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Добірка наукової літератури з теми "Uncertainty assessment in APT"

Автор: Grafiati
Опубліковано: 14 березня 2023

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Статті в журналах з теми "Uncertainty assessment in APT"

1

Pandey, Alok K., R. Krishankumar, Dragan Pamucar, Fausto Cavallaro, Abbas Mardani, Samarjit Kar, and K. S. Ravichandran. "A Bibliometric Review on Decision Approaches for Clean Energy Systems under Uncertainty." Energies 14, no. 20 (October 19, 2021): 6824. http://dx.doi.org/10.3390/en14206824.

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Анотація:
This paper aims to provide a bibliometric review on the diverse decision approaches in uncertain contexts for clean energy system (CES) assessment. A total of 126 publications are analyzed. Previous reviews on CES have discussed several research questions on the decision methods and the applicability of evaluating CES, along with the factors associated with CESs. In the present study, we focus on the bibliometric aspect that attempts to address questions related to the prominence of authors, countries/regions that focus on the current theme, impact of journals, importance of articles in the research community, and so on. The window considered for the study is from 2018 to 2021, with the motive to extend the review process from the preceding works. A review model is presented to address the questions based on the literature evidence. The results infer that CESs are the most viable mode for sustainable development, and the use of decision approaches is apt for the assessment of CESs.
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2

LIBERMAN, ALIDA. "Permissible Promise-Making Under Uncertainty." Journal of the American Philosophical Association 5, no. 4 (2019): 468–86. http://dx.doi.org/10.1017/apa.2019.26.

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AbstractI outline four conditions on permissible promise-making: the promise must be for a morally permissible end, must not be deceptive, must be in good faith, and must involve a realistic assessment of oneself. I then address whether promises that you are uncertain you can keep can meet these four criteria, with a focus on campaign promises as an illustrative example. I argue that uncertain promises can meet the first two criteria, but that whether they can meet the second two depends on the source of the promisor's uncertainty. External uncertainty stemming from outside factors is unproblematic, but internal uncertainty stemming from the promisor's doubts about her own strength leads to promises that are in bad faith or unrealistic. I conclude that campaign promises are often subject to internal uncertainty and are therefore morally impermissible to make, all else being equal.
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Rababa, Mohammad. "The Role of Nurses’ Uncertainty in Decision-Making Process of Pain Management in People with Dementia." Pain Research and Treatment 2018 (August 1, 2018): 1–7. http://dx.doi.org/10.1155/2018/7281657.

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Pain in people with dementia (PWD) is underassessed and undertreated. Treatment of pain in people with dementia goes awry because of poor assessment, poor treatment, and factors related to nursing decision-making skills. Several theoretical models addressed the role of nurses’ critical thinking and decision-making skills in pain treatment, like the cognitive continuum theory (CCT) and the adaptive pain management (APT). Only the Response to Certainty of Pain (RCP) model was the first model to posit relationships between nurses' uncertainty, pain assessment, and patient outcomes. Gilmore-Bykovskyi and Bowers developed the RCP, which incorporates the concept of uncertainty and how it relates to the problem of unrelieved pain in PWD. The RCP model has the potential to provide good understanding of the problem of unrelieved pain in people with dementia. It also could help to develop a research study that brings comfort to an often neglected and vulnerable population.
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Adshead, Gwen. "Healing ourselves: ethical issues in the care of sick doctors." Advances in Psychiatric Treatment 11, no. 5 (September 2005): 330–37. http://dx.doi.org/10.1192/apt.11.5.330.

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In this paper I review some of the ethical dilemmas that arise when psychiatrists are involved in the assessment and treatment of medical colleagues. Special attention needs to be paid to the context of the relationship between the psychiatrist and the doctor-patient, and to the extent to which the patient is seeking help voluntarily or at the request of a third party. Psychiatrists may find themselves uncertain about how to meet the ethical demands of their duties to the patient and their duties to the public, when these conflict.
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Küttenbaum, Stefan, Stefan Maack, Alexander Taffe, and Thomas Braml. "On the treatment of measurement uncertainty in stochastic modeling of basic variables." Acta Polytechnica CTU Proceedings 36 (August 18, 2022): 109–18. http://dx.doi.org/10.14311/app.2022.36.0109.

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Анотація:
The acquisition and appropriate processing of relevant information about the considered system remains a major challenge in assessment of existing structures. Both the values and the validity of computed results such as failure probabilities essentially depend on the quantity and quality of the incorporated knowledge. One source of information are onsite measurements of structural or material characteristics to be modeled as basic variables in reliability assessment. The explicit use of (quantitative) measurement results in assessment requires the quantification of the quality of the measured information, i.e., the uncertainty associated with the information acquisition and processing. This uncertainty can be referred to as measurement uncertainty. Another crucial aspect is to ensure the comparability of the measurement results.This contribution attempts to outline the necessity and the advantages of measurement uncertainty calculations in modeling of measurement data-based random variables to be included in reliability assessment. It is shown, how measured data representing time-invariant characteristics, in this case non-destructively measured inner geometrical dimensions, can be transferred into measurement results that are both comparable and quality-evaluated. The calculations are based on the rules provided in the guide to the expression of uncertainty in measurement (GUM). The GUM-framework is internationally accepted in metrology and can serve as starting point for the appropriate processing of measured data to be used in assessment. In conclusion, the effects of incorporating the non-destructively measured data into reliability analysis are presented using a prestressed concrete bridge as case-study.
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Haslbeck, Matthias, Robert Kroyer, Andreas Taras, and Thomas Braml. "Uncertainty assessment for the Bayesian updating process of concrete strength properties." Acta Polytechnica CTU Proceedings 36 (August 18, 2022): 76–83. http://dx.doi.org/10.14311/app.2022.36.0076.

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Reassessment of infrastructure buildings has become an essential approach to deal with increasing traffic loads on ageing infrastructure buildings and to verify the service-life of those structures. Good estimation of the actual material properties is highly relevant for reliable structural reassessment. Although this holds for all building materials, the importance of good parameter estimation is of special importance for concrete structures, where the strength properties show relatively high variation and where the nominal strength properties tend to be too conservative. Modern design guidelines allow to make use of scientific methods such as Bayesian Updating of material properties to enable a more realistic consideration of the actual material properties in the reassessment of existing structures. However, guidelines for application and experience with those methods are not yet reported much or are rather vague [1]. The presented study focuses on the effect of the Bayesian Updating process for material parameters with special emphasis on the number and sampling location of test specimens as well as on the accuracy and confidence in the obtained posterior distribution, since sampling also includes a certain margin of uncertainty. The investigation on the methodological potential and on the uncertainty margin in the updating process in this contribution uses a batch of 14 test results on the concrete compressive strength obtained from drill cores along with the inherent measurement uncertainties from the testing procedure. After a short review of Bayes’ Theorem, the Markov Chain Monte Carlo Method (MCMC) and the bootstrap methodology, all combinations of subsamples of size 1, 3 and 5 specimens were built and provided to the Bayes’ updating procedure via MCMC to determine the posterior distributions. The series of obtained posterior distributions for a certain subsample was used to determine the uncertainty in the Bayesian Updating process by evaluation of the scatter in the expected value, the standard deviation and the 5 %-quantile of the updated distribution. The simulations show the importance of an adequate sample size and quantify the uncertainties arising from the limited number of observations.
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Ning, T., J. Wang, G. Elgered, G. Dick, J. Wickert, M. Bradke, M. Sommer, R. Querel, and D. Smale. "The uncertainty of the atmospheric integrated water vapour estimated from GNSS observations." Atmospheric Measurement Techniques 9, no. 1 (January 18, 2016): 79–92. http://dx.doi.org/10.5194/amt-9-79-2016.

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Abstract. Within the Global Climate Observing System (GCOS) Reference Upper-Air Network (GRUAN) there is a need for an assessment of the uncertainty in the integrated water vapour (IWV) in the atmosphere estimated from ground-based global navigation satellite system (GNSS) observations. All relevant error sources in GNSS-derived IWV are therefore essential to be investigated. We present two approaches, a statistical and a theoretical analysis, for the assessment of the uncertainty of the IWV. The method is valuable for all applications of GNSS IWV data in atmospheric research and weather forecast. It will be implemented to the GNSS IWV data stream for GRUAN in order to assign a specific uncertainty to each data point. In addition, specific recommendations are made to GRUAN on hardware, software, and data processing practices to minimise the IWV uncertainty. By combining the uncertainties associated with the input variables in the estimations of the IWV, we calculated the IWV uncertainties for several GRUAN sites with different weather conditions. The results show a similar relative importance of all uncertainty contributions where the uncertainties in the zenith total delay (ZTD) dominate the error budget of the IWV, contributing over 75 % of the total IWV uncertainty. The impact of the uncertainty associated with the conversion factor between the IWV and the zenith wet delay (ZWD) is proportional to the amount of water vapour and increases slightly for moist weather conditions. The GRUAN GNSS IWV uncertainty data will provide a quantified confidence to be used for the validation of other measurement techniques.
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Bravo-Aranda, Juan Antonio, Livio Belegante, Volker Freudenthaler, Lucas Alados-Arboledas, Doina Nicolae, María José Granados-Muñoz, Juan Luis Guerrero-Rascado, et al. "Assessment of lidar depolarization uncertainty by means of a polarimetric lidar simulator." Atmospheric Measurement Techniques 9, no. 10 (October 7, 2016): 4935–53. http://dx.doi.org/10.5194/amt-9-4935-2016.

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Abstract. Lidar depolarization measurements distinguish between spherical and non-spherical aerosol particles based on the change of the polarization state between the emitted and received signal. The particle shape information in combination with other aerosol optical properties allows the characterization of different aerosol types and the retrieval of aerosol particle microphysical properties. Regarding the microphysical inversions, the lidar depolarization technique is becoming a key method since particle shape information can be used by algorithms based on spheres and spheroids, optimizing the retrieval procedure. Thus, the identification of the depolarization error sources and the quantification of their effects are crucial. This work presents a new tool to assess the systematic error of the volume linear depolarization ratio (δ), combining the Stokes–Müller formalism and the complete sampling of the error space using the lidar model presented in Freudenthaler (2016a). This tool is applied to a synthetic lidar system and to several EARLINET lidars with depolarization capabilities at 355 or 532 nm. The lidar systems show relative errors of δ larger than 100 % for δ values around molecular linear depolarization ratios (∼ 0.004 and up to ∼ 10 % for δ = 0.45). However, one system shows only relative errors of 25 and 0.22 % for δ = 0.004 and δ = 0.45, respectively, and gives an example of how a proper identification and reduction of the main error sources can drastically reduce the systematic errors of δ. In this regard, we provide some indications of how to reduce the systematic errors.
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Hassel, Thomas, Volker Mintzlaff, Joachim Stahlmann, Klaus-Jürgen Röhlig, and Anne Eckhardt. "Workshop Safety and Uncertainty." Safety of Nuclear Waste Disposal 1 (November 10, 2021): 309–10. http://dx.doi.org/10.5194/sand-1-309-2021.

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Abstract. Uncertainties have a significant influence on the assessment and evaluation of the safety of a repository system for high-level radioactive waste. Significant reasons for uncertainties concerning the safety barriers of a repository are: Conducting experiments on the long-term behaviour of the repository in real time is impossible due to the long assessment period over which the repository is supposed to ensure safety. The extrapolation of results from time-limited experiments, e.g. on the corrosion of container materials, to other temporal dimensions is associated with uncertainties. Uncertainties also stem from differences between experimental situations, e.g. laboratory experiments, and the real conditions in the repository. The interpretation of empirical results can be ambiguous and therefore associated with uncertainties. The development of future impacts on the barriers can only be predicted to a limited extent. Therefore, the future behaviour of the barriers can only be extrapolated into the future to a limited extent on the basis of experience gained in the past and uncertainties remain. The construction and operation of the repository will disturb its natural environment. The geological environment in which the repository is embedded behaves differently from a natural geological system, which in turn is associated with uncertainties. A major source of uncertainties is also the natural inhomogeneity of the geological barrier, which can only be investigated on a sample basis. During excavation and other construction work underground, unforeseen situations are to be expected, which make it necessary to act situationally. The complexity of the disposal path where decisions are interlinked, creates further uncertainties. Last but not least, it is uncertain what further findings on the safety of the repository will be obtained in the future along the disposal path. For safety studies, especially studies on the long-term safety of repository systems, methods and conventions for dealing with uncertainties have become established internationally. In the site selection process, these methods and conventions are questioned and, if necessary, must be further developed so that they ultimately also convince the interested public and scientists from other disciplines. In the workshop, uncertainties will be examined in particular from the perspectives of a civil engineer and of a materials researcher with introductory presentations. This will be followed by a moderated discussion. The workshop will focus on the preliminary safety investigations; however, the discussion can also refer to later phases of the disposal path. The aim of the discussion is to arrive at a common synthesis: Where have good practices for dealing with uncertainties already been established? Where is there still a need for research and clarification? What needs to be considered in the dialogue with the interested public?
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Glantz, P., and M. Tesche. "Assessment of two aerosol optical thickness retrieval algorithms applied to MODIS Aqua and Terra measurements in Europe." Atmospheric Measurement Techniques 5, no. 7 (July 19, 2012): 1727–40. http://dx.doi.org/10.5194/amt-5-1727-2012.

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Abstract. The aim of the present study is to validate AOT (aerosol optical thickness) and Ångström exponent (α), obtained from MODIS (MODerate resolution Imaging Spectroradiometer) Aqua and Terra calibrated level 1 data (1 km horizontal resolution at ground) with the SAER (Satellite AErosol Retrieval) algorithm and with MODIS Collection 5 (c005) standard product retrievals (10 km horizontal resolution), against AERONET (AErosol RObotic NETwork) sun photometer observations over land surfaces in Europe. An inter-comparison of AOT at 0.469 nm obtained with the two algorithms has also been performed. The time periods investigated were chosen to enable a validation of the findings of the two algorithms for a maximal possible variation in sun elevation. The satellite retrievals were also performed with a significant variation in the satellite-viewing geometry, since Aqua and Terra passed the investigation area twice a day for several of the cases analyzed. The validation with AERONET shows that the AOT at 0.469 and 0.555 nm obtained with MODIS c005 is within the expected uncertainty of one standard deviation of the MODIS c005 retrievals (ΔAOT = ± 0.05 ± 0.15 · AOT). The AOT at 0.443 nm retrieved with SAER, but with a much finer spatial resolution, also agreed reasonably well with AERONET measurements. The majority of the SAER AOT values are within the MODIS c005 expected uncertainty range, although somewhat larger average absolute deviation occurs compared to the results obtained with the MODIS c005 algorithm. The discrepancy between AOT from SAER and AERONET is, however, substantially larger for the wavelength 488 nm. This means that the values are, to a larger extent, outside of the expected MODIS uncertainty range. In addition, both satellite retrieval algorithms are unable to estimate α accurately, although the MODIS c005 algorithm performs better. Based on the inter-comparison of the SAER and MODIS c005 algorithms, it was found that SAER on the whole is able to obtain results within the expected uncertainty range of MODIS Aqua and Terra observations.
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Дисертації з теми "Uncertainty assessment in APT"

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Glass, Deborah Catherine, and mikewood@deakin edu au. "Exposure estimation, uncertainty and variability in occupational hygiene retrospective assessment." Deakin University. School of Biological and Chemical Sciences, 1999. http://tux.lib.deakin.edu.au./adt-VDU/public/adt-VDU20051017.142634.

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This thesis reports on a quantitative exposure assessment and on an analysis of the attributes of the data used in the estimations, in particular distinguishing between its uncertainty and variability. A retrospective assessment of exposure to benzene was carried out for a case control study of leukaemia in the Australian petroleum industry. The study used the mean of personal task-based measurements (Base Estimates) in a deterministic algorithm and applied factors to model back to places, times etc for which no exposure measurements were available. Mean daily exposures were estimated, on an individual subject basis, by summing the task-based exposures. These mean exposures were multiplied by the years spent on each job to provide exposure estimates in ppm-years. These were summed to provide a Cumulative Estimate for each subject. Validation was completed for the model and key inputs. Exposures were low, most jobs were below TWA of 5 ppm benzene. Exposures in terminals were generally higher than at refineries. Cumulative Estimates ranged from 0.005 to 50.9 ppm-years, with 84 percent less than 10 ppm-years. Exposure probability distributions were developed for tanker drivers using Monte Carlo simulation of the exposure estimation algorithm. The outcome was a lognormal distribution of exposure for each driver. These provide the basis for alternative risk assessment metrics e.g. the frequency of short but intense exposures which provided only a minimal contribution to the long-term average exposure but may increase risk of leukaemia. The effect of different inputs to the model were examined and their significance assessed using Monte Carlo simulation. The Base Estimates were the most important determinant of exposure in the model. The sources of variability in the measured data were examined, including the effect of having censored data and the between and within-worker variability. The sources of uncertainty in the exposure estimates were analysed and consequential improvements in exposure assessment identified. Monte Carlo sampling was also used to examine the uncertainties and variability associated with the tanker drivers' exposure assessment, to derive an estimate of the range and to put confidence intervals on the daily mean exposures. The identified uncertainty was less than the variability associated with the estimates. The traditional approach to exposure estimation typically derives only point estimates of mean exposure. The approach developed here allows a range of exposure estimates to be made and provides a more flexible and improved basis for risk assessment.
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2

Skinner, Laura. "Negotiating uncertainty : mental health professionals’ experiences of the Mental Health Act assessment process." Thesis, University of Leicester, 2006. http://hdl.handle.net/2381/8972.

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3

Hridoy, Md Rafiul Sabbir. "An Intelligent Flood Risk Assessment System using Belief Rule Base." Thesis, Luleå tekniska universitet, Institutionen för system- och rymdteknik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-65390.

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Анотація:
Natural disasters disrupt our daily life and cause many sufferings. Among the various natural disasters, flood is one of the most catastrophic. Assessing flood risk helps to take necessary precautions and can save human lives. The assessment of risk involves various factors which can not be measured with hundred percent certainty. Therefore, the present methods of flood risk assessment can not assess the risk of flooding accurately.  This research rigorously investigates various types of uncertainties associated with the flood risk factors. In addition, a comprehensive study of the present flood risk assessment approaches has been conducted. Belief Rule Base expert systems are widely used to handle various of types of uncertainties. Therefore, this research considers BRBES’s approach to develop an expert system to assess the risk of flooding. In addition, to facilitate the learning procedures of BRBES, an optimal learning algorithm has been proposed. The developed BRBES has been applied taking real world case study area, located at Cox’s Bazar, Bangladesh. The training data has been collected from the case study area to obtain the trained BRB and to develop the optimal learning model. The BRBES can generate different "What-If" scenarios which enables the analysis of flood risk of an area from various perspectives which makes the system robust and sustainable. This system is said to be intelligent as it has knowledge base, inference engine as well as the learning capability.
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4

Dixon, William J., and bill dixon@dse vic gov au. "Uncertainty in Aquatic Toxicological Exposure-Effect Models: the Toxicity of 2,4-Dichlorophenoxyacetic Acid and 4-Chlorophenol to Daphnia carinata." RMIT University. Biotechnology and Environmental Biology, 2005. http://adt.lib.rmit.edu.au/adt/public/adt-VIT20070119.163720.

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Анотація:
Uncertainty is pervasive in risk assessment. In ecotoxicological risk assessments, it arises from such sources as a lack of data, the simplification and abstraction of complex situations, and ambiguities in assessment endpoints (Burgman 2005; Suter 1993). When evaluating and managing risks, uncertainty needs to be explicitly considered in order to avoid erroneous decisions and to be able to make statements about the confidence that we can place in risk estimates. Although informative, previous approaches to dealing with uncertainty in ecotoxicological modelling have been found to be limited, inconsistent and often based on assumptions that may be false (Ferson & Ginzburg 1996; Suter 1998; Suter et al. 2002; van der Hoeven 2004; van Straalen 2002a; Verdonck et al. 2003a). In this thesis a Generalised Linear Modelling approach is proposed as an alternative, congruous framework for the analysis and prediction of a wide range of ecotoxicological effects. This approach was used to investigate the results of toxicity experiments on the effect of 2,4-Dichlorophenoxyacetic Acid (2,4-D) formulations and 4-Chlorophenol (4-CP, an associated breakdown product) on Daphnia carinata. Differences between frequentist Maximum Likelihood (ML) and Bayesian Markov-Chain Monte-Carlo (MCMC) approaches to statistical reasoning and model estimation were also investigated. These approaches are inferentially disparate and place different emphasis on aleatory and epistemic uncertainty (O'Hagan 2004). Bayesian MCMC and Probability Bounds Analysis methods for propagating uncertainty in risk models are also compared for the first time. For simple models, Bayesian and frequentist approaches to Generalised Linear Model (GLM) estimation were found to produce very similar results when non-informative prior distributions were used for the Bayesian models. Potency estimates and regression parameters were found to be similar for identical models, signifying that Bayesian MCMC techniques are at least a suitable and objective replacement for frequentist ML for the analysis of exposureresponse data. Applications of these techniques demonstrated that Amicide formulations of 2,4-D are more toxic to Daphnia than their unformulated, Technical Acid parent. Different results were obtained from Bayesian MCMC and ML methods when more complex models and data structures were considered. In the analysis of 4-CP toxicity, the treatment of 2 different factors as fixed or random in standard and Mixed-Effect models was found to affect variance estimates to the degree that different conclusions would be drawn from the same model, fit to the same data. Associated discrepancies in the treatment of overdispersion between ML and Bayesian MCMC analyses were also found to affect results. Bayesian MCMC techniques were found to be superior to the ML ones employed for the analysis of complex models because they enabled the correct formulation of hierarchical (nested) datastructures within a binomial logistic GLM. Application of these techniques to the analysis of results from 4-CP toxicity testing on two strains of Daphnia carinata found that between-experiment variability was greater than that within-experiments or between-strains. Perhaps surprisingly, this indicated that long-term laboratory culture had not significantly affected the sensitivity of one strain when compared to cultures of another strain that had recently been established from field populations. The results from this analysis highlighted the need for repetition of experiments, proper model formulation in complex analyses and careful consideration of the effects of pooling data on characterising variability and uncertainty. The GLM framework was used to develop three dimensional surface models of the effects of different length pulse exposures, and subsequent delayed toxicity, of 4-CP on Daphnia. These models described the relationship between exposure duration and intensity (concentration) on toxicity, and were constructed for both pulse and delayed effects. Statistical analysis of these models found that significant delayed effects occurred following the full range of pulse exposure durations, and that both exposure duration and intensity interacted significantly and concurrently with the delayed effect. These results indicated that failure to consider delayed toxicity could lead to significant underestimation of the effects of pulse exposure, and therefore increase uncertainty in risk assessments. A number of new approaches to modelling ecotoxicological risk and to propagating uncertainty were also developed and applied in this thesis. In the first of these, a method for describing and propagating uncertainty in conventional Species Sensitivity Distribution (SSD) models was described. This utilised Probability Bounds Analysis to construct a nonparametric 'probability box' on an SSD based on EC05 estimates and their confidence intervals. Predictions from this uncertain SSD and the confidence interval extrapolation methods described by Aldenberg and colleagues (2000; 2002a) were compared. It was found that the extrapolation techniques underestimated the width of uncertainty (confidence) intervals by 63% and the upper bound by 65%, when compared to the Probability Bounds (P3 Bounds) approach, which was based on actual confidence estimates derived from the original data. An alternative approach to formulating ecotoxicological risk modelling was also proposed and was based on a Binomial GLM. In this formulation, the model is first fit to the available data in order to derive mean and uncertainty estimates for the parameters. This 'uncertain' GLM model is then used to predict the risk of effect from possible or observed exposure distributions. This risk is described as a whole distribution, with a central tendency and uncertainty bounds derived from the original data and the exposure distribution (if this is also 'uncertain'). Bayesian and P-Bounds approaches to propagating uncertainty in this model were compared using an example of the risk of exposure to a hypothetical (uncertain) distribution of 4-CP for the two Daphnia strains studied. This comparison found that the Bayesian and P-Bounds approaches produced very similar mean and uncertainty estimates, with the P-bounds intervals always being wider than the Bayesian ones. This difference is due to the different methods for dealing with dependencies between model parameters by the two approaches, and is confirmation that the P-bounds approach is better suited to situations where data and knowledge are scarce. The advantages of the Bayesian risk assessment and uncertainty propagation method developed are that it allows calculation of the likelihood of any effect occurring, not just the (probability)bounds, and that the same software (WinBugs) and model construction may be used to fit regression models and predict risks simultaneously. The GLM risk modelling approaches developed here are able to explain a wide range of response shapes (including hormesis) and underlying (non-normal) distributions, and do not involve expression of the exposure-response as a probability distribution, hence solving a number of problems found with previous formulations of ecotoxicological risk. The approaches developed can also be easily extended to describe communities, include modifying factors, mixed-effects, population growth, carrying capacity and a range of other variables of interest in ecotoxicological risk assessments. While the lack of data on the toxicological effects of chemicals is the most significant source of uncertainty in ecotoxicological risk assessments today, methods such as those described here can assist by quantifying that uncertainty so that it can be communicated to stakeholders and decision makers. As new information becomes available, these techniques can be used to develop more complex models that will help to bridge the gap between the bioassay and the ecosystem.
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5

Cui, W. C. "Uncertainty analysis in structural safety assessment." Thesis, University of Bristol, 1989. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.303742.

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6

Budzinski, Maik. "The differentiation between variability uncertainty and knowledge uncertainty in life cycle assessment." Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2014. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-135913.

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Анотація:
The following thesis deals with methods to increase the reliability of the results in life cycle assessment. The paper is divided into two parts. The first part points out the typologies and sources of uncertainty in LCA and summarises the existing methods dealing with it. The methods are critically discussed and pros and cons are contrasted. Within the second part a case study is carried out. This study calculates the carbon footprint of a cosmetic product of Li-iL GmbH. Thereby the whole life cycle of the powder bath Blaue Traube is analysed. To increase the reliability of the result a procedure, derived from the first part, is applied. Recommendations to enhance the product´s sustainability are then given to the decision-makers of the company. Finally the applied procedure for dealing with uncertainty in LCAs is evaluated. The aims of the thesis are to make a contribution to the understanding of uncertainty in life cycle assessment and to deal with it in a more consistent manner. As well, the carbon footprint of the powder bath shall be based on appropriate assumptions and shall consider occurring uncertainties. Basing on discussed problems, a method is introduced to avoid the problematic merging of variability uncertainty and data uncertainty to generate probability distributions. The introduced uncertainty importance analysis allows a consistent differentiation of these types of uncertainty. Furthermore an assessment of the used data of LCA studies is possible. The method is applied at a PCF study of the bath powder Blaue Traube of Li-iL GmbH. Thereby the analysis is carried out over the whole life cycle (cradle-to-grave) as well as cradle-to-gate. The study gives a practical example to the company determining the carbon footprint of products. In addition, it meets the requirements of ISO guidelines of publishing the study and comparing it with other products. Within the PCF study the introduced method allows a differentiation of variability uncertainty and knowledge uncertainty. The included uncertainty importance analysis supports the assessment of each aggregated unit process within the analysed product system. Finally this analysis can provide a basis to collect additional, more reliable or uncertain data for critical processes.
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7

Burke, Michael Martin. "Software dependability assessment." Thesis, University of Bristol, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.320203.

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Mesa-Frias, M. "Modelling uncertainty in environmental health impact assessment." Thesis, London School of Hygiene and Tropical Medicine (University of London), 2015. http://researchonline.lshtm.ac.uk/2391599/.

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Quantifying uncertainty in environmental health impact assessment models is important, particularly if the models are to be used for decision support. This thesis develops a new non-probabilistic framework to quantify uncertainty in environmental health impact assessment models. The framework takes into account two different perspectives of uncertainty: conceptual and analytical in terms of where uncertainty occurs in the model. The first perspective is concerned with uncertainty in the framing assumptions of health impact assessment, whereas the second perspective is concerned with uncertainty in the parameters of a model. The construction of the framework was achieved by focusing on five specific objectives: (i) to describe the complexity of how uncertainty arises in environmental health impact assessment and classify the uncertainty to be amenable for quantitative modelling;(ii) to critically appraise the strengths and limitations of current methods used to handle the uncertainty in environmental health impact assessment; (iii) to develop a novel quantitative framework for quantifying uncertainty from the conceptual and analytical perspectives; (iv) to formulate two detailed case-study examples on health impact assessment of indoor housing interventions; (v) to apply the framework to the two case-studies. After critiquing the uncertainty quantification methods that are currently applied in environmental health impact assessment, the thesis develops the framework for quantifying uncertainty, starting with the conceptual uncertainty (uncertainty associated with the framing assumptions or formulation of the model), then quantifying the analytical uncertainty (uncertainty associated with the input parameters and outputs of the model). The first case-study was concerned with the health impact assessment of improving housing insulation. Using fuzzy cognitive maps, the thesis identifies key indoor factors and their pathways highly sensitive to the framing assumptions of the health impact assessment. The second case-study was concerned with estimating the uncertainty in the health burdens in England, associated with three ventilation exposure scenarios using fuzzy sets and interval analysis. The thesis presents a wider uncertainty framework as a first step forward in quantifying conceptual and analytical uncertainty in environmental health impact assessment when dealing with limited information.
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Senel, Ozgur. "Infill location determination and assessment of corresponding uncertainty." [College Station, Tex. : Texas A&M University, 2008. http://hdl.handle.net/1969.1/ETD-TAMU-2806.

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Jesus, André H. "Modular Bayesian uncertainty assessment for structural health monitoring." Thesis, University of Warwick, 2018. http://wrap.warwick.ac.uk/109522/.

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Civil infrastructure are critical elements to a society’s welfare and economic thriving. Understanding their behaviour and monitoring their serviceability are relevant challenges of Structural Health Monitoring (SHM). Despite the impressive improvement of miniaturisation, standardisation and diversity of monitoring systems, the ability to interpret data has registered a much slower progression across years. The underlying causes for such disparity are the overall complexity of the proposed challenge, and the inherent errors and lack of information associated with it. Overall, it is necessary to appropriately quantify the uncertainties which undermine the SHM concept. This thesis proposes an enhanced modular Bayesian framework (MBA) for structural identification (st-id) and measurement system design (MSD). The framework is hybrid, in the sense that it uses a physics-based model, and Gaussian processes (mrGp) which are trained against data, for uncertainty quantification. The mrGp act as emulators of the model response surface and its model discrepancy, also quantifying observation error, parametric and interpolation uncertainty. Finally, this framework has been enhanced with the Metropolis–Hastings for multiple parameters st-id. In contrast to other probabilistic frameworks, the MBA allows to estimate structural parameters (which reflect a performance of interest) consistently with their physical interpretation, while highlighting patterns of a model’s discrepancy. The MBA performance can be substantially improved by considering multiple responses which are sensitive to the structural parameters. An extension of the MBA for MSD has been validated on a reduced-scale aluminium bridge subject to thermal expansion (supported at one end with springs and instrumented with strain gauges and thermocouples). A finite element (FE) model of the structure was used to obtain a semi-optimal sensor configuration for stid. Results indicate that 1) measuring responses which are sensitive to the structural parameters and are more directly related to model discrepancy, provide the best results for st-id; 2) prior knowledge of the model discrepancy is essential to capture the latter type of responses. Subsequently, an extension of the MBA for st-id was also applied for identification of the springs stiffness, and results indicate relative errors five times less than other state of the art Bayesian/deterministic methodologies. Finally, a first application to field data was performed, to calibrate a detailed FE model of the Tamar suspension bridge using long-term monitored data. Measurements of temperature, traffic, mid-span displacement and natural frequencies of the bridge, were used to identify the bridge’s main/stay cables initial strain and friction of its bearings. Validation of results suggests that the identified parameters agree more closely with the true structural behaviour of the bridge, with an error that is several orders of magnitude smaller than other probabilistic st-id approaches. Additionally, the MBA allowed to predicted model discrepancy functions to assess the predictive ability of the Tamar bridge FE model. It was found, that the model predicts more accurately the bridge mid-span displacements than its natural frequencies, and that the adopted traffic model is less able to simulate the bridge behaviour during periods of traffic jams. Future developments of the MBA framework include its extension and application for damage detection and MSD with multiple parameter identification.
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Книги з теми "Uncertainty assessment in APT"

1

United States. Environmental Protection Agency. Office of the Administrator and United States. Environmental Protection Agency. Science Advisory Board, eds. Benefits and costs of Clean Air Act: Direct costs and uncertainty analysis. Washington, DC: U.S. Environmental Protection Agency, Office of the Administrator, Science Advisory Board, 2007.

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Aven, Terje, Piero Baraldi, Roger Flage, and Enrico Zio, eds. Uncertainty in Risk Assessment. Chichester, United Kingdom: John Wiley & Sons, Ltd, 2014. http://dx.doi.org/10.1002/9781118763032.

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Riley, Karin, Peter Webley, and Matthew Thompson, eds. Natural Hazard Uncertainty Assessment. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2016. http://dx.doi.org/10.1002/9781119028116.

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Lindén, Staffan. Assessment of GDP forecasts uncertainty. Brussels: European Commission, Directorate-General for Economic and Financial Affairs, 2003.

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Bradbury, A. Uncertainty in strategic environmental assessment. Oxford: Oxford Brookes University, 1993.

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6

Laboratories, Sandia National, Commission of the European Communities., and U.S. Nuclear Regulatory Commission. Office of Nuclear Regulatory Research. Division of Systems Technology., eds. Probabilistic accident consequence uncertainty analysis: Dispersion and deposition uncertainty assessment. Washington, DC: U.S. Nuclear Regulatory Commission, 1995.

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J, Goossens L. H., U.S. Nuclear Regulatory Commission. Office of Nuclear Regulatory Research. Division of Systems Technology., and Commission of the European Communities., eds. Probabilistic accident consequence uncertainty analysis: Uncertainty assessment for internal dosimetry. Washington, DC: U.S. Nuclear Regulatory Commission, 1998.

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E, Haskin F., U.S. Nuclear Regulatory Commission. Office of Nuclear Regulatory Research. Division of Systems Technology., and Sandia National Laboratories, eds. Probabilistic accident consequence uncertainty analysis: Early health effects uncertainty assessment. Washington, DC: Division of Systems Technology, Office of Nuclear Regulatory Research, U.S. Nuclear Regulatory Commission, 1997.

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9

J, Goossens L. H., U.S. Nuclear Regulatory Commission. Office of Nuclear Regulatory Research. Division of Systems Technology., and Sandia National Laboratories, eds. Probabilistic accident consequence uncertainty analysis: Uncertainty assessment for internal dosimetry. Washington, DC: Division of Systems Technology, Office of Nuclear Regulatory Research, U.S. Nuclear Regulatory Commission, 1998.

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10

U.S. Nuclear Regulatory Commission. Office of Nuclear Regulatory Research. Division of Systems Technology., Commission of the European Communities., and Sandia National Laboratories, eds. Probabilistic accident consequence uncertainty analysis: Dispersion and deposition uncertainty assessment. Washington, DC: U.S. Nuclear Regulatory Commission, 1995.

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Частини книг з теми "Uncertainty assessment in APT"

1

Brazier, Richard E., Tobias Krueger, and John Wainwright. "Uncertainty Assessment." In Patterns of Land Degradation in Drylands, 265–85. Dordrecht: Springer Netherlands, 2013. http://dx.doi.org/10.1007/978-94-007-5727-1_10.

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Rausand, Marvin. "Uncertainty and Sensitivity Analysis." In Risk Assessment, 497–514. Hoboken, New Jersey: John Wiley & Sons, Inc., 2013. http://dx.doi.org/10.1002/9781118281116.ch16.

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Bjerga, Torbjørn, Terje Aven, and Roger Flage. "Completeness Uncertainty." In Knowledge in Risk Assessment and Management, 127–41. Chichester, UK: John Wiley & Sons, Ltd, 2017. http://dx.doi.org/10.1002/9781119317906.ch6.

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Hundloe, Tor. "The Baselines and Uncertainty." In Environmental Impact Assessment, 183–203. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-80942-3_13.

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van Asselt, Marjolein B. A. "Integrated Assessment." In Perspectives on Uncertainty and Risk, 23–74. Dordrecht: Springer Netherlands, 2000. http://dx.doi.org/10.1007/978-94-017-2583-5_2.

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Wenzel, Henrik, Michael Hauschild, and Leo Alting. "Uncertainty and Sensitivity Analysis." In Environmental Assessment of Products, 129–34. Boston, MA: Springer US, 1997. http://dx.doi.org/10.1007/978-1-4615-6367-9_11.

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Rosenbaum, Ralph K., Stylianos Georgiadis, and Peter Fantke. "Uncertainty Management and Sensitivity Analysis." In Life Cycle Assessment, 271–321. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-56475-3_11.

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Baker, Scott, Jeffrey Driver, and David McCallum. "Qualitative and Quantitative Uncertainty Analysis." In Residential Exposure Assessment, 313–30. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/978-1-4615-1279-0_13.

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Kozine, Igor. "A Hierarchical Uncertainty Model, Combination Rules and Uncertainty Propagation." In Probabilistic Safety Assessment and Management, 2511–16. London: Springer London, 2004. http://dx.doi.org/10.1007/978-0-85729-410-4_403.

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Cobbing, Colin, and Charlotte Clark. "Managing Uncertainty in Noise Assessment Processes." In Uncertainty in Acoustics, 389–430. First edition. | Boca Raton, FL : CRC Press, Taylor & Francis Group, 2020.: CRC Press, 2020. http://dx.doi.org/10.1201/9780429470622-13.

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Тези доповідей конференцій з теми "Uncertainty assessment in APT"

1

Morosov, André Luís, and Denis José Schiozer. "Field Development Process Revealing Uncertainty Assessment Pitfalls." In SPE Europec featured at 78th EAGE Conference and Exhibition. Society of Petroleum Engineers, 2016. http://dx.doi.org/10.2118/180094-ms.

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Chiotoroiu, Maria-Magdalena, Torsten Clemens, Markus Zechner, Jongsoo Hwang, Mukul M. Sharma, and Marco Thiele. "Risk Assessment and Simulation of Injectivity Decline Under Uncertainty." In SPE Europec featured at 81st EAGE Conference and Exhibition. Society of Petroleum Engineers, 2019. http://dx.doi.org/10.2118/195499-ms.

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Lowry, Thomas. "Understanding Uncertainty in Geothermal Energy Development Using a Formalized Performance Assessment Approach." In Proposed for presentation at the 2021 Geothermal Rising Conference held October 3-6, 2021 in San Diego, CA US. US DOE, 2021. http://dx.doi.org/10.2172/1891084.

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Cochran, Jeffrey D., Ruohua Z. Guo, and Charles H. Panzarella. "Estimation and Visualization of the Probability of Failing an Assessment When Using a Failure Assessment Diagram." In ASME 2015 Pressure Vessels and Piping Conference. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/pvp2015-45746.

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Codes and standards are often filled with deterministic equations and relationships that are presented without explicit quantification of the uncertainty inherent in their application or derivation. That is not to say that such equations and relationships are not conservative, but to the contrary, that whatever conservatism is dutifully included sometimes goes unquantified. The gamut of Failure Assessment Diagrams (FAD) used for assessing the risk of crack-like flaws provides an excellent example of useful criteria that may benefit from uncertainty quantification. The Level 2 FAD from API 579-1/ASME FFS-1 is used as an exemplar in the probabilistic extension of existing codes and standards. As a first step toward modeling the true probability of failure for assessment points nominally below the FAD envelope, assumptions are made regarding the variance of operating conditions, geometry, and flaw sizes, and these assumptions are utilized to estimate the probability that a nominal assessment point will in fact correspond to conditions exceeding the FAD envelope. This estimation procedure is used to generate contour lines of constant probability within the existing FAD envelope, providing an easily interpretable visualization of the results that may be coupled with risk matrices or other risk-based inspection methodologies.
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Efthymiou, Mike, and Jan Willem van de Graaf. "Reliability and (Re)Assessment of Fixed Steel Structures." In ASME 2011 30th International Conference on Ocean, Offshore and Arctic Engineering. ASMEDC, 2011. http://dx.doi.org/10.1115/omae2011-50253.

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This paper reviews the structural integrity and reliability of fixed steel offshore structures with a focus on improved models and incorporation of these models in design standards. Technical achievements in four key areas are reviewed which, when combined, resulted in a step improvement in the calculation of structural reliability. The first area is the extreme environmental loading on an offshore platform; the second area is the joint occurrence of waves, winds and currents, i.e. accounting for the fact that these do not, in general, peak at the same time and do not act in the same direction. The third area is the estimation of the ultimate strength of a fixed steel platform, accounting for component strength, including the buckling and post-buckling behaviour and the uncertainty in system strength. The fourth and final area is the integration of the above models to estimate the probability of failure. The historical performance of platforms and the improvements in successive editions of API RP 2A are reviewed; reliability targets appropriate for different exposure levels and corresponding performance standards are developed, aimed at harmonizing design practices worldwide. A differentiation is recommended between permanently manned L-1 installations and manned-evacuated L-1 installations in the Gulf of Mexico; this is because the consequences of failure are considerably different.
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Steinkjer, Oddrun, Nils So̸dahl, and Guttorm Gryto̸yr. "Methodology for Time Domain Fatigue Life Assessment of Risers and Umbilicals." In ASME 2010 29th International Conference on Ocean, Offshore and Arctic Engineering. ASMEDC, 2010. http://dx.doi.org/10.1115/omae2010-20119.

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Risers and umbilicals are exposed to dynamic loading from waves and floater motions. These structures are known to have a pronounced non-linear response characteristic. Non-linear time-domain finite element analyses is in general required to give an adequate description of the non-linearities involved. Analyses of a large number of short-term environmental conditions considering stochastic wave loading are required to give a representative description of the long-term fatigue loading on the structure. Short term fatigue damage is established by means of rain-flow cycle (RFC) counting in each stationary short-term condition. It is has been experienced that significant statistical uncertainties can be present in the short-term fatigue damage estimates. This is because the accumulated fatigue damage in a stationary condition normally has significant contribution from the largest stress cycles in the realisation. Selection of proper simulation length is hence essential to obtain reliable fatigue life estimates. Applicable codes and standards for risers and umbilicals provide Design Fatigue Factors (DFF) to secure adequate safety against failure due to wave induced fatigue. The total uncertainty in the calculated fatigue damage comes from various sources and the DFFs in e.g. DNV-OS-F201 “Dynamic Risers” and API-RP-2RD corresponds to a certain uncertainty level in the fatigue damage estimate. A recommended target value for the statistical uncertainty of the fatigue damage estimates is given with basis in these design codes. The objective of this paper is to give a description of a methodology recommended for time domain fatigue assessment. Special focus will be on the importance of adequate simulation time for predicting the short-term fatigue damage and selection of the short-term seastates in the scatter diagram. Statistical uncertainty is one source that the analyst actually can influence by selecting proper analysis methodology. A statistical uncertainty meassure can be used to evaluate the robustness in the estimated fatigue life. Assessment of statistical uncertainty in fatigue damage estimate is demonstrated by case studies. The fatigue assessment methodology discussed in this paper, will be described in an update of DNV-RP-F204 “Riser Fatigue” 2010.
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Ruiz Maraggi, Leopoldo M., Larry W. Lake, and Mark P. Walsh. "Bayesian Predictive Performance Assessment of Rate-Time Models for Unconventional Production Forecasting." In SPE Europec featured at 82nd EAGE Conference and Exhibition. SPE, 2021. http://dx.doi.org/10.2118/205151-ms.

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Abstract A common industry practice is to select a particular model from a set of models to history match oil production and estimate reserves by extrapolation. Future production forecasting is usually done in this deterministic way. However, this approach neglects: a) model uncertainty, and b) quantification of uncertainty of future production forecasts. The current study evaluates the predictive accuracy of rate-time models to forecast production over a set of tight oil wells of West Texas. We present the application of an accuracy metric that evaluates the uncertainty of our models' estimates: the expected log predictive density (elpd). This work assesses the predictive performance of two empirical models—the Arps hyperbolic and the logistic growth models—and two physics-based models—scaled slightly compressible single-phase and scaled two-phase (oil and gas) solutions of the diffusivity equation. These models are arbitrarily selected for the purpose of illustrating the statistical procedure shown in this paper. First, we perform classical regression with the models and evaluate their predictive performance using frequentist (point estimates) metrics such as R2, the Akaike information criteria (AIC), and hindcasting. Second, we generate probabilistic production forecasts using Bayesian inference for each model. Third, we evaluate the predictive accuracy of the models using the elpd accuracy metric. This metric evaluates a measure of out-of-sample predictive performance. We apply both adjusted-within-sample and cross-validation techniques. The adjusted within-sample method is the widely applicable information criteria (WAIC). The cross-validation techniques are hindcasting and leave-one-out (LOO-CV) method. The results of this research are the following. First, we illustrate that the assessment of a model's predictive accuracy depends on whether we use frequentist or Bayesian approaches. This is an important finding in this work. The frequentist approach relies on point estimates while the Bayesian approach considers the uncertainty of our models' estimates. From a frequentist or classical standpoint, all of the models under study yielded very similar results which made it difficult to determine which model yielded the best predictive performance. From a Bayesian standpoint, however, we determined that the logistic growth model yielded a best match in 81 of 130 wells in our sample play and the two-phase physics-based model yielded a best match in 39 of the wells. In addition, we show that WAIC and LOO-CV present similar results for each model, a thing to expect because of their asymptotical equivalence. Finally, Our observations regarding the different models are subject to the dataset under study wherein a majority of the wells are in transient flow. The present study provides tools to evaluate the predictive accuracy of models used to forecast (extrapolate) production of tight oil wells. The elpd is an accuracy metric useful to evaluate the uncertainty of our models' estimates and compare their predictive performance since it assesses distributions instead of point estimates. To our knowledge, the proposed approach is a novel and an appropriate technique to evaluate the predictive accuracy of models to forecast hydrocarbon production.
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Tarrahi, Mohammadali, and Sardar Afra. "Markov-Chain Monte Carlo with Locally Varying Mean Kriging for Improved Reservoir Model Calibration and Uncertainty Assessment." In SPE Europec featured at 78th EAGE Conference and Exhibition. Society of Petroleum Engineers, 2016. http://dx.doi.org/10.2118/180189-ms.

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Ishizaki, Yoichi, Futoshi Yonekawa, Takeaki Yumoto, Teppei Suzuki, and Shuji Hijikawa. "Remaining Life Assessment of an External Pressure Vessel in Creep Range and Inspection Findings." In ASME 2017 Pressure Vessels and Piping Conference. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/pvp2017-65194.

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As widely recognized in the industry, it is important to evaluate the creep damage of an elevated temperature vessel so that the mechanical integrity of the vessel can be achieved through the adequate repair and replacement planning. This is quite straight forward procedure for internal pressure vessels. For an external pressure vessel, it is not easy to assess the creep damage due to the complexity of the creep buckling analysis. Eventually, creep cavity evaluation technique without identifying the correct stress distribution has been used so often. However, due to the uncertainty of the technique itself plus conservative mindset of the inspectors, it tends to leads to an excessive maintenance most of the cases. In order to conduct a reasonable remaining life assessment, it is desirable to use the creep cavity inspection in conjunction with another assessment technique such as FEM creep analysis as stated in API 579-1/ASME FFS-1 10.5.7. In this paper, comprehensive approach with FEM and field inspection such as creep cavity evaluation to reinforce the uncertainty of each method will be demonstrated.
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Cosham, Andrew, and Kenneth A. Macdonald. "ECAs, Probabilities and Axial Misalignment." In ASME 2018 37th International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/omae2018-77647.

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An engineering critical assessment (ECA) is commonly conducted during the design of an offshore pipeline in order to determine the tolerable size of flaws in the girth welds. API 579-1/ASME FFS-1 2016 and BS 7910:2013+A1:2015 Incorporating Corrigenda Nos. 1 and 2 give guidance on conducting fitness-for-service assessments of cracks and crack-like flaws. The essential data required for an assessment (nature, position and orientation of flaw; structural and weld geometry; stresses; yield and tensile strength; fracture toughness; etc.) is subject to uncertainty. That uncertainty is addressed through the use of bounding values. The use of extreme bounding values might be overly-conservative. A sensitivity analysis is one way of investigating the sensitivity of the results of an assessment to the input data. A structural reliability-based assessment (a probabilistic assessment) is an alternative. A probabilistic assessment is significantly more complicated than a deterministic assessment. API 579-1/ASME FFS-1 and BS 7910:2013 note that a sensitivity analysis, partial safety factors or a probabilistic analysis can be used to evaluate uncertainties in the input parameters. Annex K of BS 7910:2013 gives partial safety factors for different combinations of target reliability and variability of input data. ISO 16708:2006 gives guidance on the use of structural reliability-based limit-state methods in the design and operation of pipelines. The structural reliability-based assessment of circumferentially-orientated, surface crack-like flaw in a girth weld in a pipeline is used to illustrate the significance of the distributions of the difference between the wall thickness and the ovality (out-of-roundness) of two pipes when calculating the bounding value of the stress concentration factor due to axial misalignment. The (assumed) distributions of diameter, wall thickness, out-of-roundness, yield strength, etc. are based on Annex B of ISO 16708:2006. The (nominal) probability of failure is calculated. It is then used to inform the choice of an appropriate bounding value (i.e. a characteristic value) for axial misalignment.
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Звіти організацій з теми "Uncertainty assessment in APT"

1

Webster, Mort D. RECOVERY ACT - Methods for Decision under Technological Change Uncertainty and Risk Assessment for Integrated Assessment of Climate Change. Office of Scientific and Technical Information (OSTI), November 2015. http://dx.doi.org/10.2172/1227193.

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Webster, Mort David. RECOVERY ACT - Methods for Decision under Technological Change Uncertainty and Risk Assessment for Integrated Assessment of Climate Change. Office of Scientific and Technical Information (OSTI), March 2015. http://dx.doi.org/10.2172/1172111.

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Mort Webster. Uncertainty in Integrated Assessment Scenarios. Office of Scientific and Technical Information (OSTI), October 2005. http://dx.doi.org/10.2172/883668.

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Schmidt, Henrik, Arthur B. Baggeroer, and Jerome H. Milgram. Uncertainty DRI Adaptive Rapid Environmental Assessment. Fort Belvoir, VA: Defense Technical Information Center, September 2003. http://dx.doi.org/10.21236/ada629749.

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Wilhite, E. L. Preliminary Performance Assessment for Disposal of APT and CLWR/TEF Wastes at SRS. Office of Scientific and Technical Information (OSTI), October 1998. http://dx.doi.org/10.2172/4943.

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Rosser, Katy, Iulia Gherman, Erica Kintz, Paul Cook, and Anthony WIlson. Assessment of the risk to consumers as a result of disruption to the cold chain during direct supply of Qurbani meat and offal. Food Standards Agency, June 2022. http://dx.doi.org/10.46756/sci.fsa.nuc910.

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Qurbani is a religious practice that takes place during Eid al-Adha. Consumers practicing Qurbani typically wish to collect meat and red offal within a short time after slaughter, which means these products cannot complete normal chilling processes before leaving the slaughterhouse. This could permit greater growth of pathogens and has the potential to increase the risk of consumer illness. The FSA is working with industry and stakeholder groups to ensure that the risk to consumers under these conditions remains at an acceptable level. To help inform these discussions, the FSA commissioned this assessment to understand the difference in risk from allowing meat and offal to be provided to consumers without the normal chilling process. The microbiological team at the FSA have analysed scientific literature, expert opinion and business and consumer survey data to assess the effect of disrupting the cold chain on pathogens in Qurbani meat. The pathogens that were chosen for inclusion in this assessment are non-typhoidal Salmonella enterica, Shiga toxin-producing Escherichia coli, and Clostridium perfringens. Their growth characteristics and prevalence in beef, lamb and goat meat and offal are discussed. The assessment concluded that given the reported variation in the process, there were two important scenarios with distinct outcomes. In the typical scenario, which is the most likely outcome based on the collected data, there is no significant difference in risk to consumer health compared to normal chilling processes, and the risk level was established as Very Low (“very rare but cannot be excluded”). In a reasonably foreseeable worst-case scenario, Salmonella spp. and STEC levels may increase, presenting an increased risk to the consumer. This risk level was established as Low (“rare but does occur”). We also identified several areas where more evidence would be helpful, and as a result identified a High level of uncertainty in our conclusion.
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Brown, J., L. H. J. Goossens, and B. C. P. Kraan. Probabilistic accident consequence uncertainty analysis: Food chain uncertainty assessment. Volume 2: Appendices. Office of Scientific and Technical Information (OSTI), June 1997. http://dx.doi.org/10.2172/510291.

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Harper, F. T., M. L. Young, L. A. Miller, S. C. Hora, C. H. Lui, L. H. J. Goossens, R. M. Cooke, J. Paesler-Sauer, and J. C. Helton. Probabilistic accident consequence uncertainty analysis: Dispersion and deposition uncertainty assessment, main report. Office of Scientific and Technical Information (OSTI), January 1995. http://dx.doi.org/10.2172/10125585.

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Brown, J., L. H. J. Goossens, and B. C. P. Kraan. Probabilistic accident consequence uncertainty analysis: Food chain uncertainty assessment. Volume 1: Main report. Office of Scientific and Technical Information (OSTI), June 1997. http://dx.doi.org/10.2172/510290.

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Goossens, L. H. J., B. C. P. Kraan, R. M. Cooke, J. D. Harrison, F. T. Harper, and S. C. Hora. Probabilistic accident consequence uncertainty analysis -- Uncertainty assessment for internal dosimetry. Volume 2: Appendices. Office of Scientific and Technical Information (OSTI), April 1998. http://dx.doi.org/10.2172/291005.

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