Efficient Methods for the Reliability Analysis of Dynamic Systems
Author | : Bin Wu |
Publisher | : |
Total Pages | : |
Release | : 2007 |
Genre | : |
ISBN | : |
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Author | : Bin Wu |
Publisher | : |
Total Pages | : |
Release | : 2007 |
Genre | : |
ISBN | : |
Author | : Bin Wu |
Publisher | : Academic Press |
Total Pages | : 225 |
Release | : 2013-06-19 |
Genre | : Technology & Engineering |
ISBN | : 0124077390 |
Featuring aerospace examples and applications, Reliability Analysis of Dynamic Systems presents the very latest probabilistic techniques for accurate and efficient dynamic system reliability analysis. While other books cover more broadly the reliability techniques and challenges related to large systems, Dr Bin Wu presents a focused discussion of new methods particularly relevant to the reliability analysis of large aerospace systems under harmonic loads in the low frequency range. Developed and written to help you respond to challenges such as non-linearity of the failure surface, intensive computational costs and complexity in your dynamic system, Reliability Analysis of Dynamic Systems is a specific, detailed and application-focused reference for engineers, researchers and graduate students looking for the latest modeling solutions. The Shanghai Jiao Tong University Press Aerospace Series publishes titles that cover the latest advances in research and development in aerospace. Its scope includes theoretical studies, design methods, and real-world implementations and applications. The readership for the series is broad, reflecting the wide range of aerospace interest and application, but focuses on engineering. Forthcoming titles in the Shanghai Jiao Tong University Press Aerospace Series: Reliability Analysis of Dynamic Systems • Wake Vortex Control • Aeroacoustics: Fundamentals and Applications in Aeropropulsion Systems • Computational Intelligence in Aerospace Design • Unsteady Flow and Aeroelasticity in Turbomachinery Authored by a leading figure in Chinese aerospace with 20 years’ professional experience in reliability analysis and engineering simulation. Offers solutions to the challenges of non-linearity, intensive computational cost and complexity in reliability assessment. Aerospace applications and examples used throughout to illustrate accuracy and efficiency achieved with new methods.
Author | : Mahdi Norouzi |
Publisher | : |
Total Pages | : 218 |
Release | : 2012 |
Genre | : Engineering systems |
ISBN | : |
The objective of this research is to develop an efficient method to study the reliability of dynamic large complex engineering systems. In design of real-life dynamic systems, there are significant uncertainties in modeling the input. For instance, for an offshore wind turbine, there are considerable uncertainties in the power spectral density functions of the wave elevations or the wind speeds. Therefore, it is necessary to evaluate the reliability of a system for different power spectral density functions of the input loads. The reliability analysis of dynamic systems requires performing Monte Carlo simulations in time domain with thousands of replications. The computational cost of such analyses is prohibitive for most real-life complex systems. In this study, a new method is proposed to reduce the computational cost of the reliability study of dynamic systems. This method is applicable to the dynamic systems in which the loads are represented using power spectral density functions. This goal is achieved by estimating the reliability for several power spectral densities of a load by re-weighting the results of a single Monte Carlo simulation for one power spectral density function of the load. The proposed approach is based on Probabilistic Re-analysis method that is similar to the idea of Importance Sampling. That is the main variance reduction technique, which is used to lower the computational cost of Monte Carlo simulation. The proposed method extends the application of the Probabilistic Re-Analysis, which has already been applied to static problems, to dynamic problems. Static problems are modeled using random variables that are invariant with time whereas in dynamic systems both the excitation and the response are stochastic processes varying with time. Utilizing Shinozuka's method is the key idea because it enables representing a time varying random process in terms of random variables. This new approach can significantly lower the cost of the sensitivity reliability analysis of dynamic systems. This study also presents a new approach to apply Subset Simulation efficiently to dynamic problems. Subset Simulation is more efficient than Monte Carlo simulation in estimating the probability of first excursion failure of highly reliable systems. This method is based on the idea that a small failure probability can be calculated as a product of larger conditional probabilities of intermediate events. The method is more efficient because it is much faster to calculate several large probabilities than a single low probability. However, Subset Simulation is often impractical for random vibration problems because it requires considering numerous random variables that makes it very difficult to explore the space of the random variables due to its large dimension. A new approach is proposed in this research to perform Subset Simulation that utilizes Shinozuka's equation to calculate the time series of the loads from a power spectral density function. The commutative property of Shinozuka's equation enables taking advantage of its symmetry, thereby reducing the dimension of the space of the random variables in dynamic problems. Therefore, performing Subset Simulation using the new approach is more efficient than the original Subset Simulation. In addition, Shinozuka's equation assists in integrating Subset Simulation with Probabilistic Re-analysis. This new method, which is called Subset-PRRA, is more efficient than regular Probabilistic Re-analysis as the latter is based on Monte Carlo simulation, whereas Subset-PRRA reuses the results of Subset Simulation. For an offshore wind turbine, the wind and waves are represented by power spectral density functions; Subset-PRRA seems to be a promising tool to cut the computational cost of the sensitivity analysis of first excursion reliability of an offshore wind turbine. The application of the Probabilistic Re-analysis in reliability analysis of an offshore wind turbine is demonstrated in this research through two examples in which only changes in the power spectral density function of the wave elevation are considered. The method is also applicable to the case that the wind spectrum changes, but requires calculation of wind field time histories using Shinozuka's method. Finally, a probabilistic approach for the structural design of an offshore wind turbine under the Lake Erie environment is presented. To perform probabilistic design, the dependence between wind, wave and period should be modeled accurately. Modeling the dependence between wind and wave is expensive, as it requires a large amount of data. Many researchers, similar to the approach presented in the International Electrotechnical Commission standards, assume that wave height follows standard distributions conditional on wind speed. In this work, an alternative approach is used that is based on the application of copulas. This approach is more complete because the joint distribution is obtained without making any assumption on the conditional distributions. Using the joint distribution, a methodology to find the required load capacity of the structure to meet the target reliability based on Monte Carlo simulation and Tail-fitting method is presented.
Author | : Badal Thapa |
Publisher | : |
Total Pages | : 0 |
Release | : 2020 |
Genre | : Monte Carlo method |
ISBN | : |
For many problems, especially nonlinear systems, the reliability assessment must be done in the time domain. Monte-Carlo simulation (MCS) can accurately assess the reliability of the system. However, its computational cost is highly expensive for the complex dynamic system. Importance Sampling (IS) method is a more efficient method than standard MCS for the reliability assessment of a system. It has been applied to dynamic systems when the excitation is defined by a Power Spectral Density (PSD) function. The central idea of the IS method is about generating sample time histories using a sampling PSD and introducing the likelihood ratio to each replication to give the unbiased estimator of the probability of failure. Another more efficient method than MCS for the reliability assessment of the dynamic system is the Separable Monte-Carlo (SMC) method. However, this method has been applied to linear dynamic systems as following. It starts with the step of drawing frequencies from PSD of excitation, calculation of system responses to each frequency, and storing them in a database. Then the stored frequencies and the respective responses are chosen randomly with the replacement for each replication to find the system response to the linear combination of the respective sinusoidal functions. Therefore, SMC can assess the reliability of the system with a proper database. The size of the database would depend on the shape of the PSD function and the complexity of the system. This research proposed a new method by combining IS with SMC to assess the reliability of linear dynamic systems. In this method, the database of the proposed method formed by using a sampling PSD is used to estimate the reliability of the system for the true spectrum The proposed method is more efficient than both IS or SMC methods individually in terms of both computational time and accuracy. The proposed method is demonstrated using a 10-bar truss.
Author | : Liudong Xing |
Publisher | : John Wiley & Sons |
Total Pages | : 336 |
Release | : 2019-01-08 |
Genre | : Technology & Engineering |
ISBN | : 1119507685 |
Offers timely and comprehensive coverage of dynamic system reliability theory This book focuses on hot issues of dynamic system reliability, systematically introducing the reliability modeling and analysis methods for systems with imperfect fault coverage, systems with function dependence, systems subject to deterministic or probabilistic common-cause failures, systems subject to deterministic or probabilistic competing failures, and dynamic standby sparing systems. It presents recent developments of such extensions involving reliability modelling theory, reliability evaluation methods, and features numerous case studies based on real-world examples. The presented dynamic reliability theory can enable a more accurate representation of actual complex system behavior, thus more effectively guiding the reliable design of real-world critical systems. Dynamic System Reliability: Modelling and Analysis of Dynamic and Dependent Behaviors begins by describing the evolution from the traditional static reliability theory to the dynamic system reliability theory, and provides a detailed investigation of dynamic and dependent behaviors in subsequent chapters. Although written for those with a background in basic probability theory and stochastic processes, the book includes a chapter reviewing the fundamentals that readers need to know in order to understand contents of other chapters which cover advanced topics in reliability theory and case studies. The first book systematically focusing on dynamic system reliability modelling and analysis theory Provides a comprehensive treatment on imperfect fault coverage (single-level/multi-level or modular), function dependence, common cause failures (deterministic and probabilistic), competing failures (deterministic and probabilistic), and dynamic standby sparing Includes abundant illustrative examples and case studies based on real-world systems Covers recent advances in combinatorial models and algorithms for dynamic system reliability analysis Offers a rich set of references, providing helpful resources for readers to pursue further research and study of the topics Dynamic System Reliability: Modelling and Analysis of Dynamic and Dependent Behaviors is an excellent book for undergraduate and graduate students, and engineers and researchers in reliability and related disciplines.
Author | : Achintya Haldar |
Publisher | : John Wiley & Sons |
Total Pages | : 308 |
Release | : 2023-04-18 |
Genre | : Technology & Engineering |
ISBN | : 1119901642 |
RELIABILITY EVALUATION OF DYNAMIC SYSTEMS EXCITED IN TIME DOMAIN – REDSET Multi-disciplinary approach to structural reliability analysis for dynamic loadings offering a practical alternative to the random vibration theory and simulation Reliability Evaluation of Dynamic Systems Excited in Time Domain – REDSET is a multidisciplinary concept that enables readers to estimate the underlying risk that could not be solved in the past. The major hurdle was that the required limit state functions (LSFs) are implicit in nature and the lack of progress in the reliability evaluation methods for this class of problems. The most sophisticated deterministic analysis requires that the dynamic loadings must be applied in the time domain. To satisfy these requirements, REDSET is developed. Different types and forms of dynamic loadings including seismic, wind-induced wave, and thermomechanical loading in the form of heating and cooling of solder balls used in computer chips are considered to validate REDSET. Time domain representations and the uncertainty quantification procedures including the use of multiple time histories are proposed and demonstrated for all these dynamic loadings. Both onshore and offshore structures are used for validation. The potential of REDSET is demonstrated for implementing the Performance Based Seismic Design (PBSD) concept now under development in the United States. For wider multidisciplinary applications, structures are represented by finite elements to capture different types of nonlinearity more appropriately. Any computer program capable of conducting nonlinear time domain dynamic analysis can be used, and the underlying risk can be estimated with the help of several dozens or hundreds of deterministic finite element analyses, providing an alternative to the simulation approach. To aid comprehension of REDSET, numerous illustrative examples and solution strategies are presented in each chapter. Written by award-winning thought leaders from academia and professional practice, the following sample topics are included: Fundamentals of reliability assessment including set theory, modeling of uncertainty, the risk-based engineering design concept, and the evolution of reliability assessment methods Implicit performance or limit state functions are expressed explicitly by the extensively modified response surface method with several new experimental designs Uncertainty quantification procedures with multiple time histories for different dynamic loadings, illustrated with examples The underlying risk can be estimated using any computer program representing structures by finite elements with only few deterministic analyses REDSET is demonstrated to be an alternative to the classical random vibration concept and the basic simulation procedure for risk estimation purposes REDSET changes the current engineering design paradigm. Instead of conducting one deterministic analysis, a design can be made more dynamic load tolerant, resilient, and sustainable with the help of a few additional deterministic analyses This book describing REDSET is expected to complement two other books published by Wiley and authored by Haldar and Mahadevan: Probability, Reliability and Statistical Methods in Engineering Design and Reliability Assessment Using Stochastic Finite Element Analysis. The book is perfect to use as a supplementary resource for upper-level undergraduate and graduate level courses on reliability and risk-based design.
Author | : Anatoly Lisnianski |
Publisher | : Springer Nature |
Total Pages | : 195 |
Release | : 2020-08-24 |
Genre | : Technology & Engineering |
ISBN | : 3030524884 |
This book discusses recent developments in dynamic reliability in multi-state systems (MSS), addressing such important issues as reliability and availability analysis of aging MSS, the impact of initial conditions on MSS reliability and availability, changing importance of components over time in MSS with aging components, and the determination of age-replacement policies. It also describes modifications of traditional methods, such as Markov processes with rewards, as well as a modern mathematical method based on the extended universal generating function technique, the Lz-transform, presenting various successful applications and demonstrating their use in real-world problems. This book provides theoretical insights, information on practical applications, and real-world case studies that are of interest to engineers and industrial managers as well as researchers. It also serves as a textbook or supporting text for graduate and postgraduate courses in industrial, electrical, and mechanical engineering.
Author | : Seifedine Kadry |
Publisher | : Springer |
Total Pages | : 807 |
Release | : 2014-09-30 |
Genre | : Science |
ISBN | : 331907167X |
This book offers unique insight on structural safety and reliability by combining computational methods that address multiphysics problems, involving multiple equations describing different physical phenomena and multiscale problems, involving discrete sub-problems that together describe important aspects of a system at multiple scales. The book examines a range of engineering domains and problems using dynamic analysis, nonlinear methods, error estimation, finite element analysis and other computational techniques. This book also: · Introduces novel numerical methods · Illustrates new practical applications · Examines recent engineering applications · Presents up-to-date theoretical results · Offers perspective relevant to a wide audience, including teaching faculty/graduate students, researchers and practicing engineers.
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 | : Zequn Wang |
Publisher | : |
Total Pages | : 132 |
Release | : 2014 |
Genre | : Electronic dissertations |
ISBN | : |
Ensuring a high level of system reliability throughout a product life-cycle is one of paramount tasks for engineering design, which requires new reliability analysis and design techniques to effectively address the challenges of system design under time-variant probabilistic constraints, such as those induced by time-dependent loading condition and system component deterioration. Extensive reviews on existing literature on reliability analysis and reliability based design optimization for complex engineered systems have identified important challenge problems to be addressed in this research, which have been organized into three research thrusts as follows: -Reliability Analysis using Surrogate Models: In this research thrust, the objective is to develop a robust approach to approximate static reliability efficiently and accurately based on surrogate models. Two challenge problems will be addressed: (1) How to evaluate fidelity of surrogate models and accuracy of reliability approximation based on those models, and (2) How to efficiently update a surrogate model if it does not meet the accuracy requirement. -Reliability Analysis with Time-variant Probabilistic Constraints. In this research thrust, the objective is to develop an efficient approach for dynamic reliability analysis considering time-variant probabilistic constraints. There are two challenges to be addressed: (1) How to handle the time-dependency of system failure events in dynamic reliability analysis, and (2) How to improve the efficiency of dynamic reliability analysis. -Reliability Analysis with Multiple System Failure Modes. The objective of this thrust is to develop a novel system reliability analysis framework to address a grand challenge in design that multiple system failure modes must be addressed concurrently to ensure a high level of system reliability.