Uncertainty Modeling for Engineering Applications

• Corporate Author: SpringerLink (Online service)
• Other Authors: Canavero, Flavio (Editor, http://id.loc.gov/vocabulary/relators/edt)
• Format: Electronic eBook
• Language: English
• Published: Cham : Springer International Publishing : Imprint: Springer, 2019.
• Edition: 1st ed. 2019.
• Series: PoliTO Springer Series,
• Subjects: Computational intelligence.; Quality control.; Reliability.; Industrial safety.; Probabilities.; Computational Intelligence.; Quality Control, Reliability, Safety and Risk.; Probability Theory and Stochastic Processes.

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, e...

Table of Contents:

• Quadrature Strategies for Constructing Polynomial Approximations
• Weighted reduced order methods for parametrized partial differential equations with random inputs
• A new approach for state estimation
• Data-efficient Sensitivity Analysis with Surrogate Modeling
• Application of Polynomial Chaos Expansions for Uncertainty Estimation in Angle-of-Arrival based Localization
• Surrogate Modeling for Fast Experimental Assessment of Specific Absorption Rate
• Stochastic Dosimetry for Radio-Frequency exposure assessment in realistic scenarios
• On the Various Applications of Stochastic Collocation in Computational Electromagnetics
• Reducing the statistical complexity of EMC testing: improvements for radiated experiments using stochastic collocation and bootstrap methods
• Hybrid Possibilistic-Probabilistic Approach to Uncertainty Quantification in Electromagnetic Compatibility Models
• Measurement uncertainty cannot always be calculated.