Mechanical Engineering under Uncertainties

From Classical Approaches to Some Recent Developments

SCIENCES – Mechanics

Mechanical Engineering under Uncertainties

Edited by

Christian Gogu, University Toulouse III-Paul Sabatier, France

ISBN : 9781789450101

Publication Date : March 2021

Hardcover 342 pp

165.00 USD



Considering the uncertainties in mechanical engineering in order to improve the performance of future products or systems is becoming a competitive advantage, sometimes even a necessity, when seeking to guarantee an increasingly high safety requirement.

Mechanical Engineering under Uncertainties deals with modeling, quantification and propagation of uncertainties. It also examines how to take into account uncertainties through reliability analyses and optimization under uncertainty. The spectrum of the methods presented ranges from classical approaches to more recent developments and advanced methods. The methodologies are illustrated by concrete examples in various fields of mechanics (civil engineering, mechanical engineering and fluid mechanics).

This book is intended for both (young) researchers and engineers interested in the treatment of uncertainties in mechanical engineering.


Part 1. Modeling, Propagation and Quantification of Uncertainties
1. Uncertainty Modeling, Christian Gogu.
2. Microstructure Modeling and Characterization, François Willot.
3. Uncertainty Propagation at the Scale of Aging Civil Engineering Structures, David Bouhkiti, Julien Baroth and Frédéric Dufour.
4. Reduction of Uncertainties in Multidisciplinary Analysis Based on a Polynomial Chaos Sensitivity Study, Sylvain Dubreuil, Nathalie Bartoli, Christian Gogu and
Thierry Lefebvre.

Part 2. Taking Uncertainties into Account: Reliability Analysis and Optimization under Uncertainties
5. Rare-event Probability Estimation, Jean-Marc Bourinet.
6. Adaptive Kriging-based Methods for Failure Probability Evaluation: Focus on AK Methods, Cécile Mattrand, Pierre Beaurepaire and Nicolas Gayton.
7. Global Reliability-oriented Sensitivity Analysis under Distribution Parameter Uncertainty, Vincent Chabridon, Mathieu Balesdent, Guillaume Perrin, Jérôme Morio, Jean-Marc Bourinet and Nicolas Gayton.
8. Stochastic Multiobjective Optimization: A Descent Algorithm, Quentin Mercier and Fabrice Poirion.

About the authors

Christian Gogu is Associate Professor at the University Toulouse III-Paul Sabatier, France. His research, which he carries out at the Clément Ader Institute, focuses, in particular, on taking into account uncertainties in the design and optimization of aeronautical systems.