Intelligent Fatigue Statistics
eBook - ePub

Intelligent Fatigue Statistics

  1. 258 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Intelligent Fatigue Statistics

About this book

This book introduces the principles and theories of fatigue statistics and presents the Zhentong Gao method along with its practical applications.

Fatigue in metal components is a complex phenomenon and an important issue because the fatigue life of key components often determines the overall lifespan of the aircraft. The book provides an overview and analysis of existing fatigue life calculation and estimation methods, including probability statistical methods such as using Gaussian distribution, logarithmic Gaussian distribution, and Weibull distribution to fit actual data. However, the authors argue that these methods have limitations in terms of reliability and applicability. They point out that the location parameter of the Weibull distribution represents a safe life with 100% reliability. Based on these methods, the book proposes the intelligent Zhentong Gao method, which differs from traditional approaches and effectively addresses and solves the problem of estimating the three parameters of Weibull distribution.

This title will serve as a valuable reference for researchers, senior undergraduate and graduate students, and engineers in the fields of aerospace, automotive, mechanical, civil engineering, etc.

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Yes, you can access Intelligent Fatigue Statistics by Zhentong Gao,Jiajin Xu in PDF and/or ePUB format, as well as other popular books in Technology & Engineering & Engineering General. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover
  2. Half Title
  3. Title Page
  4. Copyright Page
  5. Table of Contents
  6. Abbreviations
  7. Symbols
  8. Foreword to the Chinese Edition
  9. Preface
  10. Part I Mathematical Foundations of Intelligent Fatigue Statistics
  11. Part II Computer Basics of Intelligent Statistical Fatigue
  12. Part III Some Applications of Intelligent Fatigue Statistics
  13. Epilogue: Perspectives on Intelligent Fatigue Statistics
  14. Postscript
  15. Appendix A: Python Code for Calculating Confidence Interval Curve of Weibull Distribution
  16. Appendix B: Python Code of Digital Experiment of Weibull Distribution Parameters
  17. Appendix C: Python Code for Evaluating Weibull Distribution Parameters and Confidence Intervals by the Bootstrap
  18. Index