Robust Reliability in the Mechanical Sciences de Yakov Ben-Haim

Robust Reliability in the Mechanical Sciences

Yakov Ben-Haim

en Limba Engleză Paperback – 15 sep 2011

The aim of the book is to develop methodology for reliablity analysis which is particularly suited to the types of partial information characteristic of mechanical systems and structures.
The book is designed as an upper-level undergraduate or first-year graduate text on robust reliability of mechanical systems. It will give the student or engineer a working knowledge of robust reliability which will enable him to analyse the reliability of mechanical systems. Each chapter is introduced with a brief conceptual survey of the main ideas, which are then developed through examples. Problems at the end of each chapter give the student the opportunity to strengthen and extend his or her understanding.

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Cuprins

1 Preview of Robust Reliability.- 1.1 Flexible Solar Panel.- 1.2 Quality Control of Thin Shells.- 1.3 Fatigue Failure and Reliability.- 1.4 Plastic Extrusion Manufacturing.- 1.5 Summary.- 2 Convexity and Uncertainty.- 2.1 Complex Uncertainty and Limited Information: Four Examples.- 2.2 Some Convex Models.- 2.3 Expansion of Convex Models.- 2.4 The Structure of Convex Sets.- 2.5 Clustering of Uncertain Events: The Convexity Theorem.- 2.6 Problems.- 3 Robust Reliability of Static Systems.- 3.1 Introduction.- 3.2 Beam With An Uncertain Distributed Load.- 3.3 Cooling Fin in an Uncertain Flow Field: Reliability and Design.- 3.4 Beam in Compression With Uncertain Initial Imperfections.- 3.5 Radial Buckling of Thin-Walled Shells; Reliability and Quality Control.- 3.6 Reliability of Serial and Parallel Networks.- 3.7 Problems.- 4 Robust Reliability of Time-Varying Systems.- 4.1 Mass and Spring System.- 4.2 Seismic Safety of Secondary Equipment.- 4.3 Multi-Dimensional Vibrating Structures.- 4.4 Modal Reliability.- 4.5 Axially Loaded Thin-Walled Shell With Imperfect Initial Shape.- 4.6 Fatigue Failure and Reliability With Uncertain Loading.- 4.7 Problems.- 5 Fault Diagnosis, System Identification and Reliability Testing.- 5.1 Benchmark Diagnostic Resolution: Simple Examples.- 5.2 Multi-Hypothesis Diagnosis of Anomalous Inputs.- 5.3 Least-Squares Estimation.- 5.4 Multi-Hypothesis Diagnosis of a Crack.- 5.5 Robust Reliability of Model-Order Determination.- 5.6 Ill-Posed Problems.- 5.7 Selective Sensitivity.- 5.8 Problems.- 6 Reliability of Mathematical Models.- 6.1 Models, Decisions and Reliability.- 6.2 Cooling Fin With Uncertain Geometry.- 6.3 Modal Truncation of a High-Dimensional Model.- 6.4 Robust Multi-Hypothesis System Identification.- 6.5 Problems.- 7 Convex and Probabilistic Models of Uncertainty.- 7.1 Uncertainty Is Not Necessarily Probabilistic: The Three-Box Riddle.- 7.2 Models of Uncertainty: A Comparison.- 7.3 Limitations of Probability.- 7.4 Sensitivity of the Failure Probability: An Example.- 7.5 Problems.- 8 Robust Reliability and the Poisson Process.- 8.1 The Poisson Distribution.- 8.2 Dynamic System with Uncertain Loads.- 8.3 Shells With Geometric Imperfections.- 8.4 Damage and Annealing Processes.- 8.5 Problems.- 9 Last But Not Final.- 9.1 Recapitulation of Robust Reliability.- 9.2 Subjective Calibration of Robust Reliability.- 9.3 Reliability and Social Acceptability.- 9.4 Robustness as a Managerial Strategy.- References.- Author Index.

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The book deals with analysis of reliability of mechanical systems, structures and devices. It addresses design for reliability, as well as quality assurance and quality control in mechanical manufacturing. This book is unique and non-classical, and reliability is defined non-probalistically as robustness to uncertainty. Convex-set models of uncertainty are described and used, rather than probabilistic models. This approach is particularly suited to the limited information typically available about uncertainties of complex mechanical systems. Static as well as dynamic systems, linear processes such as elastic vibration, and non-linear processes like damage evolution and fatigue failure are studied. Robust reliability is applied to evaluating the reliability of mathematical and convex models of uncertainty are combined in a hybrid reliability analysis applicable in those situations where prior information supports both types of uncertainty models. In short, a widely-applicable theory is developed through general discussion and many examples. Fachgebiet: Mechanical Engineering Zielgruppe: Research and Development