Details
20th International Probabilistic Workshop
IPW 2024Lecture Notes in Civil Engineering, Band 494
267,49 € |
|
Verlag: | Springer |
Format: | |
Veröffentl.: | 05.07.2024 |
ISBN/EAN: | 9783031602719 |
Sprache: | englisch |
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Beschreibungen
This volume presents the proceedings of the 20th International Probabilistic Workshop (IPW), which was held in Guimarães, Portugal on May 8-10, 2024. Probabilistic methods are currently of crucial importance for research and developments in the field of engineering, which face challenges presented by new materials and technologies and rapidly changing societal needs and values. Contemporary needs related to, for example, performance-based design, service-life design, life-cycle analysis, product optimization, assessment of existing structures and structural robustness give rise to new developments as well as accurate and practically applicable probabilistic and statistical engineering methods to support these developments. These proceedings are a valuable resource for anyone interested in contemporary developments in the field of probabilistic engineering applications.<p></p>
This volume presents the proceedings of the 20th International Probabilistic Workshop (IPW), which was held in Guimarães, Portugal on May 8-10, 2024. Probabilistic methods are currently of crucial importance for research and developments in the field of engineering, which face challenges presented by new materials and technologies and rapidly changing societal needs and values. Contemporary needs related to, for example, performance-based design, service-life design, life-cycle analysis, product optimization, assessment of existing structures and structural robustness give rise to new developments as well as accurate and practically applicable probabilistic and statistical engineering methods to support these developments. These proceedings are a valuable resource for anyone interested in contemporary developments in the field of probabilistic engineering applications.
Contains latest research developments in probability and statistics for engineering applications Provides methods and tools for uncertainty quantification and modeling Illustrates the application of reliability-based design and optimization
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