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Author: C. Annis Publisher: ISBN: Category : Conditional Languages : en Pages : 12
Book Description
Many engineers effect "probabilistic life prediction" by replacing constants with probability distributions and carefully modeling the physical relationships among the parameters. Surprisingly, the statistical relationships among the "constants" are often given short shrift, if not ignored altogether. Few recognize that while this simple substitution of distributions for constants will indeed produce a nondeterministic result, the corresponding "probabilities" are often woefully inaccurate. In fact, even the "trend" can be wrong, so these results can't even be used for sensitivity studies. This paper explores the familiar Paris equation relating crack growth rate and applied stress intensity to illustrate many statistical realities that are often ignored by otherwise careful engineers. Although the examples are Monte Carlo, the lessons also apply to other methods of probabilistic life prediction, including FORM/SORM (First/Second Order Reliability Method) and related "fast probability integration" methods.
Author: C. Annis Publisher: ISBN: Category : Conditional Languages : en Pages : 12
Book Description
Many engineers effect "probabilistic life prediction" by replacing constants with probability distributions and carefully modeling the physical relationships among the parameters. Surprisingly, the statistical relationships among the "constants" are often given short shrift, if not ignored altogether. Few recognize that while this simple substitution of distributions for constants will indeed produce a nondeterministic result, the corresponding "probabilities" are often woefully inaccurate. In fact, even the "trend" can be wrong, so these results can't even be used for sensitivity studies. This paper explores the familiar Paris equation relating crack growth rate and applied stress intensity to illustrate many statistical realities that are often ignored by otherwise careful engineers. Although the examples are Monte Carlo, the lessons also apply to other methods of probabilistic life prediction, including FORM/SORM (First/Second Order Reliability Method) and related "fast probability integration" methods.
Author: W. Steven Johnson Publisher: ASTM International ISBN: 9780803134782 Category : Technology & Engineering Languages : en Pages : 292
Book Description
As fatigue and fracture mechanics approaches are used more often for determining the useful life and/or inspection intervals for complex structures, realization sets-in that all factors are not well known or characterized. Indeed, inherent scatter exists in initial material quality and in material performance. Furthermore, projections of component usage in determination of applied stresses are inexact at best and are subject to much discrepancy between projected and actual usage. Even the models for predicting life contain inherent sources of error based on assumptions and/or empirically fitted parameters. All of these factors need to be accounted for to determine a distribution of potential lives based on combination of the aforementioned variables, as well as other factors. The purpose of this symposium was to create a forum for assessment of the state-of-the-art in incorporating these uncertainties and inherent scatter into systematic probabilistic methods for conducting life assessment.
Author: Lawrence N. Dworsky Publisher: John Wiley & Sons ISBN: 1119518105 Category : Mathematics Languages : en Pages : 352
Book Description
A revised edition that explores random numbers, probability, and statistical inference at an introductory mathematical level Written in an engaging and entertaining manner, the revised and updated second edition of Probably Not continues to offer an informative guide to probability and prediction. The expanded second edition contains problem and solution sets. In addition, the book’s illustrative examples reveal how we are living in a statistical world, what we can expect, what we really know based upon the information at hand and explains when we only think we know something. The author introduces the principles of probability and explains probability distribution functions. The book covers combined and conditional probabilities and contains a new section on Bayes Theorem and Bayesian Statistics, which features some simple examples including the Presecutor’s Paradox, and Bayesian vs. Frequentist thinking about statistics. New to this edition is a chapter on Benford’s Law that explores measuring the compliance and financial fraud detection using Benford’s Law. This book: Contains relevant mathematics and examples that demonstrate how to use the concepts presented Features a new chapter on Benford’s Law that explains why we find Benford’s law upheld in so many, but not all, natural situations Presents updated Life insurance tables Contains updates on the Gantt Chart example that further develops the discussion of random events Offers a companion site featuring solutions to the problem sets within the book Written for mathematics and statistics students and professionals, the updated edition of Probably Not: Future Prediction Using Probability and Statistical Inference, Second Edition combines the mathematics of probability with real-world examples. LAWRENCE N. DWORSKY, PhD, is a retired Vice President of the Technical Staff and Director of Motorola’s Components Research Laboratory in Schaumburg, Illinois, USA. He is the author of Introduction to Numerical Electrostatics Using MATLAB from Wiley.
Author: Fu-Kuo Chang Publisher: DEStech Publications, Inc ISBN: 160595053X Category : Technology & Engineering Languages : en Pages : 1397
Book Description
This 2-volume set of books, comprising over 2,700 total pages, presents 325 fully original presentations on recent advances in structural health monitoring, as applied to commercial and military aircraft (manned and unmanned), high-rise buildings, wind turbines, civil infrastructure, power plants and ships. One general theme of the books is how SHM can be used for condition-based maintenance, with the goal of developing prediction-based systems, designed to save money over the life of vehicles and structures. A second theme centers on technologies for developing systems comprising sensors, diagnostic data and decision-making, with a focus on intelligent materials able to respond to damage and in some cases repair it. Finally the books discuss the relation among data, data interpretation and decision-making in managing a wide variety of complex structures and vehicles. More recent technologies discussed in the books include SHM and environmental effects, energy harvesting, non-contact sensing, and intelligent networks.Material in these books was first presented in September, 2011 at a conference held at Stanford University and sponsored by the Air Force Office of Scientific Research, the Army Research Office, the Office of Naval Research and the National Science Foundation. Some of the highlights of the books include: SHM technologies for condition-based maintenance (CBM) and predictive maintenance Verification, validation, qualification, data mining, prognostics systems for decision-making Structural health, sensing and materials in closed-loop intelligent networks Military and aerospace, bioinspired sensors, wind turbines, monitoring with MEMS, damage sensing, hot spot monitoring, SHM and ships, high-rise structures Includes a fully-searchable CD-ROM displaying many figures and charts in full color
Author: Guy Pluvinage Publisher: Springer Science & Business Media ISBN: 9048127920 Category : Technology & Engineering Languages : en Pages : 419
Book Description
Structures that are essential for economy and security such as energy production, transportation and supply, water supply, buildings, are susceptible to failure, because of defects already present in the material, or created at fabrication, or appearing during service. Methods of assesment of the nocivity of these defects are needed, to predict the remaining service life and the eventual emergency of stopping service and repairing, if possible. To reach this objectives, this book presents the last methods derived from the classical linear, non-linear fracture mechanics concepts, including fatigue and notch fracture mechanics. Several examples of structures rehabilitations and repairing are given. This book gathers the presentation made during the Advanced Research Workshop held in Portoroz (Slovenia) in October 2008, under the auspices of NATO Science for Peace and Security Programme. It is edited by Professor Guy Pluvinage from the University Paul Verlaine – Metz (France) and Professor Aleksandar Sedmak from the University of Belgrade, Faculty of Mechanical Engineering. Both have a long and rich experience in analysis of theoretical and practical cases in safety and reliability of structures. Other contributors are all known as experts in the areas of fatigue, facture and reliability of structures.
Author: Gilles Barthe Publisher: Cambridge University Press ISBN: 110848851X Category : Computers Languages : en Pages : 583
Book Description
This book provides an overview of the theoretical underpinnings of modern probabilistic programming and presents applications in e.g., machine learning, security, and approximate computing. Comprehensive survey chapters make the material accessible to graduate students and non-experts. This title is also available as Open Access on Cambridge Core.
Author: Shane Parrish Publisher: Penguin ISBN: 0593719972 Category : Business & Economics Languages : en Pages : 209
Book Description
Discover the essential thinking tools you’ve been missing with The Great Mental Models series by Shane Parrish, New York Times bestselling author and the mind behind the acclaimed Farnam Street blog and “The Knowledge Project” podcast. This first book in the series is your guide to learning the crucial thinking tools nobody ever taught you. Time and time again, great thinkers such as Charlie Munger and Warren Buffett have credited their success to mental models–representations of how something works that can scale onto other fields. Mastering a small number of mental models enables you to rapidly grasp new information, identify patterns others miss, and avoid the common mistakes that hold people back. The Great Mental Models: Volume 1, General Thinking Concepts shows you how making a few tiny changes in the way you think can deliver big results. Drawing on examples from history, business, art, and science, this book details nine of the most versatile, all-purpose mental models you can use right away to improve your decision making and productivity. This book will teach you how to: Avoid blind spots when looking at problems. Find non-obvious solutions. Anticipate and achieve desired outcomes. Play to your strengths, avoid your weaknesses, … and more. The Great Mental Models series demystifies once elusive concepts and illuminates rich knowledge that traditional education overlooks. This series is the most comprehensive and accessible guide on using mental models to better understand our world, solve problems, and gain an advantage.
Author: C. Annis
Author: C. Annis
Author: W. Steven Johnson
Author: 
Author: Steven R. Daniewicz
Author: Lawrence N. Dworsky
Author: Fu-Kuo Chang
Author: Guy Pluvinage
Author: Gilles Barthe
Author: Shane Parrish
Author: Lawrence N. Dworsky