Georg Lindgren, Igor Rychlik, Sayan Gupta
Fatigue Prediction for Random Loads
Using the Rainflow Method
Georg Lindgren, Igor Rychlik, Sayan Gupta
Fatigue Prediction for Random Loads
Using the Rainflow Method
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Fatigue Prediction for Random Loads serves as a comprehensive treatise for methods for fatigue estimation and fatigue life prediction in randomly excited structural systems using the rainflow cycle counting method.
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Fatigue Prediction for Random Loads serves as a comprehensive treatise for methods for fatigue estimation and fatigue life prediction in randomly excited structural systems using the rainflow cycle counting method.
Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Produktdetails
- Produktdetails
- Verlag: Taylor & Francis Ltd
- Seitenzahl: 328
- Erscheinungstermin: 22. Mai 2025
- Englisch
- Abmessung: 234mm x 156mm
- ISBN-13: 9780367895846
- ISBN-10: 0367895846
- Artikelnr.: 72212076
- Herstellerkennzeichnung
- Libri GmbH
- Europaallee 1
- 36244 Bad Hersfeld
- gpsr@libri.de
- Verlag: Taylor & Francis Ltd
- Seitenzahl: 328
- Erscheinungstermin: 22. Mai 2025
- Englisch
- Abmessung: 234mm x 156mm
- ISBN-13: 9780367895846
- ISBN-10: 0367895846
- Artikelnr.: 72212076
- Herstellerkennzeichnung
- Libri GmbH
- Europaallee 1
- 36244 Bad Hersfeld
- gpsr@libri.de
Igor Rychlik is Professor emeritus at Chalmers University of Technology, Sweden. He obtained a PhD degree in Mathematical statistics fron Lund University, Sweden, 1986. During 1988-1990 he was Postdoc at Dept. of Statistics, Colorado State Uni- versity and in 1995 Visiting Prof. at Univ, of Queensland, Brisbane, Australia. He be- came professor in Mathematical Statistics in Lund 1999 and from 2007 at Chalmers University of Technology, Göteborg. There he also worked as scientific advisor to the Fraunhofer-Chalmers Centre for industrial mathematics. Since 2017 he is "emeritus professor". His main interest is in engineering applications of random processes and fields and in modelling of complex environmental loads, wind, sea waves, vehicle operating conditions. He is coauthor of Guide to Load Analysis for Durability in Ve- hicle Engineering and Probability and Risk Analysis: An Introduction for Engineers. Sayan Gupta is a Professor in Indian Institute of Technology Madras in the De- partment of Applied Mechanics. He graduated with a degree in civil engineering from Jadavpur University Kolkata in 1997, obtained his PhD from Indian Institute of Science Bangalore in 2005 and was a postdoc at the Technical University of Delft be- tween 2005-2007. He has held visiting positions at Waterloo, Lund and in Chalmers. Since 2007, he has been working at IIT Madras where he leads The Uncertainty Lab. He is the principal investigator for the Center for Complex Systems and Dynamics, IIT Madras and is the coordinator for the degree program on Complex Systems and Dynamics. His primary research interests are in nonlinear dynamics and stochastic mechanics. Georg Lindgren is Professor emeritus at the Engineering faculty of Lund Univer- sity, Sweden. He obtained a PhD degree in Mathematical statistics in Lund 1972 on a thesis inspired by an intriguing question regarding random load cycle ranges. After a period as Associate professor in Lund and in Umeå he became professor in Math- ematical statistics in Lund 1986, since 2006 "emeritus". His main interest is random processes and their use in communication technology, marine and mechanical engi- neering, and medicine. He is coauthor of a research volume on Extremes and related properties of random sequences and processes 1983, and two research/advanced stu- dent texts on stationary stochastic processes. He is member of the Royal Swedish Academy of Engineering Sciences (IVA).
Chapter 1 Fatigue damage
Chapter 2 Mathematical prerequisite
Chapter 3 Reliability estimation
Chapter 4 Cycle count and expected damage
Chapter 5 Sampled loads - Time series
Chapter 6 Gaussian loads, theory
Chapter 7 Gaussian loads, applications
Chapter 8 Markov loads
Chapter 9 Laplace moving average
Chapter 10 Non-linear load transformations
Chapter 11 Variance of damage estimate
Chapter 2 Mathematical prerequisite
Chapter 3 Reliability estimation
Chapter 4 Cycle count and expected damage
Chapter 5 Sampled loads - Time series
Chapter 6 Gaussian loads, theory
Chapter 7 Gaussian loads, applications
Chapter 8 Markov loads
Chapter 9 Laplace moving average
Chapter 10 Non-linear load transformations
Chapter 11 Variance of damage estimate
Chapter 1 Fatigue damage
Chapter 2 Mathematical prerequisite
Chapter 3 Reliability estimation
Chapter 4 Cycle count and expected damage
Chapter 5 Sampled loads - Time series
Chapter 6 Gaussian loads, theory
Chapter 7 Gaussian loads, applications
Chapter 8 Markov loads
Chapter 9 Laplace moving average
Chapter 10 Non-linear load transformations
Chapter 11 Variance of damage estimate
Chapter 2 Mathematical prerequisite
Chapter 3 Reliability estimation
Chapter 4 Cycle count and expected damage
Chapter 5 Sampled loads - Time series
Chapter 6 Gaussian loads, theory
Chapter 7 Gaussian loads, applications
Chapter 8 Markov loads
Chapter 9 Laplace moving average
Chapter 10 Non-linear load transformations
Chapter 11 Variance of damage estimate