Uncertainty Modeling for Engineering Applications

Description

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. Front Matter ....Pages i-viii Quadrature Strategies for Constructing Polynomial Approximations (Pranay Seshadri, Gianluca Iaccarino, Tiziano Ghisu)....Pages 1-25 Weighted Reduced Order Methods for Parametrized Partial Differential Equations with Random Inputs (Luca Venturi, Davide Torlo, Francesco Ballarin, Gianluigi Rozza)....Pages 27-40 A New Approach for State Estimation (Eduardo Souza de Cursi, Rafael Holdorf Lopez, André Gustavo Carlon)....Pages 41-54 Data-Efficient Sensitivity Analysis with Surrogate Modeling (Tom Van Steenkiste, Joachim van der Herten, Ivo Couckuyt, Tom Dhaene)....Pages 55-69 Surrogate Modeling for Fast Experimental Assessment of Specific Absorption Rate (Günter Vermeeren, Wout Joseph, Luc Martens)....Pages 71-87 Stochastic Dosimetry for Radio-Frequency Exposure Assessment in Realistic Scenarios (E. Chiaramello, S. Fiocchi, M. Parazzini, P. Ravazzani, J. Wiart)....Pages 89-102 Application of Polynomial Chaos Expansions for Uncertainty Estimation in Angle-of-Arrival Based Localization (Thomas Van der Vorst, Mathieu Van Eeckhaute, Aziz Benlarbi-Delaï, Julien Sarrazin, François Quitin, François Horlin et al.)....Pages 103-117 Reducing the Statistical Complexity of EMC Testing: Improvements for Radiated Experiments Using Stochastic Collocation and Bootstrap Methods (Chaouki Kasmi, Sébastien Lalléchère, Sébastien Girard, José Lopes-Esteves, Pierre Bonnet, Françoise Paladian et al.)....Pages 119-133 On the Various Applications of Stochastic Collocation in Computational Electromagnetics (Dragan Poljak, Silvestar Sesnic, Mario Cvetkovic, Anna Susnjara, Pierre Bonnet, Khalil El Khamlichi Drissi et al.)....Pages 135-155 Hybrid Possibilistic-Probabilistic Approach to Uncertainty Quantification in Electromagnetic Compatibility Models (Nicola Toscani, Flavia Grassi, Giordano Spadacini, Sergio A. Pignari)....Pages 157-172 Measurement Uncertainty Cannot Always Be Calculated (Carlo F. M. Carobbi)....Pages 173-184