Open access peer-reviewed Edited Volume

Uncertainty Quantification and Model Calibration

Uncertainty quantification may appear daunting for practitioners due to its inherent complexity but can be intriguing and rewarding for anyone with mathematical ambitions and genuine concern for modeling quality. Uncertainty quantification is what remains to be done when too much credibility has been invested in deterministic analyses and unwarranted assumptions. Model calibration describes the inverse operation targeting optimal prediction and refers to inference of best uncertain model estimates from experimental calibration data. The limited applicability of most state-of-the-art approaches to many of the large and complex calculations made today makes uncertainty quantification and model calibration major topics open for debate, with rapidly growing interest from both science and technology, addressing subtle questions such as credible predictions of climate heating.

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Uncertainty Quantification and Model CalibrationEdited by Jan Peter Hessling

Published: July 5th 2017

DOI: 10.5772/65579

ISBN: 978-953-51-3280-6

Print ISBN: 978-953-51-3279-0

eBook (PDF) ISBN: 978-953-51-4754-1

Copyright year: 2017

Books open for chapter submissions

12285 Total Chapter Downloads

11 Crossref Citations

8 Web of Science Citations

22 Dimensions Citations

chaptersDownloads

Open access peer-reviewed

1. Introductory Chapter: Challenges of Uncertainty Quantification

By Jan Peter Hessling

1190

Open access peer-reviewed

2. Polynomial Chaos Expansion for Probabilistic Uncertainty Propagation

By Shuxing Yang, Fenfen Xiong and Fenggang Wang

2269

Open access peer-reviewed

3. State‐of‐the‐Art Nonprobabilistic Finite Element Analyses

By Wang Lei, Qiu Zhiping and Zheng Yuning

1185

Open access peer-reviewed

4. Epistemic Uncertainty Quantification of Seismic Damage Assessment

By Hesheng Tang, Dawei Li and Songtao Xue

1105

Open access peer-reviewed

5. Uncertainty Quantification and Reduction of Molecular Dynamics Models

By Xiaowang Zhou and Stephen M. Foiles

999

Open access peer-reviewed

6. Bayesian Uncertainty Quantification for Functional Response

By Xiao Guo, Yang He, Binbin Zhu, Yang Yang, Ke Deng, Ruopeng Liu and Chunlin Ji

1145

Open access peer-reviewed

7. Fitting Models to Data: Residual Analysis, a Primer

By Julia Martin, David Daffos Ruiz de Adana and Agustin G. Asuero

1889

Open access peer-reviewed

8. An Improved Wavelet‐Based Multivariable Fault Detection Scheme

By Fouzi Harrou, Ying Sun and Muddu Madakyaru

1144

Open access peer-reviewed

9. Practical Considerations on Indirect Calibration in Analytical Chemistry

By Antonio Gustavo González

1362

Edited Volume and chapters are indexed in

  • Worldcat
  • OpenAIRE
  • Google Scholar
  • AZ ebsco
  • Base
  • CNKI

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