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.
Produktdetails
- Produktdetails
- Verlag: Taylor & Francis Ltd
- Seitenzahl: 306
- 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: 306
- 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 earned a PhD in mathematical statistics at Lund University, Sweden, 1986. During 1988-1990 he was a post-doctoral student at the Department of Statistics, Colorado State University, and in 1995 he was a visiting professor at the University of Queensland, Brisbane, Australia. He became a Professor of Mathematical Statistics at Lund in 1999 and from 2007 at Chalmers University of Technology, Göteborg. There he also worked as a scientific advisor to the Fraunhofer-Chalmers Centre for industrial mathematics. Since 2017 he has been a Professor Emeritus. His main interest is in engineering applications of random processes and fields and in the modelling of complex environmental loads, wind, sea waves and vehicle operating conditions. He is a coauthor of Guide to Load Analysis for Durability in Vehicle Engineering and Probability and Risk Analysis: An Introduction for Engineers. Sayan Gupta is a Professor at the Indian Institute of Technology Madras in the Department of Applied Mechanics. He graduated with a degree in civil engineering from Jadavpur University Kolkata in 1997, earned a PhD at the Indian Institute of Science Bangalore in 2005 and was a post-doctoral student at the Technical University of Delft from 2005 to 2007. He has held visiting positions at Waterloo, Lund, and 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 he is the coordinator for the degree program on Complex Systems and Dynamics. His primary research interests include non-linear dynamics and stochastic mechanics. Georg Lindgren is Professor Emeritus in the Engineering Faculty at Lund University, Sweden. He earned a PhD in mathematical statistics at Lund in 1972 with a thesis inspired by an intriguing question regarding random load cycle ranges. After a period as an Associate Professor at Lund and Umeå, he became a Professor of Mathematical Statistics at Lund in 1986, and since 2006 he has been a Professor Emeritus. His main interest is random processes and their use in communication technology, marine and mechanical engineering and medicine. He is a coauthor of a 1983 research volume on the extremes and related properties of random sequences and processes and two research/advanced student texts on stationary stochastic processes. He is a member of the Royal Swedish Academy of Engineering Sciences (IVA).
1. Fatigue Damage. 2. Mathematical Prerequisite. 3. Reliability Estimation. 4. Cycle Count and Expected Damage. 5. Sampled Loads
Time Series. 6. Gaussian Loads
Theory. 7. Gaussian Loads
Applications. 8. Markov Loads. 9. Laplace Moving Average (LMA). 10. Non
Linear Load Transformations. 11. Variance of Damage Estimate.
Time Series. 6. Gaussian Loads
Theory. 7. Gaussian Loads
Applications. 8. Markov Loads. 9. Laplace Moving Average (LMA). 10. Non
Linear Load Transformations. 11. Variance of Damage Estimate.
1. Fatigue Damage. 2. Mathematical Prerequisite. 3. Reliability Estimation. 4. Cycle Count and Expected Damage. 5. Sampled Loads
Time Series. 6. Gaussian Loads
Theory. 7. Gaussian Loads
Applications. 8. Markov Loads. 9. Laplace Moving Average (LMA). 10. Non
Linear Load Transformations. 11. Variance of Damage Estimate.
Time Series. 6. Gaussian Loads
Theory. 7. Gaussian Loads
Applications. 8. Markov Loads. 9. Laplace Moving Average (LMA). 10. Non
Linear Load Transformations. 11. Variance of Damage Estimate.