Author: Zhangli Hu Publisher: ISBN: Category : Languages : en Pages : 152
Book Description
"Engineers always encounter time-dependent uncertainties that ubiquitously exist, such as the random deterioration of material properties and time-variant loads. Therefore the reliability of engineering systems becomes time-dependent. It is crucial to predict the time-dependent reliability in the design stage, given possible catastrophic consequences of a failure. Although extensive research has been conducted on reliability analysis, estimating the reliability accurately and efficiently is still challenging. The objective of this work is to develop accurate and efficient reliability methodologies for engineering design. The basic idea is the integration of traditional reliability methods with saddlepoint approximation (SPA), which can accurately approximate the tail distribution of a random variable. Four methods are proposed in this work. The first three methods deal with time-independent reliability while the last one estimates the time-dependent reliability. The first method combines SPA with first-order approximation and achieves higher accuracy over the traditional first-order reliability method when bimodal distributions are involved. The second method further improves the accuracy of reliability estimation by integrating SPA with the second-order approximation. The third method extends the second method into the reliability-based design for higher accuracy, and the high efficiency is maintained by an efficient algorithm for searching for an equivalent reliability index. The fourth method uses sequential efficient global optimization to convert a time-dependent problem into a time-independent counterpart. Then the second method is utilized to estimate the time-independent reliability after the conversion. The accuracy and effectiveness of the above methods are demonstrated by both numerical examples and engineering applications"--Abstract, page iv.
Author: Chun-Qing Li Publisher: Elsevier ISBN: 0323860168 Category : Technology & Engineering Languages : en Pages : 626
Book Description
Time-Dependent Reliability Theory and Its Applications introduces the theory of time-dependent reliability and presents methods to determine the reliability of structures over the lifespan of their services. The book contains state-of-the-art solutions to first passage probability derived from the theory of stochastic processes with different types of probability distribution functions, including Gaussian and non-Gaussian distributions and stationary and non-stationary processes. In addition, it provides various methods to determine the probability of failure over time, considering different failure modes and a methodology to predict the service life of structures. Sections also cover the applications of time-dependent reliability to prediction of service life and development of risk cost-optimized maintenance strategy for existing structures. This new book is for those who wants to know how to predict the service life of a structure (buildings, bridges, aircraft structures, etc.) and how to develop a risk-cost, optimized maintenance strategy for these structures. Presents the basic knowledge required to predict service life and develop a maintenance strategy for infrastructure Explains how to predict the remaining safe life of the infrastructure during its lifespan of operation Describes how to carry out maintenance for an infrastructure to ensure its safe and serviceable operation during the designed service life
Author: Yu Liu Publisher: Springer Nature ISBN: 3031288599 Category : Technology & Engineering Languages : en Pages : 642
Book Description
This comprehensive book brings together the latest developments in reliability and maintainability methods from leading research groups globally. Covering a diverse range of subject areas, from mechanical systems to cyber-physical systems, the book offers both theoretical advancements and practical applications in various industries. With a focus on reliability modelling, reliability analysis, reliability design, maintenance optimization, warranty policy, prognostics and health management, this book appeals to academic and industrial professionals in the field of reliability engineering and beyond. It features real-world case studies from turbofan engines bearings, industrial robots, wireless networks, aircraft actuation systems, and more. This book is ideal for engineers, scientists, and graduate students in reliability, maintainability, design optimization, prognostics and health management, and applied probability and statistics.
Author: Zhifu Zhu Publisher: ISBN: Category : Reliability (Engineering) Languages : en Pages : 158
Book Description
"Engineering systems are usually subjected to time-variant loads and operate under time-dependent uncertainty; system performances are therefore time-dependent. Accurate and efficient estimate of system reliability is crucial for decision makings on system design, lifetime cost estimate, maintenance strategy, etc. Although significant progresses have been made in time-independent reliability analysis for components and systems, time-dependent system reliability methodologies are still limited. This dissertation is motivated by the need of accurate and effective reliability prediction for engineering systems under time-dependent uncertainty. Based on the classic First and Second Order Reliability Method (FORM and SORM), a system reliability method is developed for multidisciplinary systems involving stationary stochastic processes. A dependent Kriging method is also developed for general components. This method accounts for dependent responses from surrogate models and is therefore more accurate than existing Kriging Monte Carlo simulation methods that neglect the dependence between responses. The extension of the dependent Kriging method to systems is also a contribution of this dissertation. To overcome the difficulty of obtaining extreme value distributions and get rid of global optimization with a double-loop procedure, a Kriging surrogate modeling method is also proposed. This method provides a new perspective of surrogate modeling for time-dependent systems and is applicable to general systems having random variables, time, and stochastic processes. The proposed methods are evaluated through a wide range of engineering systems, including a compound cylinders system, a liquid hydrogen fuel tank, function generator mechanisms, slider-crank mechanisms, and a Daniels system"--Abstract, page iv.
Author: Ronald W. Butler Publisher: Cambridge University Press ISBN: 1139466518 Category : Mathematics Languages : en Pages : 548
Book Description
Modern statistical methods use complex, sophisticated models that can lead to intractable computations. Saddlepoint approximations can be the answer. Written from the user's point of view, this book explains in clear language how such approximate probability computations are made, taking readers from the very beginnings to current applications. The core material is presented in chapters 1-6 at an elementary mathematical level. Chapters 7-9 then give a highly readable account of higher-order asymptotic inference. Later chapters address areas where saddlepoint methods have had substantial impact: multivariate testing, stochastic systems and applied probability, bootstrap implementation in the transform domain, and Bayesian computation and inference. No previous background in the area is required. Data examples from real applications demonstrate the practical value of the methods. Ideal for graduate students and researchers in statistics, biostatistics, electrical engineering, econometrics, and applied mathematics, this is both an entry-level text and a valuable reference.
Author: Publisher: ISBN: Category : Failure analysis (Engineering) Languages : en Pages : 392
Book Description
Time-dependent reliability has recently become an important area of research in order to design products which perform their desired function dependably for their entire lifecycle. Without considering the degradation of reliability over time, many unexpected costs and failures may occur, incurring costly repairs, warranty costs and loss of market share, In this research, we introduce two new time-dependent reliability methods for dynamic as well as linear vibratory systems with random parameters and input random processes. The first method we introduced uses the concept of composite limit state to solve time-dependent (dynamic or vibratory) problems with limit-state functions of input random variables and input random processes. The input random processes are assumed Gaussian and are expressed in terms of standard normal variables using a spectral decomposition method. The total probability theorem is employed to calculate the time-dependent probability of failure using time-dependent conditional probabilities which are computed accurately and efficiently in the standard normal space using First Order Reliability Methods (FORM). The second methodology calculates the failure rate of a linear vibratory system with random parameters excited by stationary or non-stationary Gaussian processes. The response of such a system is non-stationary because of the randomness of the input parameters. A space-filling design is first used to sample the input parameter space. For each design point, the corresponding conditional time-dependent probability of failure is calculated efficiently using random vibrations principles and an efficient numerical estimation of the up-crossing and joint up-crossing rates. A time-dependent metamodel is then created which allows us to estimate the conditional probabilities for any set of input parameters. The total probability theorem is finally applied to calculate the time-dependent probability of failure. Principles from the developed time-dependent reliability methods are also applied to estimate fatigue reliability. all new methodologies are demonstrated using a hydrokinetic turbine blade design problem and vibratory beam examples. The fatigue reliability research has been demonstrated and validated using an experimental set-up in TARDEC's Physical Simulation Lab. All methodologies can be extended to systems with millions of degrees of freedom using a procedure described in the Future Work section.
Author: Alan Genz Publisher: Springer Science & Business Media ISBN: 3642016898 Category : Computers Languages : en Pages : 130
Book Description
Multivariate normal and t probabilities are needed for statistical inference in many applications. Modern statistical computation packages provide functions for the computation of these probabilities for problems with one or two variables. This book describes recently developed methods for accurate and efficient computation of the required probability values for problems with two or more variables. The book discusses methods for specialized problems as well as methods for general problems. The book includes examples that illustrate the probability computations for a variety of applications.
Author: A.M. Mathai Publisher: CRC Press ISBN: 9780824786915 Category : Mathematics Languages : en Pages : 424
Book Description
Textbook for a one-semester graduate course for students specializing in mathematical statistics or in multivariate analysis, or reference for theoretical as well as applied statisticians, confines its discussion to quadratic forms and second degree polynomials in real normal random vectors and matr
Author: Erik Vanmarcke Publisher: World Scientific ISBN: 9812563539 Category : Mathematics Languages : en Pages : 363
Book Description
Random variation is a fact of life that provides substance to a wide range of problems in the sciences, engineering, and economics. There is a growing need in diverse disciplines to model complex patterns of variation and interdependence using random fields, as both deterministic treatment and conventional statistics are often insufficient. An ideal random field model will capture key features of complex random phenomena in terms of a minimum number of physically meaningful and experimentally accessible parameters. This volume, a revised and expanded edition of an acclaimed book first published by the M I T Press, offers a synthesis of methods to describe and analyze and, where appropriate, predict and control random fields. There is much new material, covering both theory and applications, notably on a class of probability distributions derived from quantum mechanics, relevant to stochastic modeling in fields such as cosmology, biology and system reliability, and on discrete-unit or agent-based random processes.Random Fields is self-contained and unified in presentation. The first edition was found, in a review in EOS (American Geophysical Union) to be ?both technically interesting and a pleasure to read ? the presentation is clear and the book should be useful to almost anyone who uses random processes to solve problems in engineering or science ? and (there is) continued emphasis on describing the mathematics in physical terms.?
Author: Zhangli Hu
Author: Chun-Qing Li
Author: Yu Liu
Author: Zhifu Zhu
Author: Ronald W. Butler
Author: 
Author: Jianrong Tan
Author: Alan Genz
Author: A.M. Mathai
Author: Erik Vanmarcke