Sensitivity Analysis Of Dynamic Systems
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| Author | : Mansour Eslami |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 618 |
| Release | : 2013-11-09 |
| Genre | : Technology & Engineering |
| ISBN | : 366201632X |
This book provides a comprehensive treatment of the development and present state of the theory of sensitivity of dynamic systems. It is intended as a textbook and reference for researchers and scientists in electrical engineering, control and information theory as well as for mathematicians. The extensive and structured bibliography provides an overview of the literature in the field and points out directions for further research.
| Author | : Hector Jensen |
| Publisher | : Springer |
| Total Pages | : 231 |
| Release | : 2019-03-26 |
| Genre | : Science |
| ISBN | : 3030128199 |
This book combines a model reduction technique with an efficient parametrization scheme for the purpose of solving a class of complex and computationally expensive simulation-based problems involving finite element models. These problems, which have a wide range of important applications in several engineering fields, include reliability analysis, structural dynamic simulation, sensitivity analysis, reliability-based design optimization, Bayesian model validation, uncertainty quantification and propagation, etc. The solution of this type of problems requires a large number of dynamic re-analyses. To cope with this difficulty, a model reduction technique known as substructure coupling for dynamic analysis is considered. While the use of reduced order models alleviates part of the computational effort, their repetitive generation during the simulation processes can be computational expensive due to the substantial computational overhead that arises at the substructure level. In this regard, an efficient finite element model parametrization scheme is considered. When the division of the structural model is guided by such a parametrization scheme, the generation of a small number of reduced order models is sufficient to run the large number of dynamic re-analyses. Thus, a drastic reduction in computational effort is achieved without compromising the accuracy of the results. The capabilities of the developed procedures are demonstrated in a number of simulation-based problems involving uncertainty.
| Author | : Vadim Komkov |
| Publisher | : Academic Press |
| Total Pages | : 399 |
| Release | : 1986-05-01 |
| Genre | : Technology & Engineering |
| ISBN | : 0080960006 |
The book is organized into four chapters. The first three treat distinct types of design variables, and the fourth presents a built-up structure formulation that combines the other three. The first chapter treats finite-dimensional problems, in which the state variable is a finite-dimensional vector of structure displacements and the design parameters. The structual state equations are matrix equations for static response, vibration, and buckling of structures and matrix differential equations for transient dynamic response of structures, which design variables appearing in the coefficient matrices.
| Author | : Andrea Saltelli |
| Publisher | : John Wiley & Sons |
| Total Pages | : 232 |
| Release | : 2004-07-16 |
| Genre | : Mathematics |
| ISBN | : 047087094X |
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 | : Assem Deif |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 235 |
| Release | : 2012-12-06 |
| Genre | : Technology & Engineering |
| ISBN | : 364282739X |
A text surveying perturbation techniques and sensitivity analysis of linear systems is an ambitious undertaking, considering the lack of basic comprehensive texts on the subject. A wide-ranging and global coverage of the topic is as yet missing, despite the existence of numerous monographs dealing with specific topics but generally of use to only a narrow category of people. In fact, most works approach this subject from the numerical analysis point of view. Indeed, researchers in this field have been most concerned with this topic, although engineers and scholars in all fields may find it equally interesting. One can state, without great exaggeration, that a great deal of engineering work is devoted to testing systems' sensitivity to changes in design parameters. As a rule, high-sensitivity elements are those which should be designed with utmost care. On the other hand, as the mathematical modelling serving for the design process is usually idealized and often inaccurately formulated, some unforeseen alterations may cause the system to behave in a slightly different manner. Sensitivity analysis can help the engineer innovate ways to minimize such system discrepancy, since it starts from the assumption of such a discrepancy between the ideal and the actual system.
| Author | : Andrea Saltelli |
| Publisher | : John Wiley & Sons |
| Total Pages | : 304 |
| Release | : 2008-02-28 |
| Genre | : Mathematics |
| ISBN | : 9780470725177 |
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 | : Daniel Wallach |
| Publisher | : Academic Press |
| Total Pages | : 504 |
| Release | : 2013-11-25 |
| Genre | : Business & Economics |
| ISBN | : 0444594469 |
This second edition of Working with Dynamic Crop Models is meant for self-learning by researchers or for use in graduate level courses devoted to methods for working with dynamic models in crop, agricultural, and related sciences. Each chapter focuses on a particular topic and includes an introduction, a detailed explanation of the available methods, applications of the methods to one or two simple models that are followed throughout the book, real-life examples of the methods from literature, and finally a section detailing implementation of the methods using the R programming language. The consistent use of R makes this book immediately and directly applicable to scientists seeking to develop models quickly and effectively, and the selected examples ensure broad appeal to scientists in various disciplines. - 50% new content – 100% reviewed and updated - Clearly explains practical application of the methods presented, including R language examples - Presents real-life examples of core crop modeling methods, and ones that are translatable to dynamic system models in other fields
| Author | : John Sterman |
| Publisher | : McGraw-Hill Education |
| Total Pages | : 982 |
| Release | : 2000-02-23 |
| Genre | : Business & Economics |
| ISBN | : 9780072389159 |
Today’s leading authority on the subject of this text is the author, MIT Standish Professor of Management and Director of the System Dynamics Group, John D. Sterman. Sterman’s objective is to explain, in a true textbook format, what system dynamics is, and how it can be successfully applied to solve business and organizational problems. System dynamics is both a currently utilized approach to organizational problem solving at the professional level, and a field of study in business, engineering, and social and physical sciences.
| Author | : Hal Caswell |
| Publisher | : Springer |
| Total Pages | : 308 |
| Release | : 2019-04-02 |
| Genre | : Social Science |
| ISBN | : 3030105342 |
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 | : Reuven Y. Rubinstein |
| Publisher | : |
| Total Pages | : 360 |
| Release | : 1993-10-19 |
| Genre | : Mathematics |
| ISBN | : |
A unified and rigorous treatment of the associated stochastic optimization problems is provided and recent advances in perturbation theory encompassed. Throughout the book emphasis is upon concepts rather than mathematical completeness with the advantage that the reader only requires a basic knowledge of probability, statistics and optimization.
