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Author :
Publisher :
ISBN 13 : 9783844375503
Total Pages : 0 pages
Book Rating : 4.3/5 (755 download)
Download or read book Improved Sensitivity Analysis Using State Dependent Parameter Models written by and published by . This book was released on 2011 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author :
Publisher :
ISBN 13 : 9789279020360
Total Pages : 31 pages
Book Rating : 4.0/5 (23 download)
Download or read book Improved and Accelerated Sensitivity Analysis Using State Dependent Parameter Models written by and published by . This book was released on 2006 with total page 31 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this paper we apply State Dependent Parameter (SDP) modelling (a model estimation approach, based on recursive filtering and smoothing estimation) to estimate the variance based main effect sensitivity indices of computational models (a popular method for quantitative sensitivity analysis). The method is conceptually simple and all measures of interest are computed using a single set of model runs. It is flexible because in principle it can be applied with any available type of Monte Carlo sample. It is extremely efficient, especially when coupled with efficient sampling methods, such as the quasi-random LP-tau sequence, it allows for a strong reduction in the cost of the analysis. Moreover, the method also allows us to estimate the first order terms of the High Dimensional Model Representation of the model under analysis.
Author : Andrea Saltelli
Publisher : John Wiley & Sons
ISBN 13 : 9780470725177
Total Pages : 304 pages
Book Rating : 4.7/5 (251 download)
Download or read book Global Sensitivity Analysis written by Andrea Saltelli and published by John Wiley & Sons. This book was released on 2008-02-28 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: Complex mathematical and computational models are used in all areas of society and technology and yet model based science is increasingly contested or refuted, especially when models are applied to controversial themes in domains such as health, the environment or the economy. More stringent standards of proofs are demanded from model-based numbers, especially when these numbers represent potential financial losses, threats to human health or the state of the environment. Quantitative sensitivity analysis is generally agreed to be one such standard. Mathematical models are good at mapping assumptions into inferences. A modeller makes assumptions about laws pertaining to the system, about its status and a plethora of other, often arcane, system variables and internal model settings. To what extent can we rely on the model-based inference when most of these assumptions are fraught with uncertainties? Global Sensitivity Analysis offers an accessible treatment of such problems via quantitative sensitivity analysis, beginning with the first principles and guiding the reader through the full range of recommended practices with a rich set of solved exercises. The text explains the motivation for sensitivity analysis, reviews the required statistical concepts, and provides a guide to potential applications. The book: Provides a self-contained treatment of the subject, allowing readers to learn and practice global sensitivity analysis without further materials. Presents ways to frame the analysis, interpret its results, and avoid potential pitfalls. Features numerous exercises and solved problems to help illustrate the applications. Is authored by leading sensitivity analysis practitioners, combining a range of disciplinary backgrounds. Postgraduate students and practitioners in a wide range of subjects, including statistics, mathematics, engineering, physics, chemistry, environmental sciences, biology, toxicology, actuarial sciences, and econometrics will find much of use here. This book will prove equally valuable to engineers working on risk analysis and to financial analysts concerned with pricing and hedging.
Author : Andrea Saltelli
Publisher : John Wiley & Sons
ISBN 13 : 047087094X
Total Pages : 232 pages
Book Rating : 4.4/5 (78 download)
Download or read book Sensitivity Analysis in Practice written by Andrea Saltelli and published by John Wiley & Sons. This book was released on 2004-07-16 with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sensitivity analysis should be considered a pre-requisite for statistical model building in any scientific discipline where modelling takes place. For a non-expert, choosing the method of analysis for their model is complex, and depends on a number of factors. This book guides the non-expert through their problem in order to enable them to choose and apply the most appropriate method. It offers a review of the state-of-the-art in sensitivity analysis, and is suitable for a wide range of practitioners. It is focussed on the use of SIMLAB – a widely distributed freely-available sensitivity analysis software package developed by the authors – for solving problems in sensitivity analysis of statistical models. Other key features: Provides an accessible overview of the current most widely used methods for sensitivity analysis. Opens with a detailed worked example to explain the motivation behind the book. Includes a range of examples to help illustrate the concepts discussed. Focuses on implementation of the methods in the software SIMLAB - a freely-available sensitivity analysis software package developed by the authors. Contains a large number of references to sources for further reading. Authored by the leading authorities on sensitivity analysis.
Author : Dan Gabriel Cacuci
Publisher : Springer Nature
ISBN 13 : 3030963640
Total Pages : 373 pages
Book Rating : 4.0/5 (39 download)
Download or read book The nth-Order Comprehensive Adjoint Sensitivity Analysis Methodology, Volume I written by Dan Gabriel Cacuci and published by Springer Nature. This book was released on 2022-07-19 with total page 373 pages. Available in PDF, EPUB and Kindle. Book excerpt: The computational models of physical systems comprise parameters, independent and dependent variables. Since the physical processes themselves are seldom known precisely and since most of the model parameters stem from experimental procedures which are also subject to imprecisions, the results predicted by these models are also imprecise, being affected by the uncertainties underlying the respective model. The functional derivatives (also called “sensitivities”) of results (also called “responses”) produced by mathematical/computational models are needed for many purposes, including: (i) understanding the model by ranking the importance of the various model parameters; (ii) performing “reduced-order modeling” by eliminating unimportant parameters and/or processes; (iii) quantifying the uncertainties induced in a model response due to model parameter uncertainties; (iv) performing “model validation,” by comparing computations to experiments to address the question “does the model represent reality?” (v) prioritizing improvements in the model; (vi) performing data assimilation and model calibration as part of forward “predictive modeling” to obtain best-estimate predicted results with reduced predicted uncertainties; (vii) performing inverse “predictive modeling”; (viii) designing and optimizing the system. This 3-Volume monograph describes a comprehensive adjoint sensitivity analysis methodology, developed by the author, which enables the efficient and exact computation of arbitrarily high-order sensitivities of model responses in large-scale systems comprising many model parameters. The qualifier “comprehensive” is employed to highlight that the model parameters considered within the framework of this methodology also include the system’s uncertain boundaries and internal interfaces in phase-space. The model’s responses can be either scalar-valued functionals of the model’s parameters and state variables (e.g., as customarily encountered in optimization problems) or general function-valued responses. Since linear operators admit bona-fide adjoint operators, responses of models that are linear in the state functions (i.e., dependent variables) can depend simultaneously on both the forward and the adjoint state functions. Hence, the sensitivity analysis of such responses warrants the treatment of linear systems in their own right, rather than treating them as particular cases of nonlinear systems. This is in contradistinction to responses for nonlinear systems, which can depend only on the forward state functions, since nonlinear operators do not admit bona-fide adjoint operators (only a linearized form of a nonlinear operator may admit an adjoint operator). Thus, Volume 1 of this book presents the mathematical framework of the nth-Order Comprehensive Adjoint Sensitivity Analysis Methodology for Response-Coupled Forward/Adjoint Linear Systems (abbreviated as “nth-CASAM-L”), which is conceived for the most efficient computation of exactly obtained mathematical expressions of arbitrarily-high-order (nth-order) sensitivities of a generic system response with respect to all of the parameters underlying the respective forward/adjoint systems. Volume 2 of this book presents the application of the nth-CASAM-L to perform a fourth-order sensitivity and uncertainty analysis of an OECD/NEA reactor physics benchmark which is representative of a large-scale model comprises many (21,976) uncertain parameters, thereby amply illustrating the unique potential of the nth-CASAM-L to enable the exact and efficient computation of chosen high-order response sensitivities to model parameters. Volume 3 of this book presents the “nth-Order Comprehensive Adjoint Sensitivity Analysis Methodology for Nonlinear Systems” (abbreviation: nth-CASAM-N) for the practical, efficient, and exact computation of arbitrarily-high order sensitivities of responses to model parameters for systems that are also nonlinear in their underlying state functions. Such computations are not feasible with any other methodology. The application of the nth-CASAM-L and the nth-CASAM-N overcomes the so-called “curse of dimensionality” in sensitivity and uncertainty analysis, thus revolutionizing all of the fields of activities which require accurate computation of response sensitivities. Since this monograph includes many illustrative, fully worked-out, paradigm problems, it can serve as a textbook or as supplementary reading for graduate courses in academic departments in the natural sciences and engineering.
Author : Agency for Health Care Research and Quality (U.S.)
Publisher : Government Printing Office
ISBN 13 : 1587634236
Total Pages : 236 pages
Book Rating : 4.5/5 (876 download)
Download or read book Developing a Protocol for Observational Comparative Effectiveness Research: A User's Guide written by Agency for Health Care Research and Quality (U.S.) and published by Government Printing Office. This book was released on 2013-02-21 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: This User’s Guide is a resource for investigators and stakeholders who develop and review observational comparative effectiveness research protocols. It explains how to (1) identify key considerations and best practices for research design; (2) build a protocol based on these standards and best practices; and (3) judge the adequacy and completeness of a protocol. Eleven chapters cover all aspects of research design, including: developing study objectives, defining and refining study questions, addressing the heterogeneity of treatment effect, characterizing exposure, selecting a comparator, defining and measuring outcomes, and identifying optimal data sources. Checklists of guidance and key considerations for protocols are provided at the end of each chapter. The User’s Guide was created by researchers affiliated with AHRQ’s Effective Health Care Program, particularly those who participated in AHRQ’s DEcIDE (Developing Evidence to Inform Decisions About Effectiveness) program. Chapters were subject to multiple internal and external independent reviews. More more information, please consult the Agency website: www.effectivehealthcare.ahrq.gov)
Author : Peter A. Vanrolleghem
Publisher : IWA Publishing
ISBN 13 : 1843392232
Total Pages : 353 pages
Book Rating : 4.8/5 (433 download)
Download or read book Modelling Aspects of Water Framework Directive Implementation written by Peter A. Vanrolleghem and published by IWA Publishing. This book was released on 2010-04-30 with total page 353 pages. Available in PDF, EPUB and Kindle. Book excerpt: Special Offer: Water Framework Directive Series Set. To buy all four titles including Volume 3 and save £100, visit: http://iwapublishing.com/books/9781780400013/water-framework-directive-series-set Modelling Aspects of Water Framework Directive Implementation: Volume 1 is a concrete outcome from the Harmoni-CA concerted action as part of a 4-volume series of Guidance Reports that guide water professionals through the implementation process of the Water Framework Directive, with a focus on the use of ICT-tools (and in particular modelling). They are complementary to the Guidance Documents produced by the EU Directorate General for Environment. Water resources planning and management and the development of appropriate policies require methodologies and tools that are able to support systematic, integrative and multidisciplinary assessments at various scales. It also requires the quantification of various uncertainties in both data and models, and the incorporation of stakeholders participation and institutional mechanisms into the various tools and risk assessment methodologies, to help decision makers understand and evaluate alternative measures and decisions. The other three volumes in the Water Framework Directive Series are: Water Framework Directive: Model supported Implementation - A Water Manager’s Guide edited by Fred Hattermann and Zbigniew W Kundzewicz Integrated Assessment for WFD implementation: Data, economic and human dimension - Volume 2, edited by Peter A. Vanrolleghem Decision support for WFD implementation - Volume 3, edited by Peter A. Vanrolleghem. Visit the IWA WaterWiki to read and share material related to this title: http://www.iwawaterwiki.org/xwiki/bin/view/Articles/IntegratedAssessmentforWaterFrameworkDirectiveImplementation
Author : National Research Council
Publisher : National Academies Press
ISBN 13 : 030918651X
Total Pages : 163 pages
Book Rating : 4.3/5 (91 download)
Download or read book The Prevention and Treatment of Missing Data in Clinical Trials written by National Research Council and published by National Academies Press. This book was released on 2010-12-21 with total page 163 pages. Available in PDF, EPUB and Kindle. Book excerpt: Randomized clinical trials are the primary tool for evaluating new medical interventions. Randomization provides for a fair comparison between treatment and control groups, balancing out, on average, distributions of known and unknown factors among the participants. Unfortunately, these studies often lack a substantial percentage of data. This missing data reduces the benefit provided by the randomization and introduces potential biases in the comparison of the treatment groups. Missing data can arise for a variety of reasons, including the inability or unwillingness of participants to meet appointments for evaluation. And in some studies, some or all of data collection ceases when participants discontinue study treatment. Existing guidelines for the design and conduct of clinical trials, and the analysis of the resulting data, provide only limited advice on how to handle missing data. Thus, approaches to the analysis of data with an appreciable amount of missing values tend to be ad hoc and variable. The Prevention and Treatment of Missing Data in Clinical Trials concludes that a more principled approach to design and analysis in the presence of missing data is both needed and possible. Such an approach needs to focus on two critical elements: (1) careful design and conduct to limit the amount and impact of missing data and (2) analysis that makes full use of information on all randomized participants and is based on careful attention to the assumptions about the nature of the missing data underlying estimates of treatment effects. In addition to the highest priority recommendations, the book offers more detailed recommendations on the conduct of clinical trials and techniques for analysis of trial data.
Author : Emmanuel Laporte
Publisher : Springer Science & Business Media
ISBN 13 : 1461200695
Total Pages : 202 pages
Book Rating : 4.4/5 (612 download)
Download or read book Numerical Methods in Sensitivity Analysis and Shape Optimization written by Emmanuel Laporte and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sensitivity analysis and optimal shape design are key issues in engineering that have been affected by advances in numerical tools currently available. This book, and its supplementary online files, presents basic optimization techniques that can be used to compute the sensitivity of a given design to local change, or to improve its performance by local optimization of these data. The relevance and scope of these techniques have improved dramatically in recent years because of progress in discretization strategies, optimization algorithms, automatic differentiation, software availability, and the power of personal computers. Numerical Methods in Sensitivity Analysis and Shape Optimization will be of interest to graduate students involved in mathematical modeling and simulation, as well as engineers and researchers in applied mathematics looking for an up-to-date introduction to optimization techniques, sensitivity analysis, and optimal design.
Author : Dan Gabriel Cacuci
Publisher :
ISBN 13 : 9788303096364
Total Pages : 0 pages
Book Rating : 4.0/5 (963 download)
Download or read book The Nth-order Comprehensive Adjoint Sensitivity Analysis Methodology written by Dan Gabriel Cacuci and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The computational models of physical systems comprise parameters, independent and dependent variables. Since the physical processes themselves are seldom known precisely and since most of the model parameters stem from experimental procedures which are also subject to imprecisions, the results predicted by these models are also imprecise, being affected by the uncertainties underlying the respective model. The functional derivatives (also called "sensitivities") of results (also called "responses") produced by mathematical/computational models are needed for many purposes, including: (i) understanding the model by ranking the importance of the various model parameters; (ii) performing "reduced-order modeling" by eliminating unimportant parameters and/or processes; (iii) quantifying the uncertainties induced in a model response due to model parameter uncertainties; (iv) performing "model validation," by comparing computations to experiments to address the question "does the model represent reality?" prioritizing improvements in the model; (vi) performing data assimilation and model calibration as part of forward "predictive modeling" to obtain best-estimate predicted results with reduced predicted uncertainties; (vii) performing inverse "predictive modeling" designing and optimizing the system. This 3-Volume monograph describes a comprehensive adjoint sensitivity analysis methodology, developed by the author, which enables the efficient and exact computation of arbitrarily high-order sensitivities of model responses in large-scale systems comprising many model parameters. The qualifier "comprehensive" is employed to highlight that the model parameters considered within the framework of this methodology also include the systems uncertain boundaries and internal interfaces in phase-space. The models responses can be either scalar-valued functionals of the models parameters and state variables (e.g., as customarily encountered in optimization problems) or general function-valued responses. Since linear operators admit bona-fide adjoint operators, responses of models that are linear in the state functions (i.e., dependent variables) can depend simultaneously on both the forward and the adjoint state functions. Hence, the sensitivity analysis of such responses warrants the treatment of linear systems in their own right, rather than treating them as particular cases of nonlinear systems. This is in contradistinction to responses for nonlinear systems, which can depend only on the forward state functions, since nonlinear operators do not admit bona-fide adjoint operators (only a linearized form of a nonlinear operator may admit an adjoint operator). Thus, Volume 1 of this book presents the mathematical framework of the nth-Order Comprehensive Adjoint Sensitivity Analysis Methodology for Response-Coupled Forward/Adjoint Linear Systems (abbreviated as "nth-CASAM-L"), which is conceived for the most efficient computation of exactly obtained mathematical expressions of arbitrarily-high-order (nth-order) sensitivities of a generic system response with respect to all of the parameters underlying the respective forward/adjoint systems. Volume 2 of this book presents the application of the nth-CASAM-L to perform a fourth-order sensitivity and uncertainty analysis of an OECD/NEA reactor physics benchmark which is representative of a large-scale model comprises many (21,976) uncertain parameters, thereby amply illustrating the unique potential of the nth-CASAM-L to enable the exact and efficient computation of chosen high-order response sensitivities to model parameters. Volume 3 of this book presents the "nth-Order Comprehensive Adjoint Sensitivity Analysis Methodology for Nonlinear Systems" (abbreviation: nth-CASAM-N) for the practical, efficient, and exact computation of arbitrarily-high order sensitivities of responses to model parameters for systems that are also nonlinear in their underlying state functions. Such computations are not feasible with any other methodology. The application of the nth-CASAM-L and the nth-CASAM-N overcomes the so-called "curse of dimensionality" in sensitivity and uncertainty analysis, thus revolutionizing all of the fields of activities which require accurate computation of response sensitivities. Since this monograph includes many illustrative, fully worked-out, paradigm problems, it can serve as a textbook or as supplementary reading for graduate courses in academic departments in the natural sciences and engineering.
Author : Hal Caswell
Publisher : Springer
ISBN 13 : 3030105342
Total Pages : 308 pages
Book Rating : 4.0/5 (31 download)
Download or read book Sensitivity Analysis: Matrix Methods in Demography and Ecology written by Hal Caswell and published by Springer. This book was released on 2019-04-02 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book shows how to use sensitivity analysis in demography. It presents new methods for individuals, cohorts, and populations, with applications to humans, other animals, and plants. The analyses are based on matrix formulations of age-classified, stage-classified, and multistate population models. Methods are presented for linear and nonlinear, deterministic and stochastic, and time-invariant and time-varying cases. Readers will discover results on the sensitivity of statistics of longevity, life disparity, occupancy times, the net reproductive rate, and statistics of Markov chain models in demography. They will also see applications of sensitivity analysis to population growth rates, stable population structures, reproductive value, equilibria under immigration and nonlinearity, and population cycles. Individual stochasticity is a theme throughout, with a focus that goes beyond expected values to include variances in demographic outcomes. The calculations are easily and accurately implemented in matrix-oriented programming languages such as Matlab or R. Sensitivity analysis will help readers create models to predict the effect of future changes, to evaluate policy effects, and to identify possible evolutionary responses to the environment. Complete with many examples of the application, the book will be of interest to researchers and graduate students in human demography and population biology. The material will also appeal to those in mathematical biology and applied mathematics.
Author : Robert Barthorpe
Publisher : Springer
ISBN 13 : 3319548581
Total Pages : 368 pages
Book Rating : 4.3/5 (195 download)
Download or read book Model Validation and Uncertainty Quantification, Volume 3 written by Robert Barthorpe and published by Springer. This book was released on 2017-06-07 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: Model Validation and Uncertainty Quantification, Volume 3: Proceedings of the 35th IMAC, A Conference and Exposition on Structural Dynamics, 2017, the third volume of ten from the Conference brings together contributions to this important area of research and engineering. The collection presents early findings and case studies on fundamental and applied aspects of Model Validation and Uncertainty Quantification, including papers on: Uncertainty Quantification in Material Models Uncertainty Propagation in Structural Dynamics Practical Applications of MVUQ Advances in Model Validation & Uncertainty Quantification: Model Updating Model Validation & Uncertainty Quantification: Industrial Applications Controlling Uncertainty Uncertainty in Early Stage Design Modeling of Musical Instruments Overview of Model Validation and Uncertainty
Author : Lisa G. Stanley
Publisher : SIAM
ISBN 13 : 9780898717556
Total Pages : 160 pages
Book Rating : 4.7/5 (175 download)
Download or read book Design Sensitivity Analysis written by Lisa G. Stanley and published by SIAM. This book was released on 2002-01-01 with total page 160 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an understandable introduction to one approach to design sensitivity computation and illustrates some of the important mathematical and computational issues inherent in using the sensitivity equation method (SEM) for partial differential equations. The authors use basic models to illustrate the computational issues that one might encounter when applying the SEM in a laboratory or research setting, while providing an overview of applications and computational issues regarding sensitivity calculations performed by way of continuous sensitivity equation methods (CSEM).
Author : Dan G. Cacuci
Publisher : CRC Press
ISBN 13 : 020348357X
Total Pages : 367 pages
Book Rating : 4.2/5 (34 download)
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.
Author : Andrea Saltelli
Publisher : Wiley
ISBN 13 : 9780470743829
Total Pages : 0 pages
Book Rating : 4.7/5 (438 download)
Download or read book Sensitivity Analysis written by Andrea Saltelli and published by Wiley. This book was released on 2009-03-16 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Wiley Paperback Series makes valuable content more accessible to a new generation of statisticians, mathematicians and scientists. Sensitivity analysis is used to ascertain how a given model output depends upon the input parameters. This is an important method for checking the quality of a given model, as well as a powerful tool for checking the robustness and reliability of its analysis. The topic is acknowledged as essential for good modelling practice and is an implicit part of any modelling field. Offers an accessible introduction to sensitivity analysis. Covers all the latest research. Illustrates concepts with numerous examples, applications and case studies. Includes contributions from the leading researchers active in developing strategies for sensitivity analysis. The principles of sensitivity analysis are carefully described and suitable methods for approaching many types of problems are given. The book introduces the modeller to the entire casual assessment chain, from data to predictions, whilst explaining the impact of source uncertainties and framing assumptions. A ‘hitch-hikers guide’ is included to allow the more experienced reader to readily access specific applications. Modellers from a wide range of disciplines, including biostatistics, economics, environmental impact assessment, chemistry and engineering will benefit greatly from the numerous examples and applications. "Presents many different sensitivity analysis methodologies and demonstrates their usefulness in scientific research." (Zentralblatt MATH)
Author : National Academies of Sciences, Engineering, and Medicine
Publisher : National Academies Press
ISBN 13 : 0309491843
Total Pages : 213 pages
Book Rating : 4.3/5 (94 download)
Download or read book A Decision Framework for Interventions to Increase the Persistence and Resilience of Coral Reefs written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2019-09-29 with total page 213 pages. Available in PDF, EPUB and Kindle. Book excerpt: Coral reefs are critical to ocean and human life because they provide food, living area, storm protection, tourism income, and more. However, human-induced stressors, such as overfishing, sediment, pollution, and habitat destruction have threatened ocean ecosystems globally for decades. In the face of climate change, these ecosystems now face an array of unfamiliar challenges due to destructive rises in ocean temperature, acidity and sea level. These factors lead to an increased frequency of bleaching events, hindered growth, and a decreasing rate of calcification. Research on interventions to combat these relatively new stressors and a reevaluation of longstanding interventions is necessary to understand and protect coral reefs in this changing climate. Previous research on these methods prompts further questions regarding the decision making process for site-specific interventions. A Decision Framework for Interventions to Increase the Persistence and Resilience of Coral Reefs builds upon a previous report that reviews the state of research on methods that have been used, tested, or proposed to increase the resilience of coral reefs. This new report aims to help coral managers evaluate the specific needs of their site and navigate the 23 different interventions described in the previous report. A case study of the Caribbean, a region with low coral population plagued by disease, serves as an example for coral intervention decision making. This report provides complex coral management decision making tools, identifies gaps in coral biology and conservation research, and provides examples to help individuals and communities tailor a decision strategy to a local area.
Download or read book Use of Forward Sensitivity Analysis Method to Improve Code Scaling, Applicability, and Uncertainty (CSAU) Methodology written by and published by . This book was released on 2010 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Code Scaling, Applicability, and Uncertainty (CSAU) methodology was developed in late 1980s by US NRC to systematically quantify reactor simulation uncertainty. Basing on CSAU methodology, Best Estimate Plus Uncertainty (BEPU) methods have been developed and widely used for new reactor designs and existing LWRs power uprate. In spite of these successes, several aspects of CSAU have been criticized for further improvement: i.e., (1) subjective judgement in PIRT process; (2) high cost due to heavily relying large experimental database, needing many experts man-years work, and very high computational overhead; (3) mixing numerical errors with other uncertainties; (4) grid dependence and same numerical grids for both scaled experiments and real plants applications; (5) user effects; Although large amount of efforts have been used to improve CSAU methodology, the above issues still exist. With the effort to develop next generation safety analysis codes, new opportunities appear to take advantage of new numerical methods, better physical models, and modern uncertainty qualification methods. Forward sensitivity analysis (FSA) directly solves the PDEs for parameter sensitivities (defined as the differential of physical solution with respective to any constant parameter). When the parameter sensitivities are available in a new advanced system analysis code, CSAU could be significantly improved: (1) Quantifying numerical errors: New codes which are totally implicit and with higher order accuracy can run much faster with numerical errors quantified by FSA. (2) Quantitative PIRT (Q-PIRT) to reduce subjective judgement and improving efficiency: treat numerical errors as special sensitivities against other physical uncertainties; only parameters having large uncertainty effects on design criterions are considered. (3) Greatly reducing computational costs for uncertainty qualification by (a) choosing optimized time steps and spatial sizes; (b) using gradient information (sensitivity result) to reduce sampling number. (4) Allowing grid independence for scaled integral effect test (IET) simulation and real plant applications: (a) eliminate numerical uncertainty on scaling; (b) reduce experimental cost by allowing smaller scaled IET; (c) eliminate user effects. This paper will review the issues related to the current CSAU, introduce FSA, discuss a potential Q-PIRT process, and show simple examples to perform FSA. Finally, the general research direction and requirements to use FSA in a system analysis code will be discussed.
