Computational Methods in Stochastic Dynamics - Info and Reading Options
By Manolis Papadrakakis
"Computational Methods in Stochastic Dynamics" was published by Springer in 2011 - Dordrecht, it has 342 pages and the language of the book is English.
“Computational Methods in Stochastic Dynamics” Metadata:
- Title: ➤ Computational Methods in Stochastic Dynamics
- Author: Manolis Papadrakakis
- Language: English
- Number of Pages: 342
- Publisher: Springer
- Publish Date: 2011
- Publish Location: Dordrecht
“Computational Methods in Stochastic Dynamics” Subjects and Themes:
- Subjects: ➤ Engineering - Computer science - Vibration - Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences - Vibration, Dynamical Systems, Control - Computational Science and Engineering - Dynamics - Stochastic processes
Edition Specifications:
- Pagination: xii, 342
Edition Identifiers:
- The Open Library ID: OL37121036M - OL19836295W
- ISBN-13: 9789048199877
- All ISBNs: 9789048199877
AI-generated Review of “Computational Methods in Stochastic Dynamics”:
"Computational Methods in Stochastic Dynamics" Description:
Open Data:
At the dawn of the 21st century, computational stochastic dynamics is an emerging research frontier. This book focuses on advanced computational methods and software tools which can highly assist in tackling complex problems in stochastic dynamic/seismic analysis and design of structures. The book is primarily intended for researchers and post-graduate students in the fields of computational mechanics and stochastic structural dynamics. Nevertheless, practice engineers as well could benefit from it as most code provisions tend to incorporate probabilistic concepts in the analysis and design of structures. The book addresses mathematical and numerical issues in stochastic structural dynamics and connects them to real-world applications. It consists of 16 chapters dealing with recent advances in a wide range of related topics (dynamic response variability and reliability of stochastic systems, risk assessment, stochastic simulation of earthquake ground motions, efficient solvers for the analysis of stochastic systems, dynamic stability, stochastic modelling of heterogeneous materials). Numerical examples demonstrating the significance of the proposed methods are presented in each chapter
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