Download or read book Uncertainty Analysis of EUSES written by T. Jager and published by . This book was released on 1997 with total page 80 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Uncertainty Analysis of EUSES written by Dirk Tjalling Jager and published by . This book was released on 1998 with total page 31 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Uncertainty characterization in risk analysis for decision making practice written by Enrico Zio and published by FonCSI. This book was released on 2012-05-01 with total page 63 pages. Available in PDF, EPUB and Kindle. Book excerpt: This document provides an overview of sources of uncertainty in probabilistic risk analysis. For each phase of the risk analysis process (system modeling, hazard identification, estimation of the probability and consequences of accident sequences, risk evaluation), the authors describe and classify the types of uncertainty that can arise. The document provides : a description of the risk assessment process, as used in hazardous industries such as nuclear power and offshore oil and gas extraction ; a classification of sources of uncertainty (both epistemic and aleatory) and a description of techniques for uncertainty representation ; a description of the different steps involved in a Probabilistic Risk Assessement (PRA) or Quantitative Risk Assessment (QRA), and an analysis of the types of uncertainty that can affect each of these steps ; annexes giving an overview of a number of tools used during probabilistic risk assessment, including the HAZID technique, fault trees and event tree analysis.
Download or read book Uncertainty in Risk Assessment written by Terje Aven and published by John Wiley & Sons. This book was released on 2013-12-17 with total page 152 pages. Available in PDF, EPUB and Kindle. Book excerpt: Explores methods for the representation and treatment of uncertainty in risk assessment In providing guidance for practical decision-making situations concerning high-consequence technologies (e.g., nuclear, oil and gas, transport, etc.), the theories and methods studied in Uncertainty in Risk Assessment have wide-ranging applications from engineering and medicine to environmental impacts and natural disasters, security, and financial risk management. The main focus, however, is on engineering applications. While requiring some fundamental background in risk assessment, as well as a basic knowledge of probability theory and statistics, Uncertainty in Risk Assessment can be read profitably by a broad audience of professionals in the field, including researchers and graduate students on courses within risk analysis, statistics, engineering, and the physical sciences. Uncertainty in Risk Assessment: Illustrates the need for seeing beyond probability to represent uncertainties in risk assessment contexts. Provides simple explanations (supported by straightforward numerical examples) of the meaning of different types of probabilities, including interval probabilities, and the fundamentals of possibility theory and evidence theory. Offers guidance on when to use probability and when to use an alternative representation of uncertainty. Presents and discusses methods for the representation and characterization of uncertainty in risk assessment. Uses examples to clearly illustrate ideas and concepts.
Download or read book The Uncertainty Analysis of Model Results written by Eduard Hofer and published by Springer. This book was released on 2018-05-02 with total page 355 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a practical guide to the uncertainty analysis of computer model applications. Used in many areas, such as engineering, ecology and economics, computer models are subject to various uncertainties at the level of model formulations, parameter values and input data. Naturally, it would be advantageous to know the combined effect of these uncertainties on the model results as well as whether the state of knowledge should be improved in order to reduce the uncertainty of the results most effectively. The book supports decision-makers, model developers and users in their argumentation for an uncertainty analysis and assists them in the interpretation of the analysis results.
Download or read book Quality Assurance of Exposure Models for Environmental Risk Assessment of Substances written by Stefan Schwartz and published by GRIN Verlag. This book was released on 2001-11-06 with total page 204 pages. Available in PDF, EPUB and Kindle. Book excerpt: Doctoral Thesis / Dissertation from the year 2000 in the subject Mathematics - Applied Mathematics, grade: 1,0 (A), University of Osnabrück (Institute for Environmental System Research, Mathematics/Computer Science), language: English, abstract: Summary Environmental risk assessment of chemical substances in the European Union is based on a harmonised scheme. The required models and parameters are laid down in the Technical Guidance Document (TGD) and are implemented in the EUSES software. Although the results may have a considerable ecological and economic impact, guidance is rarely given on the applicability of the framework. To fill this gap, an evaluation study of the TGD exposure models was carried out. In particular, the models for estimating chemical intake by humans were investigated. These models, which are a key component in risk assessment, involve a quantification of human contact with environmental contamination in various media of exposure through various exposure pathways. The objective of this study was two-fold: firstly, to develop an evaluation methodology, since no appropriate approach is available in the scientific literature. Secondly, to elaborate applicability and limitations of the models and to provide proposals for their improvement. The principles of model evaluation in terms of quality assurance, model validation and software evaluation were elaborated and a suitable evaluation protocol for chemical risk assessment models was developed. Since scientific theories and the mathematical models embedded therein cannot be proved as true, a pragmatic meaning of validation is required, of which the primary purpose is to increase the level of confidence placed in the model. The accuracy of the model outcome is a necessary, but insufficient criterion for the quality assurance of models. A wider approach is required which examines the scientific inference that can be made about models with regard to their intended purpose. By reviewing the literature on the validation problem, it was found that all the facets of validation can be assigned to generic (internal) and task-specific (external) properties of a model. In this context, sensitivity and uncertainty analyses are essential to tackle the issues of uncertainty. Sensitivity analysis aims to ascertain how a given model depends upon the information fed into it. Uncertainty analysis aims to quantify the uncertainty regarding what comes out of the model. It was argued that targeted uncertainty analysis and sensitivity analysis, as a part of it, is capable of reducing critical uncertainties and represents an essential contribution for assuring the quality of a model. [...]
Download or read book Overview of Methods for Uncertainty Analysis and Sensitivity Analysis in Probabilistic Risk Assessment written by Ronald L. Iman and published by . This book was released on 1984 with total page 9 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Sensitivity and Uncertainty Analysis Volume II written by Dan G. Cacuci and published by CRC Press. This book was released on 2005-05-16 with total page 367 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 convective model for climate simulations, and large-scale models for numerical weather prediction.
Download or read book Literature review of methods for representing uncertainty written by Enrico Zio and published by FonCSI. This book was released on 2013-03-01 with total page 61 pages. Available in PDF, EPUB and Kindle. Book excerpt: This document provides a critical review of different frameworks for uncertainty analysis, in a risk analysis context : classical probabilistic analysis, imprecise probability (interval analysis), probability bound analysis, evidence theory, and possibility theory. The driver of the critical analysis is the decision-making process and the need to feed it with representative information derived from the risk assessment, to robustly support the decision. Technical details of the different frameworks are exposed only to the extent necessary to analyze and judge how these contribute to the communication of risk and the representation of the associated uncertainties to decision-makers, in the typical settings of high-consequence risk analysis of complex systems with limited knowledge on their behaviour.
Download or read book Sensitivity Uncertainty Analysis Volume 1 written by Dan G. Cacuci and published by CRC Press. This book was released on 2003-05-28 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: As computer-assisted modeling and analysis of physical processes have continued to grow and diversify, sensitivity and uncertainty analyses have become indispensable investigative scientific tools in their own right. While most techniques used for these analyses are well documented, there has yet to appear a systematic treatment of the method based
Download or read book Uncertainty Analysis for Engineers and Scientists written by Faith A. Morrison and published by Cambridge University Press. This book was released on 2021-01-07 with total page 389 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build the skills for determining appropriate error limits for quantities that matter with this essential toolkit. Understand how to handle a complete project and how uncertainty enters into various steps. Provides a systematic, worksheet-based process to determine error limits on measured quantities, and all likely sources of uncertainty are explored, measured or estimated. Features instructions on how to carry out error analysis using Excel and MATLAB®, making previously tedious calculations easy. Whether you are new to the sciences or an experienced engineer, this useful resource provides a practical approach to performing error analysis. Suitable as a text for a junior or senior level laboratory course in aerospace, chemical and mechanical engineering, and for professionals.
Download or read book Experimental Uncertainty Analysis A Textbook for Science and Engineering Students written by Supreet Singh Bahga and published by Supreet Singh Bahga. This book was released on 2021-07-06 with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt: Uncertainties are inevitable in any experimental measurement. Therefore, it is essential for science and engineering graduates to design and develop reliable experiments and estimate the uncertainty in the measurements. This book describes the methods and application of uncertainty analysis during the planning, data analysis, and reporting stages of an experiment. This book is aimed at postgraduate and advanced undergraduate students of various branches of science and engineering. The book teaches methods for estimating random and systematic uncertainties and combining them to determine the overall uncertainty in a measurement. In addition, the method for propagating measurement uncertainties in the calculated result is discussed. The book also discusses methods of reducing the uncertainties through proper instrumentation, data acquisition, and experiment planning. This book provides detailed background and assumptions underlying the uncertainty analysis techniques for the reader to understand their applicability. Various solved examples are provided to demonstrate the application of the uncertainty analysis techniques. The exercises at the end of the chapters have been chosen carefully to reinforce the concepts discussed in the text.
Download or read book Uncertainty Analysis in Engineering and Sciences Fuzzy Logic Statistics and Neural Network Approach written by Bilal M. Ayyub and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: Uncertainty has been of concern to engineers, managers and . scientists for many centuries. In management sciences there have existed definitions of uncertainty in a rather narrow sense since the beginning of this century. In engineering and uncertainty has for a long time been considered as in sciences, however, synonymous with random, stochastic, statistic, or probabilistic. Only since the early sixties views on uncertainty have ~ecome more heterogeneous and more tools to model uncertainty than statistics have been proposed by several scientists. The problem of modeling uncertainty adequately has become more important the more complex systems have become, the faster the scientific and engineering world develops, and the more important, but also more difficult, forecasting of future states of systems have become. The first question one should probably ask is whether uncertainty is a phenomenon, a feature of real world systems, a state of mind or a label for a situation in which a human being wants to make statements about phenomena, i. e. , reality, models, and theories, respectively. One cart also ask whether uncertainty is an objective fact or just a subjective impression which is closely related to individual persons. Whether uncertainty is an objective feature of physical real systems seems to be a philosophical question. This shall not be answered in this volume.
Download or read book Uncertainty in Industrial Practice written by Etienne de Rocquigny and published by John Wiley & Sons. This book was released on 2008-09-15 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt: Managing uncertainties in industrial systems is a daily challenge to ensure improved design, robust operation, accountable performance and responsive risk control. Authored by a leading European network of experts representing a cross section of industries, Uncertainty in Industrial Practice aims to provide a reference for the dissemination of uncertainty treatment in any type of industry. It is concerned with the quantification of uncertainties in the presence of data, model(s) and knowledge about the system, and offers a technical contribution to decision-making processes whilst acknowledging industrial constraints. The approach presented can be applied to a range of different business contexts, from research or early design through to certification or in-service processes. The authors aim to foster optimal trade-offs between literature-referenced methodologies and the simplified approaches often inevitable in practice, owing to data, time or budget limitations of technical decision-makers. Uncertainty in Industrial Practice: Features recent uncertainty case studies carried out in the nuclear, air & space, oil, mechanical and civil engineering industries set in a common methodological framework. Presents methods for organizing and treating uncertainties in a generic and prioritized perspective. Illustrates practical difficulties and solutions encountered according to the level of complexity, information available and regulatory and financial constraints. Discusses best practice in uncertainty modeling, propagation and sensitivity analysis through a variety of statistical and numerical methods. Reviews recent standards, references and available software, providing an essential resource for engineers and risk analysts in a wide variety of industries. This book provides a guide to dealing with quantitative uncertainty in engineering and modelling and is aimed at practitioners, including risk-industry regulators and academics wishing to develop industry-realistic methodologies.
Download or read book Probability Methods for Cost Uncertainty Analysis written by Paul R. Garvey and published by CRC Press. This book was released on 2016-01-06 with total page 526 pages. Available in PDF, EPUB and Kindle. Book excerpt: Probability Methods for Cost Uncertainty Analysis: A Systems Engineering Perspective, Second Edition gives you a thorough grounding in the analytical methods needed for modeling and measuring uncertainty in the cost of engineering systems. This includes the treatment of correlation between the cost of system elements, how to present the analysis to
Download or read book Uncertainty written by Millett Granger Morgan and published by Cambridge University Press. This book was released on 1990-08-31 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: The authors explain the ways in which uncertainty is an important factor in the problems of risk and policy analysis. This book outlines the source and nature of uncertainty, discusses techniques for obtaining and using expert judgment, and reviews a variety of simple and advanced methods for analyzing uncertainty.
Download or read book Sensitivity Analysis written by Emanuele Borgonovo and published by Springer. This book was released on 2017-04-19 with total page 291 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is an expository introduction to the methodology of sensitivity analysis of model output. It is primarily intended for investigators, students and researchers that are familiar with mathematical models but are less familiar with the techniques for performing their sensitivity analysis. A variety of sensitivity methods have been developed over the years. This monograph helps the analyst in her/his first exploration of this world. The main goal is to foster the recognition of the crucial role of sensitivity analysis methods as the techniques that allow us to gain insights from quantitative models. Also, exercising rigor in performing sensitivity analysis becomes increasingly relevant both to decision makers and modelers. The book helps the analyst in structuring her/his sensitivity analysis quest properly, so as to obtain the correct answer to the corresponding managerial question. The first part of the book covers Deterministic Methods, including Tornado Diagrams; One-Way Sensitivity Analysis; Differentiation-Based Methods and Local Sensitivity Analysis with Constraints. The second part looks at Probabilistic Methods, including Regression-Based methods, Variance-Based Methods, and Distribution-Based methods. The final section looks at Applications, including capital budgeting, sensitivity analysis in climate change modelling and in the risk assessment of a lunar space mission.
