Uncertainty modeling for engineering applications
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...
| Other Authors: | Canavero, Flavio,, SpringerLink (Online service) |
|---|---|
| Format: | eBook |
| Language: | English |
| Published: |
Cham, Switzerland :
Springer,
[2019]
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| Physical Description: |
1 online resource. |
| Series: |
PoliTO Springer series.
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| Subjects: |
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.