relationship between uncertainty and investment
MENG Li; WANG Ding-wei
2005-01-01
This study focuses on revealing the relationship between uncertainty and investment probability through real option model involving investment critical trigger and project earning. Use of Matlab software on the experimental results showing that project earning volatility influences investment probability, led the authors to conclude that this notion is not always correct, as increasing uncertainty should have an inhibiting effect on investment, and that in certain situation, increasing uncertainty actually increases the investment probability and so, should have positive impact on investment.
Evaluating Predictive Uncertainty of Hyporheic Exchange Modelling
Chow, R.; Bennett, J.; Dugge, J.; Wöhling, T.; Nowak, W.
2017-12-01
Hyporheic exchange is the interaction of water between rivers and groundwater, and is difficult to predict. One of the largest contributions to predictive uncertainty for hyporheic fluxes have been attributed to the representation of heterogeneous subsurface properties. This research aims to evaluate which aspect of the subsurface representation - the spatial distribution of hydrofacies or the model for local-scale (within-facies) heterogeneity - most influences the predictive uncertainty. Also, we seek to identify data types that help reduce this uncertainty best. For this investigation, we conduct a modelling study of the Steinlach River meander, in Southwest Germany. The Steinlach River meander is an experimental site established in 2010 to monitor hyporheic exchange at the meander scale. We use HydroGeoSphere, a fully integrated surface water-groundwater model, to model hyporheic exchange and to assess the predictive uncertainty of hyporheic exchange transit times (HETT). A highly parameterized complex model is built and treated as `virtual reality', which is in turn modelled with simpler subsurface parameterization schemes (Figure). Then, we conduct Monte-Carlo simulations with these models to estimate the predictive uncertainty. Results indicate that: Uncertainty in HETT is relatively small for early times and increases with transit times. Uncertainty from local-scale heterogeneity is negligible compared to uncertainty in the hydrofacies distribution. Introducing more data to a poor model structure may reduce predictive variance, but does not reduce predictive bias. Hydraulic head observations alone cannot constrain the uncertainty of HETT, however an estimate of hyporheic exchange flux proves to be more effective at reducing this uncertainty. Figure: Approach for evaluating predictive model uncertainty. A conceptual model is first developed from the field investigations. A complex model (`virtual reality') is then developed based on that conceptual model
Notes on the effect of dose uncertainty
Morris, M.D.
1987-01-01
The apparent dose-response relationship between amount of exposure to acute radiation and level of mortality in humans is affected by uncertainties in the dose values. It is apparent that one of the greatest concerns regarding the human data from Hiroshima and Nagasaki is the unexpectedly shallow slope of the dose response curve. This may be partially explained by uncertainty in the dose estimates. Some potential effects of dose uncertainty on the apparent dose-response relationship are demonstrated
Uncertainties of Molecular Structural Parameters
Császár, Attila G.
2014-01-01
Full text: The most fundamental property of a molecule is its three-dimensional (3D) structure formed by its constituent atoms (see, e.g., the perfectly regular hexagon associated with benzene). It is generally accepted that knowledge of the detailed structure of a molecule is a prerequisite to determine most of its other properties. What nowadays is a seemingly simple concept, namely that molecules have a structure, was introduced into chemistry in the 19th century. Naturally, the word changed its meaning over the years. Elemental analysis, simple structural formulae, two-dimensional and then 3D structures mark the development of the concept to its modern meaning. When quantum physics and quantum chemistry emerged in the 1920s, the simple concept associating structure with a three-dimensional object seemingly gained a firm support. Nevertheless, what seems self-explanatory today is in fact not so straightforward to justify within quantum mechanics. In quantum chemistry the concept of an equilibrium structure of a molecule is tied to the Born-Oppenheimer approximation but beyond the adiabatic separation of the motions of the nuclei and the electrons the meaning of a structure is still slightly obscured. Putting the conceptual difficulties aside, there are several experimental, empirical, and theoretical techniques to determine structures of molecules. One particular problem, strongly related to the question of uncertainties of “measured” or “computed” structural parameters, is that all the different techniques correspond to different structure definitions and thus yield different structural parameters. Experiments probing the structure of molecules rely on a number of structure definitions, to name just a few: r_0, r_g, r_a, r_s, r_m, etc., and one should also consider the temperature dependence of most of these structural parameters which differ from each other in the way the rovibrational motions of the molecules are treated and how the averaging is
Uncertainties of the Yn Parameters of the Hage-Cifarelli Formalism
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.
Unexpected uncertainty, volatility and decision-making
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.
Urban drainage models - making uncertainty analysis simple
Vezzaro, Luca; Mikkelsen, Peter Steen; Deletic, Ana
2012-01-01
in each measured/observed datapoint; an issue which is commonly overlook in the uncertainty analysis of urban drainage models. This comparison allows the user to intuitively estimate the optimum number of simulations required to conduct uncertainty analyses. The output of the method includes parameter......There is increasing awareness about uncertainties in modelling of urban drainage systems and, as such, many new methods for uncertainty analyses have been developed. Despite this, all available methods have limitations which restrict their widespread application among practitioners. Here...
Fuzzy Uncertainty Evaluation for Fault Tree Analysis
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.
Model Uncertainty for Bilinear Hysteretic Systems
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...
Uncertainties in s-process nucleosynthesis in massive stars determined by Monte Carlo variations
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.
Scientific uncertainties and climate risks
Petit, M.
2005-01-01
Human activities have induced a significant change in the Earth's atmospheric composition and, most likely, this trend will increase throughout the coming decades. During the last decades, the mean temperature has actually increased by the expected amount. Moreover, the geographical distribution of the warming, and day-to-night temperature variation have evolved as predicted. The magnitude of those changes is relatively small for the time being, but is expected to increase alarmingly during the coming decades. Greenhouse warming is a representative example of the problems of sustainable development: long-term risks can be estimated on a rational basis from scientific laws alone, but the non-specialist is generally not prepared to understand the steps required. However, even the non-specialist has obviously the right to decide about his way of life and the inheritance that he would like to leave for his children, but it is preferable that he is fully informed before making his decisions. Dialog, mutual understanding and confidence must prevail between Science and Society to avoid irrational actions. Controversy among experts is quite frequent. In the case of greenhouse warming, a commendable collective expertise has drastically reduced possible confusion. The Intergovernmental Panel on Climate Change was created jointly by the World Meteorology Organization (WMO) and the UN Program for the Environment (UNEP). Its reports evaluate the state of knowledge on past and future global climate changes, their impact, and the possibility of controlling anthropogenic emissions. The main targeted readers are, nevertheless, non-specialists, who should be made aware of results deduced from approaches that they may not be able to follow step by step. Moreover, these results, in particular, future projections, are, and will remain, subject to some uncertainty, which a fair description of the state of knowledge must include. Many misunderstandings between writers and readers can
Recognizing and responding to uncertainty: a grounded theory of nurses' uncertainty.
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.
Detailed modeling of the statistical uncertainty of Thomson scattering measurements
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
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)
Formal modeling of a system of chemical reactions under uncertainty.
Ghosh, Krishnendu; Schlipf, John
2014-10-01
We describe a novel formalism representing a system of chemical reactions, with imprecise rates of reactions and concentrations of chemicals, and describe a model reduction method, pruning, based on the chemical properties. We present two algorithms, midpoint approximation and interval approximation, for construction of efficient model abstractions with uncertainty in data. We evaluate computational feasibility by posing queries in computation tree logic (CTL) on a prototype of extracellular-signal-regulated kinase (ERK) pathway.
Unconditional security of quantum key distribution and the uncertainty principle
Koashi, Masato
2006-01-01
An approach to the unconditional security of quantum key distribution protocols is presented, which is based on the uncertainty principle. The approach applies to every case that has been treated via the argument by Shor and Preskill, but it is not necessary to find quantum error correcting codes. It can also treat the cases with uncharacterized apparatuses. The proof can be applied to cases where the secret key rate is larger than the distillable entanglement
Management of internal communication in times of uncertainty
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)
Implementation of unscented transform to estimate the uncertainty of a liquid flow standard system
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.
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
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.
Handbook of management under uncertainty
2001-01-01
A mere few years ago it would have seemed odd to propose a Handbook on the treatment of management problems within a sphere of uncertainty. Even today, on the threshold of the third millennium, this statement may provoke a certain wariness. In fact, to resort to exact or random data, that is probable date, is quite normal and con venient, as we then know where we are going best, where we are proposing to go if all occurs as it is conceived and hoped for. To treat uncertain information, to accept a new principle and from there determined criteria, without being sure of oneself and confiding only in the will to better understand objects and phenomena, constitutes and compromise with a new form of understanding the behaviour of current beings that goes even further than simple rationality. Economic Science and particularly the use of its elements of configuration in the world of management, has imbued several generations with an analytical spirit that has given rise to the elaboration of theories widely accept...
Perceptual uncertainty supports design reasoning
Tseng, Winger S. W.
2018-06-01
The unstructured, ambiguous figures used as design cues in the experiment were classified as being at high, moderate, and low ambiguity. Participants were required to use the ideas suggested by the visual cues to design a novel table. Results showed that different levels of ambiguity within the cues significantly influenced the quantity of idea development of expert designers, but not novice designers, whose idea generation remained relatively low across all levels of ambiguity. For experts, as the level of ambiguity in the cue increased so did the number of design ideas that were generated. Most design interpretations created by both experts and novices were affected by geometric contours within the figures. In addition, when viewing cues of high ambiguity, experts produced more interpretative transformations than when viewing cues of moderate or low ambiguity. Furthermore, experts produced significantly more new functions or meanings than novices. We claim that increased ambiguity within presented visual cues engenders uncertainty in designers that facilitates flexible transformations and interpretations that prevent premature commitment to uncreative solutions. Such results could be applied in design learning and education, focused on differences between experts and novices, to generalize the principles and strategies of interpretations by experts during concept sketching to train novices when face design problems, and the development of CACD tools to support designers.
Evaluation of uncertainty in dosimetry of irradiator system
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
Model uncertainties in top-quark physics
Seidel, Markus
2014-01-01
The ATLAS and CMS collaborations at the Large Hadron Collider (LHC) are studying the top quark in pp collisions at 7 and 8 TeV. Due to the large integrated luminosity, precision measurements of production cross-sections and properties are often limited by systematic uncertainties. An overview of the modeling uncertainties for simulated events is given in this report.
Accounting for uncertainty in marine reserve design.
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.
Nonclassicality in phase-number uncertainty relations
Matia-Hernando, Paloma; Luis, Alfredo
2011-01-01
We show that there are nonclassical states with lesser joint fluctuations of phase and number than any classical state. This is rather paradoxical since one would expect classical coherent states to be always of minimum uncertainty. The same result is obtained when we replace phase by a phase-dependent field quadrature. Number and phase uncertainties are assessed using variance and Holevo relation.
Nonclassicality in phase-number uncertainty relations
Matia-Hernando, Paloma; Luis, Alfredo [Departamento de Optica, Facultad de Ciencias Fisicas, Universidad Complutense, 28040 Madrid (Spain)
2011-12-15
We show that there are nonclassical states with lesser joint fluctuations of phase and number than any classical state. This is rather paradoxical since one would expect classical coherent states to be always of minimum uncertainty. The same result is obtained when we replace phase by a phase-dependent field quadrature. Number and phase uncertainties are assessed using variance and Holevo relation.
CEC/USDOE workshop on uncertainty analysis
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
Stochastic variational approach to minimum uncertainty states
Illuminati, F.; Viola, L. [Dipartimento di Fisica, Padova Univ. (Italy)
1995-05-21
We introduce a new variational characterization of Gaussian diffusion processes as minimum uncertainty states. We then define a variational method constrained by kinematics of diffusions and Schroedinger dynamics to seek states of local minimum uncertainty for general non-harmonic potentials. (author)
On treatment of uncertainty in system planning
Flage, R.; Aven, T.
2009-01-01
In system planning and operation considerable efforts and resources are spent to reduce uncertainties, as a part of project management, uncertainty management and safety management. The basic idea seems to be that uncertainties are purely negative and should be reduced. In this paper we challenge this way of thinking, using a common industry practice as an example. In accordance with this industry practice, three uncertainty interval categories are used: ±40% intervals for the feasibility phase, ±30% intervals for the concept development phase and ±20% intervals for the engineering phase. The problem is that such a regime could easily lead to a conservative management regime encouraging the use of existing methods and tools, as new activities and novel solutions and arrangements necessarily mean increased uncertainties. In the paper we suggest an alternative approach based on uncertainty and risk descriptions, but having no predefined uncertainty reduction structures. The approach makes use of risk assessments and economic optimisation tools such as the expected net present value, but acknowledges the need for broad risk management processes which extend beyond the analyses. Different concerns need to be balanced, including economic aspects, uncertainties and risk, and practicability
Wastewater treatment modelling: dealing with uncertainties
Belia, E.; Amerlinck, Y.; Benedetti, L.
2009-01-01
This paper serves as a problem statement of the issues surrounding uncertainty in wastewater treatment modelling. The paper proposes a structure for identifying the sources of uncertainty introduced during each step of an engineering project concerned with model-based design or optimisation...
Framework for managing uncertainty in property projects
Reymen, I.M.M.J.; Dewulf, G.P.M.R.; Blokpoel, S.B.
2008-01-01
A primary task of property development (or real estate development, RED) is making assessments and managing risks and uncertainties. Property managers cope with a wide range of uncertainties, particularly in the early project phases. Although the existing literature addresses the management of
Uncertainty Propagation in an Ecosystem Nutrient Budget.
New aspects and advancements in classical uncertainty propagation methods were used to develop a nutrient budget with associated error for a northern Gulf of Mexico coastal embayment. Uncertainty was calculated for budget terms by propagating the standard error and degrees of fr...
Repeated checking induces uncertainty about future threat
Giele, C.L.|info:eu-repo/dai/nl/318754460; Engelhard, I.M.|info:eu-repo/dai/nl/239681533; van den Hout, M.A.|info:eu-repo/dai/nl/070445354; Dek, E.C.P.|info:eu-repo/dai/nl/313959552; Damstra, Marianne; Douma, Ellen
2015-01-01
Studies have shown that obsessive-compulsive (OC) -like repeated checking paradoxically increases memory uncertainty. This study tested if checking also induces uncertainty about future threat by impairing the distinction between danger and safety cues. Participants (n = 54) engaged in a simulated
Handling uncertainty through adaptiveness in planning approaches
Zandvoort, M.; Vlist, van der M.J.; Brink, van den A.
2018-01-01
Planners and water managers seek to be adaptive to handle uncertainty through the use of planning approaches. In this paper, we study what type of adaptiveness is proposed and how this may be operationalized in planning approaches to adequately handle different uncertainties. We took a
Use of uncertainty data in neutron dosimetry
Greenwood, L.R.
1980-01-01
Uncertainty and covariance data are required for neutron activation cross sections and nuclear decay data used to adjust neutron flux spectra measured at accelerators and reactors. Covariances must be evaluated in order to assess errors in derived damage parameters, such as nuclear displacements. The primary sources of error are discussed along with needed improvements in presently available uncertainty data
Section summary: Uncertainty and design considerations
Stephen Hagen
2013-01-01
Well planned sampling designs and robust approaches to estimating uncertainty are critical components of forest monitoring. The importance of uncertainty estimation increases as deforestation and degradation issues become more closely tied to financing incentives for reducing greenhouse gas emissions in the forest sector. Investors like to know risk and risk is tightly...
Gamma-Ray Telescope and Uncertainty Principle
Shivalingaswamy, T.; Kagali, B. A.
2012-01-01
Heisenberg's Uncertainty Principle is one of the important basic principles of quantum mechanics. In most of the books on quantum mechanics, this uncertainty principle is generally illustrated with the help of a gamma ray microscope, wherein neither the image formation criterion nor the lens properties are taken into account. Thus a better…
Error and uncertainty in scientific practice
Boumans, M.; Hon, G.; Petersen, A.C.
2014-01-01
Assessment of error and uncertainty is a vital component of both natural and social science. Empirical research involves dealing with all kinds of errors and uncertainties, yet there is significant variance in how such results are dealt with. Contributors to this volume present case studies of
Inflation and Inflation Uncertainty in Turkey
dogru, bulent
2014-01-01
Abstract: In this study, the relationship between inflation and inflation uncertainty is analyzed using Granger causality tests with annual inflation series covering the time period 1923 to 2012 for Turkish Economy. Inflation uncertainty is measured by Exponential Generalized Autoregressive Conditional Heteroskedastic model. Econometric findings suggest that although in long run the Friedman's hypothesis that high inflation increases inflation ...
Comparing uncertainty aversion towards different sources
Baillon, Aurélien; Liu, Ning; van Dolder, Dennie
2017-01-01
We propose simple behavioral definitions of comparative uncertainty aversion for a single agent towards different sources of uncertainty. Our definitions allow for the comparison of utility curvature for different sources if the agent’s choices satisfy subjective expected utility towards each
Operational Flexibility Responses to Environmental Uncertainties
Miller, Kent D.
1994-01-01
This study develops and tests a behavioral model of organizational changes in operational flexibility. Regression results using an international data set provide strong support for the general proposition that uncertainties associated with different environmental components--poitical, government policy, macroeconomic, competitive, input and product demand uncertainties--have different implications for firm internal, locational, and supploer flexibility. Slack acts as a buffer attenuating, a...
The Stock Market: Risk vs. Uncertainty.
Griffitts, Dawn
2002-01-01
This economics education publication focuses on the U.S. stock market and the risk and uncertainty that an individual faces when investing in the market. The material explains that risk and uncertainty relate to the same underlying concept randomness. It defines and discusses both concepts and notes that although risk is quantifiable, uncertainty…
Predictive uncertainty in auditory sequence processing
Hansen, Niels Chr.; Pearce, Marcus T
2014-01-01
in a melodic sequence (inferred uncertainty). Finally, we simulate listeners' perception of expectedness and uncertainty using computational models of auditory expectation. A detailed model comparison indicates which model parameters maximize fit to the data and how they compare to existing models...
Refinement of the concept of uncertainty.
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.
Worry, Intolerance of Uncertainty, and Statistics Anxiety
Williams, Amanda S.
2013-01-01
Statistics anxiety is a problem for most graduate students. This study investigates the relationship between intolerance of uncertainty, worry, and statistics anxiety. Intolerance of uncertainty was significantly related to worry, and worry was significantly related to three types of statistics anxiety. Six types of statistics anxiety were…
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.
Potential effects of organizational uncertainty on safety
Durbin, N.E.; Lekberg, A.; Melber, B.D.
2001-12-01
When organizations face significant change - reorganization, mergers, acquisitions, down sizing, plant closures or decommissioning - both the organizations and the workers in those organizations experience significant uncertainty about the future. This uncertainty affects the organization and the people working in the organization - adversely affecting morale, reducing concentration on safe operations, and resulting in the loss of key staff. Hence, organizations, particularly those using high risk technologies, which are facing significant change need to consider and plan for the effects of organizational uncertainty on safety - as well as planning for other consequences of change - technical, economic, emotional, and productivity related. This paper reviews some of what is known about the effects of uncertainty on organizations and individuals, discusses the potential consequences of uncertainty on organizational and individual behavior, and presents some of the implications for safety professionals
Decay heat uncertainty quantification of MYRRHA
Fiorito Luca
2017-01-01
Full Text Available MYRRHA is a lead-bismuth cooled MOX-fueled accelerator driven system (ADS currently in the design phase at SCK·CEN in Belgium. The correct evaluation of the decay heat and of its uncertainty level is very important for the safety demonstration of the reactor. In the first part of this work we assessed the decay heat released by the MYRRHA core using the ALEPH-2 burnup code. The second part of the study focused on the nuclear data uncertainty and covariance propagation to the MYRRHA decay heat. Radioactive decay data, independent fission yield and cross section uncertainties/covariances were propagated using two nuclear data sampling codes, namely NUDUNA and SANDY. According to the results, 238U cross sections and fission yield data are the largest contributors to the MYRRHA decay heat uncertainty. The calculated uncertainty values are deemed acceptable from the safety point of view as they are well within the available regulatory limits.
Uncertainty relation and probability. Numerical illustration
Fujikawa, Kazuo; Umetsu, Koichiro
2011-01-01
The uncertainty relation and the probability interpretation of quantum mechanics are intrinsically connected, as is evidenced by the evaluation of standard deviations. It is thus natural to ask if one can associate a very small uncertainty product of suitably sampled events with a very small probability. We have shown elsewhere that some examples of the evasion of the uncertainty relation noted in the past are in fact understood in this way. We here numerically illustrate that a very small uncertainty product is realized if one performs a suitable sampling of measured data that occur with a very small probability. We introduce a notion of cyclic measurements. It is also shown that our analysis is consistent with the Landau-Pollak-type uncertainty relation. It is suggested that the present analysis may help reconcile the contradicting views about the 'standard quantum limit' in the detection of gravitational waves. (author)
Potential effects of organizational uncertainty on safety
Durbin, N.E. [MPD Consulting Group, Kirkland, WA (United States); Lekberg, A. [Swedish Nuclear Power Inspectorate, Stockholm (Sweden); Melber, B.D. [Melber Consulting, Seattle WA (United States)
2001-12-01
When organizations face significant change - reorganization, mergers, acquisitions, down sizing, plant closures or decommissioning - both the organizations and the workers in those organizations experience significant uncertainty about the future. This uncertainty affects the organization and the people working in the organization - adversely affecting morale, reducing concentration on safe operations, and resulting in the loss of key staff. Hence, organizations, particularly those using high risk technologies, which are facing significant change need to consider and plan for the effects of organizational uncertainty on safety - as well as planning for other consequences of change - technical, economic, emotional, and productivity related. This paper reviews some of what is known about the effects of uncertainty on organizations and individuals, discusses the potential consequences of uncertainty on organizational and individual behavior, and presents some of the implications for safety professionals.
Some reflections on uncertainty analysis and management
Aven, Terje
2010-01-01
A guide to quantitative uncertainty analysis and management in industry has recently been issued. The guide provides an overall framework for uncertainty modelling and characterisations, using probabilities but also other uncertainty representations (including the Dempster-Shafer theory). A number of practical applications showing how to use the framework are presented. The guide is considered as an important contribution to the field, but there is a potential for improvements. These relate mainly to the scientific basis and clarification of critical issues, for example, concerning the meaning of a probability and the concept of model uncertainty. A reformulation of the framework is suggested using probabilities as the only representation of uncertainty. Several simple examples are included to motivate and explain the basic ideas of the modified framework.
Measuring uncertainty within the theory of evidence
Salicone, Simona
2018-01-01
This monograph considers the evaluation and expression of measurement uncertainty within the mathematical framework of the Theory of Evidence. With a new perspective on the metrology science, the text paves the way for innovative applications in a wide range of areas. Building on Simona Salicone’s Measurement Uncertainty: An Approach via the Mathematical Theory of Evidence, the material covers further developments of the Random Fuzzy Variable (RFV) approach to uncertainty and provides a more robust mathematical and metrological background to the combination of measurement results that leads to a more effective RFV combination method. While the first part of the book introduces measurement uncertainty, the Theory of Evidence, and fuzzy sets, the following parts bring together these concepts and derive an effective methodology for the evaluation and expression of measurement uncertainty. A supplementary downloadable program allows the readers to interact with the proposed approach by generating and combining ...
Uncertainty for Part Density Determination: An Update
Valdez, Mario Orlando [Los Alamos National Laboratory
2016-12-14
Accurate and precise density measurements by hydrostatic weighing requires the use of an analytical balance, configured with a suspension system, to both measure the weight of a part in water and in air. Additionally, the densities of these liquid media (water and air) must be precisely known for the part density determination. To validate the accuracy and precision of these measurements, uncertainty statements are required. The work in this report is a revision of an original report written more than a decade ago, specifically applying principles and guidelines suggested by the Guide to the Expression of Uncertainty in Measurement (GUM) for determining the part density uncertainty through sensitivity analysis. In this work, updated derivations are provided; an original example is revised with the updated derivations and appendix, provided solely to uncertainty evaluations using Monte Carlo techniques, specifically using the NIST Uncertainty Machine, as a viable alternative method.
Balancing certainty and uncertainty in clinical medicine.
Hayward, Richard
2006-01-01
Nothing in clinical medicine is one hundred per cent certain. Part of a doctor's education involves learning how to cope with the anxiety that uncertainty in decisions affecting life and death inevitably produces. This paper examines: (1) the role of anxiety -- both rational and irrational -- in the provision of health care; (2) the effects of uncertainty upon the doctor-patient relationship; (3) the threat uncertainty poses to medical authority (and the assumption of infallibility that props it up); (4) the contribution of clinical uncertainty to the rising popularity of alternative therapies; and (5) the clash between the medical and the legal understanding of how certainty should be defined, particularly as it affects the paediatric community. It concludes by suggesting some strategies that might facilitate successful navigation between the opposing and ever-present forces of certainty and uncertainty.
Habitable zone dependence on stellar parameter uncertainties
Kane, Stephen R.
2014-01-01
An important property of exoplanetary systems is the extent of the Habitable Zone (HZ), defined as that region where water can exist in a liquid state on the surface of a planet with sufficient atmospheric pressure. Both ground- and space-based observations have revealed a plethora of confirmed exoplanets and exoplanetary candidates, most notably from the Kepler mission using the transit detection technique. Many of these detected planets lie within the predicted HZ of their host star. However, as is the case with the derived properties of the planets themselves, the HZ boundaries depend on how well we understand the host star. Here we quantify the uncertainties of HZ boundaries on the parameter uncertainties of the host star. We examine the distribution of stellar parameter uncertainties from confirmed exoplanet hosts and Kepler candidate hosts and translate these into HZ boundary uncertainties. We apply this to several known systems with an HZ planet to determine the uncertainty in their HZ status.
Habitable zone dependence on stellar parameter uncertainties
Kane, Stephen R., E-mail: skane@sfsu.edu [Department of Physics and Astronomy, San Francisco State University, 1600 Holloway Avenue, San Francisco, CA 94132 (United States)
2014-02-20
An important property of exoplanetary systems is the extent of the Habitable Zone (HZ), defined as that region where water can exist in a liquid state on the surface of a planet with sufficient atmospheric pressure. Both ground- and space-based observations have revealed a plethora of confirmed exoplanets and exoplanetary candidates, most notably from the Kepler mission using the transit detection technique. Many of these detected planets lie within the predicted HZ of their host star. However, as is the case with the derived properties of the planets themselves, the HZ boundaries depend on how well we understand the host star. Here we quantify the uncertainties of HZ boundaries on the parameter uncertainties of the host star. We examine the distribution of stellar parameter uncertainties from confirmed exoplanet hosts and Kepler candidate hosts and translate these into HZ boundary uncertainties. We apply this to several known systems with an HZ planet to determine the uncertainty in their HZ status.
Background and Qualification of Uncertainty Methods
D'Auria, F.; Petruzzi, A.
2008-01-01
The evaluation of uncertainty constitutes the necessary supplement of Best Estimate calculations performed to understand accident scenarios in water cooled nuclear reactors. The needs come from the imperfection of computational tools on the one side and from the interest in using such tool to get more precise evaluation of safety margins. The paper reviews the salient features of two independent approaches for estimating uncertainties associated with predictions of complex system codes. Namely the propagation of code input error and the propagation of the calculation output error constitute the key-words for identifying the methods of current interest for industrial applications. Throughout the developed methods, uncertainty bands can be derived (both upper and lower) for any desired quantity of the transient of interest. For the second case, the uncertainty method is coupled with the thermal-hydraulic code to get the Code with capability of Internal Assessment of Uncertainty, whose features are discussed in more detail.
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.
The legal status of Uncertainty
Altamura, M.; Ferraris, L.; Miozzo, D.; Musso, L.; Siccardi, F.
2011-03-01
An exponential improvement of numerical weather prediction (NWP) models was observed during the last decade (Lynch, 2008). Civil Protection (CP) systems exploited Meteo services in order to redeploy their actions towards the prediction and prevention of events rather than towards an exclusively response-oriented mechanism1. Nevertheless, experience tells us that NWP models, even if assisted by real time observations, are far from being deterministic. Complications frequently emerge in medium to long range forecasting, which are subject to sudden modifications. On the other hand, short term forecasts, if seen through the lens of criminal trials2, are to the same extent, scarcely reliable (Molini et al., 2009). One particular episode related with wrong forecasts, in the Italian panorama, has deeply frightened CP operators as the NWP model in force missed a meteorological adversity which, in fact, caused death and dealt severe damage in the province of Vibo Valentia (2006). This event turned into a very discussed trial, lasting over three years, and intended against whom assumed the legal position of guardianship within the CP. A first set of data is now available showing that in concomitance with the trial of Vibo Valentia the number of alerts issued raised almost three folds. We sustain the hypothesis that the beginning of the process of overcriminalization (Husak, 2008) of CPs is currently increasing the number of false alerts with the consequent effect of weakening alert perception and response by the citizenship (Brezntiz, 1984). The common misunderstanding of such an issue, i.e. the inherent uncertainty in weather predictions, mainly by prosecutors and judges, and generally by whom deals with law and justice, is creating the basis for a defensive behaviour3 within CPs. This paper intends, thus, to analyse the social and legal relevance of uncertainty in the process of issuing meteo-hydrological alerts by CPs. Footnotes: 1 The Italian Civil Protection is working
The legal status of Uncertainty
M. Altamura
2011-03-01
Full Text Available An exponential improvement of numerical weather prediction (NWP models was observed during the last decade (Lynch, 2008. Civil Protection (CP systems exploited Meteo services in order to redeploy their actions towards the prediction and prevention of events rather than towards an exclusively response-oriented mechanism^{1}.
Nevertheless, experience tells us that NWP models, even if assisted by real time observations, are far from being deterministic. Complications frequently emerge in medium to long range forecasting, which are subject to sudden modifications. On the other hand, short term forecasts, if seen through the lens of criminal trials^{2}, are to the same extent, scarcely reliable (Molini et al., 2009.
One particular episode related with wrong forecasts, in the Italian panorama, has deeply frightened CP operators as the NWP model in force missed a meteorological adversity which, in fact, caused death and dealt severe damage in the province of Vibo Valentia (2006. This event turned into a very discussed trial, lasting over three years, and intended against whom assumed the legal position of guardianship within the CP. A first set of data is now available showing that in concomitance with the trial of Vibo Valentia the number of alerts issued raised almost three folds. We sustain the hypothesis that the beginning of the process of overcriminalization (Husak, 2008 of CPs is currently increasing the number of false alerts with the consequent effect of weakening alert perception and response by the citizenship (Brezntiz, 1984.
The common misunderstanding of such an issue, i.e. the inherent uncertainty in weather predictions, mainly by prosecutors and judges, and generally by whom deals with law and justice, is creating the basis for a defensive behaviour^{3} within CPs. This paper intends, thus, to analyse the social and legal relevance of uncertainty in the process of issuing
Uncertainty analysis in Monte Carlo criticality computations
Qi Ao
2011-01-01
Highlights: ► Two types of uncertainty methods for k eff Monte Carlo computations are examined. ► Sampling method has the least restrictions on perturbation but computing resources. ► Analytical method is limited to small perturbation on material properties. ► Practicality relies on efficiency, multiparameter applicability and data availability. - Abstract: Uncertainty analysis is imperative for nuclear criticality risk assessments when using Monte Carlo neutron transport methods to predict the effective neutron multiplication factor (k eff ) for fissionable material systems. For the validation of Monte Carlo codes for criticality computations against benchmark experiments, code accuracy and precision are measured by both the computational bias and uncertainty in the bias. The uncertainty in the bias accounts for known or quantified experimental, computational and model uncertainties. For the application of Monte Carlo codes for criticality analysis of fissionable material systems, an administrative margin of subcriticality must be imposed to provide additional assurance of subcriticality for any unknown or unquantified uncertainties. Because of a substantial impact of the administrative margin of subcriticality on economics and safety of nuclear fuel cycle operations, recently increasing interests in reducing the administrative margin of subcriticality make the uncertainty analysis in criticality safety computations more risk-significant. This paper provides an overview of two most popular k eff uncertainty analysis methods for Monte Carlo criticality computations: (1) sampling-based methods, and (2) analytical methods. Examples are given to demonstrate their usage in the k eff uncertainty analysis due to uncertainties in both neutronic and non-neutronic parameters of fissionable material systems.
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
Uncertainty in relative cost investigation
Bunn, D.; Viahos, K.
1989-01-01
One of the consequences of the privatization of the Central Electricity Generating Board has been a weakening of the economic case for nuclear generation over coal. Nuclear has higher capital, but lower operating costs than coal and is therefore favoured in capital budgeting by discounting at lower rates of return. In the Sizewell case (in 1987), discounting at the public sector rate of 5 per cent favoured nuclear. However, the private sector will require higher rates of return, thus rendering nuclear less attractive. Hence the imposition by the government of a diversity constraint on the privatized industry to ensure that contracts are made for a minimum fraction of non-fossil (essentially nuclear) energy. An electricity capacity planning model was developed to estimate the costs of imposing various non-fossil energy constraints on the planning decision of a privatized electricity supply industry, as a function of various discount rates. Using a large-scale linear programming technique, the model optimizes over a 50 year horizon the schedule of installation, and mix of generating capacity, both with and without a minimum non-fossil constraint. The conclusion is that the opportunity cost of diversity may be a complex joint substation of more than one type of plant (eg coal and gas) depending on the discount rate. (author)
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.
Estimation of the uncertainties considered in NPP PSA level 2
Kalchev, B.; Hristova, R.
2005-01-01
The main approaches of the uncertainties analysis are presented. The sources of uncertainties which should be considered in PSA level 2 for WWER reactor such as: uncertainties propagated from level 1 PSA; uncertainties in input parameters; uncertainties related to the modelling of physical phenomena during the accident progression and uncertainties related to the estimation of source terms are defined. The methods for estimation of the uncertainties are also discussed in this paper
Uncertainty analysis for geologic disposal of radioactive waste
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
Sibling Dependence, Uncertainty and Education
Lilleør, Helene Bie
in the educational decision, which is consistent with a human capital portfolio theory of risk diversification and which cannot be explained by sibling rivalry over scarce resources for credit constrained households. The paper thus provides a complementary explanation to why enrolment rates in developing countries......Primary school enrolment rates are continuously low in many developing countries. The main explanation in the economic literature on schooling is focused on credit constraints and child labour, implying that the indirect cost of schooling in terms of foregone earnings is too high. This paper...
The state of the art of the impact of sampling uncertainty on measurement uncertainty
Leite, V. J.; Oliveira, E. C.
2018-03-01
The measurement uncertainty is a parameter that marks the reliability and can be divided into two large groups: sampling and analytical variations. Analytical uncertainty is a controlled process, performed in the laboratory. The same does not occur with the sampling uncertainty, which, because it faces several obstacles and there is no clarity on how to perform the procedures, has been neglected, although it is admittedly indispensable to the measurement process. This paper aims at describing the state of the art of sampling uncertainty and at assessing its relevance to measurement uncertainty.
Linepack storage valuation under price uncertainty
Arvesen, Ø.; Medbø, V.; Fleten, S.-E.; Tomasgard, A.; Westgaard, S.
2013-01-01
Natural gas flows in pipelines as a consequence of the pressure difference at the inlet and outlet. Adjusting these pressures makes it possible to inject natural gas at one rate and withdraw at a different rate, hence using the pipeline as storage as well as transport. We study the value of using the so called pipeline linepack as a short-term gas storage and how this functionality may offset the discrepancy between the low flexibility in take-or-pay contracts and the high inherent flexibility of a gas-fired power plant. To value the storage option, we consider a cycling power plant facing volatile power prices while purchasing gas on a take-or-pay contract. We estimate a Markov regime-switching model for power prices and a mean reverting jump diffusion model for gas prices. Applying Least Squares Monte Carlo simulation to the operation of the linepack storage, we find that the storage option indeed has significant value for the plant, enabling it to better exploit the sometimes extreme price fluctuations. Finally, we show how power price volatility and jump frequency are the main value drivers, and that the size of the storage increases the value up to a point where no additional flexibility is used. - Highlights: ► Linepack, i.e., storage of natural gas en route in long pipelines, is valued for the first time. ► We find significant storage value for a North Sea case and a German gas-fired power plant. ► Power and natural gas prices are modelled realistically, as related stochastic processes with mean reversion and spikes. ► Storage operation is valued under uncertainty yielding close to exact values, without heuristics
Towards quantifying uncertainty in predictions of Amazon 'dieback'.
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
Sensitivity and uncertainty studies of the CRAC2 computer code
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
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.
Results from the Application of Uncertainty Methods in the CSNI Uncertainty Methods Study (UMS)
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.
[Influence of Uncertainty and Uncertainty Appraisal on Self-management in Hemodialysis Patients].
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.
Planning ATES systems under uncertainty
Jaxa-Rozen, Marc; Kwakkel, Jan; Bloemendal, Martin
2015-04-01
form a complex adaptive system, for which agent-based modelling provides a useful analysis framework. This study therefore explores the interactions between endogenous ATES adoption processes and the relative performance of different planning schemes, using an agent-based adoption model coupled with a hydrologic model of the subsurface. The models are parameterized to simulate typical operating conditions for ATES systems in a dense urban area. Furthermore, uncertainties relating to planning parameters, adoption processes, and climactic conditions are explicitly considered using exploratory modelling techniques. Results are therefore presented for the performance of different planning policies over a broad range of plausible scenarios.
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
Determination of uncertainties in energy and exergy analysis of a power plant
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
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.
Uncertainties in Forecasting Streamflow using Entropy Theory
Cui, H.; Singh, V. P.
2017-12-01
Streamflow forecasting is essential in river restoration, reservoir operation, power generation, irrigation, navigation, and water management. However, there is always uncertainties accompanied in forecast, which may affect the forecasting results and lead to large variations. Therefore, uncertainties must be considered and be assessed properly when forecasting streamflow for water management. The aim of our work is to quantify the uncertainties involved in forecasting streamflow and provide reliable streamflow forecast. Despite that streamflow time series are stochastic, they exhibit seasonal and periodic patterns. Therefore, streamflow forecasting entails modeling seasonality, periodicity, and its correlation structure, and assessing uncertainties. This study applies entropy theory to forecast streamflow and measure uncertainties during the forecasting process. To apply entropy theory for streamflow forecasting, spectral analysis is combined to time series analysis, as spectral analysis can be employed to characterize patterns of streamflow variation and identify the periodicity of streamflow. That is, it permits to extract significant information for understanding the streamflow process and prediction thereof. Application of entropy theory for streamflow forecasting involves determination of spectral density, determination of parameters, and extension of autocorrelation function. The uncertainties brought by precipitation input, forecasting model and forecasted results are measured separately using entropy. With information theory, how these uncertainties transported and aggregated during these processes will be described.
Uncertainty in hydraulic tests in fractured rock
Ji, Sung-Hoon; Koh, Yong-Kwon
2014-01-01
Interpretation of hydraulic tests in fractured rock has uncertainty because of the different hydraulic properties of a fractured rock to a porous medium. In this study, we reviewed several interesting phenomena which show uncertainty in a hydraulic test at a fractured rock and discussed their origins and the how they should be considered during site characterisation. Our results show that the estimated hydraulic parameters of a fractured rock from a hydraulic test are associated with uncertainty due to the changed aperture and non-linear groundwater flow during the test. Although the magnitude of these two uncertainties is site-dependent, the results suggest that it is recommended to conduct a hydraulic test with a little disturbance from the natural groundwater flow to consider their uncertainty. Other effects reported from laboratory and numerical experiments such as the trapping zone effect (Boutt, 2006) and the slip condition effect (Lee, 2014) can also introduce uncertainty to a hydraulic test, which should be evaluated in a field test. It is necessary to consider the way how to evaluate the uncertainty in the hydraulic property during the site characterisation and how to apply it to the safety assessment of a subsurface repository. (authors)
Resolving uncertainty in chemical speciation determinations
Smith, D. Scott; Adams, Nicholas W. H.; Kramer, James R.
1999-10-01
Speciation determinations involve uncertainty in system definition and experimentation. Identification of appropriate metals and ligands from basic chemical principles, analytical window considerations, types of species and checking for consistency in equilibrium calculations are considered in system definition uncertainty. A systematic approach to system definition limits uncertainty in speciation investigations. Experimental uncertainty is discussed with an example of proton interactions with Suwannee River fulvic acid (SRFA). A Monte Carlo approach was used to estimate uncertainty in experimental data, resulting from the propagation of uncertainties in electrode calibration parameters and experimental data points. Monte Carlo simulations revealed large uncertainties present at high (>9-10) and low (monoprotic ligands. Least-squares fit the data with 21 sites, whereas linear programming fit the data equally well with 9 sites. Multiresponse fitting, involving simultaneous fluorescence and pH measurements, improved model discrimination. Deconvolution of the excitation versus emission fluorescence surface for SRFA establishes a minimum of five sites. Diprotic sites are also required for the five fluorescent sites, and one non-fluorescent monoprotic site was added to accommodate the pH data. Consistent with greater complexity, the multiresponse method had broader confidence limits than the uniresponse methods, but corresponded better with the accepted total carboxylic content for SRFA. Overall there was a 40% standard deviation in total carboxylic content for the multiresponse fitting, versus 10% and 1% for least-squares and linear programming, respectively.
Uncertainty and global climate change research
Tonn, B.E. [Oak Ridge National Lab., TN (United States); Weiher, R. [National Oceanic and Atmospheric Administration, Boulder, CO (United States)
1994-06-01
The Workshop on Uncertainty and Global Climate Change Research March 22--23, 1994, in Knoxville, Tennessee. This report summarizes the results and recommendations of the workshop. The purpose of the workshop was to examine in-depth the concept of uncertainty. From an analytical point of view, uncertainty is a central feature of global climate science, economics and decision making. The magnitude and complexity of uncertainty surrounding global climate change has made it quite difficult to answer even the most simple and important of questions-whether potentially costly action is required now to ameliorate adverse consequences of global climate change or whether delay is warranted to gain better information to reduce uncertainties. A major conclusion of the workshop is that multidisciplinary integrated assessments using decision analytic techniques as a foundation is key to addressing global change policy concerns. First, uncertainty must be dealt with explicitly and rigorously since it is and will continue to be a key feature of analysis and recommendations on policy questions for years to come. Second, key policy questions and variables need to be explicitly identified, prioritized, and their uncertainty characterized to guide the entire scientific, modeling, and policy analysis process. Multidisciplinary integrated assessment techniques and value of information methodologies are best suited for this task. In terms of timeliness and relevance of developing and applying decision analytic techniques, the global change research and policy communities are moving rapidly toward integrated approaches to research design and policy analysis.
[Dealing with diagnostic uncertainty in general practice].
Wübken, Magdalena; Oswald, Jana; Schneider, Antonius
2013-01-01
In general, the prevalence of diseases is low in primary care. Therefore, the positive predictive value of diagnostic tests is lower than in hospitals where patients are highly selected. In addition, the patients present with milder forms of disease; and many diseases might hide behind the initial symptom(s). These facts lead to diagnostic uncertainty which is somewhat inherent to general practice. This narrative review discusses different sources of and reasons for uncertainty and strategies to deal with it in the context of the current literature. Fear of uncertainty correlates with higher diagnostic activities. The attitude towards uncertainty correlates with the choice of medical speciality by vocational trainees or medical students. An intolerance of uncertainty, which still increases as medicine is making steady progress, might partly explain the growing shortage of general practitioners. The bio-psycho-social context appears to be important to diagnostic decision-making. The effect of intuition and heuristics are investigated by cognitive psychologists. It is still unclear whether these aspects are prone to bias or useful, which might depend on the context of medical decisions. Good communication is of great importance to share uncertainty with the patients in a transparent way and to alleviate shared decision-making. Dealing with uncertainty should be seen as an important core component of general practice and needs to be investigated in more detail to improve the respective medical decisions. Copyright © 2013. Published by Elsevier GmbH.
Approach to uncertainty in risk analysis
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.
Lognormal Approximations of Fault Tree Uncertainty Distributions.
El-Shanawany, Ashraf Ben; Ardron, Keith H; Walker, Simon P
2018-01-26
Fault trees are used in reliability modeling to create logical models of fault combinations that can lead to undesirable events. The output of a fault tree analysis (the top event probability) is expressed in terms of the failure probabilities of basic events that are input to the model. Typically, the basic event probabilities are not known exactly, but are modeled as probability distributions: therefore, the top event probability is also represented as an uncertainty distribution. Monte Carlo methods are generally used for evaluating the uncertainty distribution, but such calculations are computationally intensive and do not readily reveal the dominant contributors to the uncertainty. In this article, a closed-form approximation for the fault tree top event uncertainty distribution is developed, which is applicable when the uncertainties in the basic events of the model are lognormally distributed. The results of the approximate method are compared with results from two sampling-based methods: namely, the Monte Carlo method and the Wilks method based on order statistics. It is shown that the closed-form expression can provide a reasonable approximation to results obtained by Monte Carlo sampling, without incurring the computational expense. The Wilks method is found to be a useful means of providing an upper bound for the percentiles of the uncertainty distribution while being computationally inexpensive compared with full Monte Carlo sampling. The lognormal approximation method and Wilks's method appear attractive, practical alternatives for the evaluation of uncertainty in the output of fault trees and similar multilinear models. © 2018 Society for Risk Analysis.
Approach to uncertainty in risk analysis
Rish, W.R.
1988-08-01
In the Fall of 1985 EPA's Office of Radiation Programs (ORP) initiated a project to develop a formal approach to dealing with uncertainties encountered when estimating and evaluating risks to human health and the environment. Based on a literature review of modeling uncertainty, interviews with ORP technical and management staff, and input from experts on uncertainty analysis, a comprehensive approach was developed. This approach recognizes by design the constraints on budget, time, manpower, expertise, and availability of information often encountered in ''real world'' modeling. It is based on the observation that in practice risk modeling is usually done to support a decision process. As such, the approach focuses on how to frame a given risk modeling problem, how to use that framing to select an appropriate mixture of uncertainty analyses techniques, and how to integrate the techniques into an uncertainty assessment that effectively communicates important information and insight to decision-makers. The approach is presented in this report. Practical guidance on characterizing and analyzing uncertainties about model form and quantities and on effectively communicating uncertainty analysis results is included. Examples from actual applications are presented
Uncertainty estimation of ultrasonic thickness measurement
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)
Sediment Curve Uncertainty Estimation Using GLUE and Bootstrap Methods
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
Optimum sizing of wind-battery systems incorporating resource uncertainty
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)
Propagation of uncertainty and sensitivity analysis in an integral oil-gas plume model
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.
Improving the driver-automation interaction: an approach using automation uncertainty.
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.
Bayesian uncertainty analyses of probabilistic risk models
Pulkkinen, U.
1989-01-01
Applications of Bayesian principles to the uncertainty analyses are discussed in the paper. A short review of the most important uncertainties and their causes is provided. An application of the principle of maximum entropy to the determination of Bayesian prior distributions is described. An approach based on so called probabilistic structures is presented in order to develop a method of quantitative evaluation of modelling uncertainties. The method is applied to a small example case. Ideas for application areas for the proposed method are discussed
Managing Innovation In View Of The Uncertainties
Anton Igorevich Mosalev
2012-12-01
Full Text Available Study of the problems of uncertainty in innovation is at present the most up to date. Approaches to its definition, arranged primarily on the assumption and include the known parameters, which essentially is a game approach to the assessment. Address specific issues of governance of innovation in accounting uncertainty still remains open and the most relevant, especially when the innovation represented by one of the drivers of growth of national economies. This paper presents a methodological approach to determining the degree of uncertainty and an approach to the management of innovation through a system of mathematical modeling on the criterion of gross errors.
Quantification of uncertainties of modeling and simulation
Ma Zhibo; Yin Jianwei
2012-01-01
The principles of Modeling and Simulation (M and S) is interpreted by a functional relation, from which the total uncertainties of M and S are identified and sorted to three parts considered to vary along with the conceptual models' parameters. According to the idea of verification and validation, the space of the parameters is parted to verified and applied domains, uncertainties in the verified domain are quantified by comparison between numerical and standard results, and those in the applied domain are quantified by a newly developed extrapolating method. Examples are presented to demonstrate and qualify the ideas aimed to build a framework to quantify the uncertainties of M and S. (authors)
Uncertainties in Safety Analysis. A literature review
Ekberg, C.
1995-05-01
The purpose of the presented work has been to give a short summary of the origins of many uncertainties arising in the designing and performance assessment of a repository for spent nuclear fuel. Some different methods to treat these uncertainties is also included. The methods and conclusions are in many cases general in the sense that they are applicable to many other disciplines where simulations are used. As a conclusion it may be noted that uncertainties of different origin have been discussed and debated, but one large group, e.g. computer simulations, where the methods to make a more explicit investigation exists, have not been investigated in a satisfying way. 50 refs
Uncertainty: the Curate's egg in financial economics.
Pixley, Jocelyn
2014-06-01
Economic theories of uncertainty are unpopular with financial experts. As sociologists, we rightly refuse predictions, but the uncertainties of money are constantly sifted and turned into semi-denial by a financial economics set on somehow beating the future. Picking out 'bits' of the future as 'risk' and 'parts' as 'information' is attractive but socially dangerous, I argue, because money's promises are always uncertain. New studies of uncertainty are reversing sociology's neglect of the unavoidable inability to know the forces that will shape the financial future. © London School of Economics and Political Science 2014.
Believable statements of uncertainty and believable science
Lindstrom, R.M.
2017-01-01
Nearly 50 years ago, two landmark papers appeared that should have cured the problem of ambiguous uncertainty statements in published data. Eisenhart's paper in Science called for statistically meaningful numbers, and Currie's Analytical Chemistry paper revealed the wide range in common definitions of detection limit. Confusion and worse can result when uncertainties are misinterpreted or ignored. The recent stories of cold fusion, variable radioactive decay, and piezonuclear reactions provide cautionary examples in which prior probability has been neglected. We show examples from our laboratory and others to illustrate the fact that uncertainty depends on both statistical and scientific judgment. (author)
Uncertainties in Safety Analysis. A literature review
Ekberg, C [Chalmers Univ. of Technology, Goeteborg (Sweden). Dept. of Nuclear Chemistry
1995-05-01
The purpose of the presented work has been to give a short summary of the origins of many uncertainties arising in the designing and performance assessment of a repository for spent nuclear fuel. Some different methods to treat these uncertainties is also included. The methods and conclusions are in many cases general in the sense that they are applicable to many other disciplines where simulations are used. As a conclusion it may be noted that uncertainties of different origin have been discussed and debated, but one large group, e.g. computer simulations, where the methods to make a more explicit investigation exists, have not been investigated in a satisfying way. 50 refs.
Development of a Dynamic Lidar Uncertainty Framework
Newman, Jennifer [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Clifton, Andrew [WindForS; Bonin, Timothy [CIRES/NOAA ESRL; Choukulkar, Aditya [CIRES/NOAA ESRL; Brewer, W. Alan [NOAA ESRL; Delgado, Ruben [University of Maryland Baltimore County
2017-08-07
As wind turbine sizes increase and wind energy expands to more complex and remote sites, remote-sensing devices such as lidars are expected to play a key role in wind resource assessment and power performance testing. The switch to remote-sensing devices represents a paradigm shift in the way the wind industry typically obtains and interprets measurement data for wind energy. For example, the measurement techniques and sources of uncertainty for a remote-sensing device are vastly different from those associated with a cup anemometer on a meteorological tower. Current IEC standards for quantifying remote sensing device uncertainty for power performance testing consider uncertainty due to mounting, calibration, and classification of the remote sensing device, among other parameters. Values of the uncertainty are typically given as a function of the mean wind speed measured by a reference device and are generally fixed, leading to climatic uncertainty values that apply to the entire measurement campaign. However, real-world experience and a consideration of the fundamentals of the measurement process have shown that lidar performance is highly dependent on atmospheric conditions, such as wind shear, turbulence, and aerosol content. At present, these conditions are not directly incorporated into the estimated uncertainty of a lidar device. In this presentation, we describe the development of a new dynamic lidar uncertainty framework that adapts to current flow conditions and more accurately represents the actual uncertainty inherent in lidar measurements under different conditions. In this new framework, sources of uncertainty are identified for estimation of the line-of-sight wind speed and reconstruction of the three-dimensional wind field. These sources are then related to physical processes caused by the atmosphere and lidar operating conditions. The framework is applied to lidar data from a field measurement site to assess the ability of the framework to predict
Uncertainty analysis of the FRAP code
Peck, S.O.
1978-01-01
A user oriented, automated uncertainty analysis capability has been built into the Fuel Rod Analysis Program (FRAP) code and has been applied to a pressurized water reactor (PWR) fuel rod undergoing a loss-of-coolant accident (LOCA). The method of uncertainty analysis is the response surface method. The automated version significantly reduced the time required to complete the analysis and, at the same time, greatly increased the problem scope. Results of the analysis showed a significant difference in the total and relative contributions to the uncertainty of the response parameters between steady state and transient conditions
Uncertainties in thick-target PIXE analysis
Campbell, J.L.; Cookson, J.A.; Paul, H.
1983-01-01
Thick-target PIXE analysis insolves uncertainties arising from the calculation of thick-target X-ray production in addition to the usual PIXE uncertainties. The calculation demands knowledge of ionization cross-sections, stopping powers and photon attenuation coefficients. Information on these is reviewed critically and a computational method is used to estimate the uncertainties transmitted from this data base into results of thick-target PIXE analyses with reference to particular specimen types using beams of 2-3 MeV protons. A detailed assessment of the accuracy of thick-target PIXE is presented. (orig.)
Evaluation method for uncertainty of effective delayed neutron fraction βeff
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)
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)
Empirical Bayesian inference and model uncertainty
Poern, K.
1994-01-01
This paper presents a hierarchical or multistage empirical Bayesian approach for the estimation of uncertainty concerning the intensity of a homogeneous Poisson process. A class of contaminated gamma distributions is considered to describe the uncertainty concerning the intensity. These distributions in turn are defined through a set of secondary parameters, the knowledge of which is also described and updated via Bayes formula. This two-stage Bayesian approach is an example where the modeling uncertainty is treated in a comprehensive way. Each contaminated gamma distributions, represented by a point in the 3D space of secondary parameters, can be considered as a specific model of the uncertainty about the Poisson intensity. Then, by the empirical Bayesian method each individual model is assigned a posterior probability
Measurement Errors and Uncertainties Theory and Practice
Rabinovich, Semyon G
2006-01-01
Measurement Errors and Uncertainties addresses the most important problems that physicists and engineers encounter when estimating errors and uncertainty. Building from the fundamentals of measurement theory, the author develops the theory of accuracy of measurements and offers a wealth of practical recommendations and examples of applications. This new edition covers a wide range of subjects, including: - Basic concepts of metrology - Measuring instruments characterization, standardization and calibration -Estimation of errors and uncertainty of single and multiple measurements - Modern probability-based methods of estimating measurement uncertainty With this new edition, the author completes the development of the new theory of indirect measurements. This theory provides more accurate and efficient methods for processing indirect measurement data. It eliminates the need to calculate the correlation coefficient - a stumbling block in measurement data processing - and offers for the first time a way to obtain...
Uncertainty Quantification with Applications to Engineering Problems
Bigoni, Daniele
in measurements, predictions and manufacturing, and we can say that any dynamical system used in engineering is subject to some of these uncertainties. The first part of this work presents an overview of the mathematical framework used in Uncertainty Quantification (UQ) analysis and introduces the spectral tensor...... and thus the UQ analysis of the associated systems will benefit greatly from the application of methods which require few function evaluations. We first consider the propagation of the uncertainty and the sensitivity analysis of the non-linear dynamics of railway vehicles with suspension components whose......-scale problems, where efficient methods are necessary with today’s computational resources. The outcome of this work was also the creation of several freely available Python modules for Uncertainty Quantification, which are listed and described in the appendix....
BEPU methods and combining of uncertainties
Prosek, A.; Mavko, B.
2004-01-01
After approval of the revised rule on the acceptance of emergency core cooling system (ECCS) performance in 1988 there has been significant interest in the development of codes and methodologies for best-estimate loss-of-coolant accident (LOCAs) analyses. The Code Scaling, Applicability and Uncertainty (CSAU) evaluation method was developed and demonstrated for large-break (LB) LOCA in a pressurized water reactor. Later several new best estimate plus uncertainty methods (BEPUs) were developed in the world. The purpose of the paper is to identify and compare the statistical approaches of BEPU methods and present their important plant and licensing applications. The study showed that uncertainty analysis with random sampling of input parameters and the use of order statistics for desired tolerance limits of output parameters is today commonly accepted approach. The existing BEPU methods seems mature enough while the future research may be focused on the codes with internal assessment of uncertainty. (author)
Information-theoretic approach to uncertainty importance
Park, C.K.; Bari, R.A.
1985-01-01
A method is presented for importance analysis in probabilistic risk assessments (PRA) for which the results of interest are characterized by full uncertainty distributions and not just point estimates. The method is based on information theory in which entropy is a measure of uncertainty of a probability density function. We define the relative uncertainty importance between two events as the ratio of the two exponents of the entropies. For the log-normal and log-uniform distributions the importance measure is comprised of the median (central tendency) and of the logarithm of the error factor (uncertainty). Thus, if accident sequences are ranked this way, and the error factors are not all equal, then a different rank order would result than if the sequences were ranked by the central tendency measure alone. As an illustration, the relative importance of internal events and in-plant fires was computed on the basis of existing PRA results
Uncertainty in prediction and in inference
Hilgevoord, J.; Uffink, J.
1991-01-01
The concepts of uncertainty in prediction and inference are introduced and illustrated using the diffraction of light as an example. The close relationship between the concepts of uncertainty in inference and resolving power is noted. A general quantitative measure of uncertainty in inference can be obtained by means of the so-called statistical distance between probability distributions. When applied to quantum mechanics, this distance leads to a measure of the distinguishability of quantum states, which essentially is the absolute value of the matrix element between the states. The importance of this result to the quantum mechanical uncertainty principle is noted. The second part of the paper provides a derivation of the statistical distance on the basis of the so-called method of support
Estimating real-time predictive hydrological uncertainty
Verkade, J.S.
2015-01-01
Flood early warning systems provide a potentially highly effective flood risk reduction measure. The effectiveness of early warning, however, is affected by forecasting uncertainty: the impossibility of knowing, in advance, the exact future state of hydrological systems. Early warning systems
Systematic uncertainties in direct reaction theories
Lovell, A E; Nunes, F M
2015-01-01
Nuclear reactions are common probes to study nuclei and in particular, nuclei at the limits of stability. The data from reaction measurements depend strongly on theory for a reliable interpretation. Even when using state-of-the-art reaction theories, there are a number of sources of systematic uncertainties. These uncertainties are often unquantified or estimated in a very crude manner. It is clear that for theory to be useful, a quantitative understanding of the uncertainties is critical. Here, we discuss major sources of uncertainties in a variety of reaction theories used to analyze (d,p) nuclear reactions in the energy range E d = 10–20 MeV, and we provide a critical view on how these have been handled in the past and how estimates can be improved. (paper)
Risk Characterization uncertainties associated description, sensitivity analysis
Carrillo, M.; Tovar, M.; Alvarez, J.; Arraez, M.; Hordziejewicz, I.; Loreto, I.
2013-01-01
The power point presentation is about risks to the estimated levels of exposure, uncertainty and variability in the analysis, sensitivity analysis, risks from exposure to multiple substances, formulation of guidelines for carcinogenic and genotoxic compounds and risk subpopulations
''Nature is unknowable''. The idea of uncertainty
Crozon, M.
2000-01-01
This paper deals with one of the great idea of the twentieth century, the uncertainty principle of Heisenberg. With a philosophical approach the author explains this principle and presents its cultural impacts on mind. (A.L.B.)
Statistical Uncertainty in the Medicare Shared Savings...
U.S. Department of Health & Human Services — According to analysis reported in Statistical Uncertainty in the Medicare Shared Savings Program published in Volume 2, Issue 4 of the Medicare and Medicaid Research...
Policy Uncertainty and the US Ethanol Industry
Jason P. H. Jones
2017-11-01
Full Text Available The Renewable Fuel Standard (RFS2, as implemented, has introduced uncertainty into US ethanol producers and the supporting commodity market. First, the fixed mandate for what is mainly cornstarch-based ethanol has increased feedstock price volatility and exerts a general effect across the agricultural sector. Second, the large discrepancy between the original Energy Independence and Security Act (EISA intentions and the actual RFS2 implementation for some fuel classes has increased the investment uncertainty facing investors in biofuel production, distribution, and consumption. Here we discuss and analyze the sources of uncertainty and evaluate the effect of potential RFS2 adjustments as they influence these uncertainties. This includes the use of a flexible, production dependent mandate on corn starch ethanol. We find that a flexible mandate on cornstarch ethanol relaxed during drought could significantly reduce commodity price spikes and alleviate the decline of livestock production in cases of feedstock production shortfalls, but it would increase the risk for ethanol investors.
Uncertainty Quantification in Aerodynamics Simulations, Phase I
National Aeronautics and Space Administration — The objective of the proposed work (Phases I and II) is to develop uncertainty quantification methodologies and software suitable for use in CFD simulations of...
Business, industrial marketing and uncertainty [Editorial
Merigó Lindahl, José M.; Gil Lafuente, Anna Maria; Gil Lafuente, Jaime
2016-01-01
This special issue of the Journal of Business & Industrial Marketing, entitled "Business, Industrial Marketing and Uncertainty", presents selected extended studies that were presented at the European Academy of Management and Business Economics Conference (AEDEM 2012).
Piezoelectric energy harvesting with parametric uncertainty
Ali, S F; Friswell, M I; Adhikari, S
2010-01-01
The design and analysis of energy harvesting devices is becoming increasing important in recent years. Most of the literature has focused on the deterministic analysis of these systems and the problem of uncertain parameters has received less attention. Energy harvesting devices exhibit parametric uncertainty due to errors in measurement, errors in modelling and variability in the parameters during manufacture. This paper investigates the effect of parametric uncertainty in the mechanical system on the harvested power, and derives approximate explicit formulae for the optimal electrical parameters that maximize the mean harvested power. The maximum of the mean harvested power decreases with increasing uncertainty, and the optimal frequency at which the maximum mean power occurs shifts. The effect of the parameter variance on the optimal electrical time constant and optimal coupling coefficient are reported. Monte Carlo based simulation results are used to further analyse the system under parametric uncertainty