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Uncertainty Modeling for Engineering Applications

  • Flavio Canavero

Part of the PoliTO Springer Series book series (PTSS)

Table of contents

  1. Front Matter
    Pages i-viii
  2. Pranay Seshadri, Gianluca Iaccarino, Tiziano Ghisu
    Pages 1-25
  3. Luca Venturi, Davide Torlo, Francesco Ballarin, Gianluigi Rozza
    Pages 27-40
  4. Eduardo Souza de Cursi, Rafael Holdorf Lopez, André Gustavo Carlon
    Pages 41-54
  5. Tom Van Steenkiste, Joachim van der Herten, Ivo Couckuyt, Tom Dhaene
    Pages 55-69
  6. Günter Vermeeren, Wout Joseph, Luc Martens
    Pages 71-87
  7. E. Chiaramello, S. Fiocchi, M. Parazzini, P. Ravazzani, J. Wiart
    Pages 89-102
  8. Thomas Van der Vorst, Mathieu Van Eeckhaute, Aziz Benlarbi-Delaï, Julien Sarrazin, François Quitin, François Horlin et al.
    Pages 103-117
  9. Chaouki Kasmi, Sébastien Lalléchère, Sébastien Girard, José Lopes-Esteves, Pierre Bonnet, Françoise Paladian et al.
    Pages 119-133
  10. Dragan Poljak, Silvestar Sesnic, Mario Cvetkovic, Anna Susnjara, Pierre Bonnet, Khalil El Khamlichi Drissi et al.
    Pages 135-155
  11. Nicola Toscani, Flavia Grassi, Giordano Spadacini, Sergio A. Pignari
    Pages 157-172
  12. Carlo F. M. Carobbi
    Pages 173-184

About this book

Introduction

This book provides an overview of state-of-the-art uncertainty quantification (UQ) methodologies and applications, and covers a wide range of current research, future challenges and applications in various domains, such as aerospace and mechanical applications, structure health and seismic hazard, electromagnetic energy (its impact on systems and humans) and global environmental state change. Written by leading international experts from different fields, the book demonstrates the unifying property of UQ theme that can be profitably adopted to solve problems of different domains. The collection in one place of different methodologies for different applications has the great value of stimulating the cross-fertilization and alleviate the language barrier among areas sharing a common background of mathematical modeling for problem solution. The book is designed for researchers, professionals and graduate students interested in quantitatively assessing the effects of uncertainties in their fields of application. The contents build upon the workshop “Uncertainty Modeling for Engineering Applications” (UMEMA 2017), held in Torino, Italy in November 2017.

Keywords

Uncertainty Quantification Surrogate Models Response Surfaces Stochastic Models Sensitivity Analysis Model Reduction Risk Analysis Computational Fluid Dynamics UMEMA 2017 Variability Issues Prediction Uncertainty Multi-scale Modelling Model Validation

Editors and affiliations

  • Flavio Canavero
    • 1
  1. 1.Department of Electronics and Telecommunications (DET)Politecnico di TorinoTurinItaly

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