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Basic Framework and Main Methods of Uncertainty Quantification

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  • Juan Zhang
  • Junping Yin
  • Ruili Wang

Abstract

Since 2000, the research of uncertainty quantification (UQ) has been successfully applied in many fields and has been highly valued and strongly supported by academia and industry. This review firstly discusses the sources and the types of uncertainties and gives an overall discussion on the goal, practical significance, and basic framework of the research of UQ. Then, the core ideas and typical methods of several important UQ processes are introduced, including sensitivity analysis, uncertainty propagation, model calibration, Bayesian inference, experimental design, surrogate model, and model uncertainty analysis.

Suggested Citation

  • Juan Zhang & Junping Yin & Ruili Wang, 2020. "Basic Framework and Main Methods of Uncertainty Quantification," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-18, August.
    • Handle: RePEc:hin:jnlmpe:6068203
    DOI: 10.1155/2020/6068203
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    Cited by:

    1. Lamia Hammadi & Hajar Raillani & Babacar Mbaye Ndiaye & Badria Aggoug & Abdessamad El Ballouti & Said Jidane & Lahcen Belyamani & Eduardo Souza de Cursi, 2023. "Uncertainty Quantification for Epidemic Risk Management: Case of SARS-CoV-2 in Morocco," IJERPH, MDPI, vol. 20(5), pages 1-29, February.
    2. Gradov, Dmitry Vladimirovich & Yusuf, Yusuf Oluwatoki & Ohjainen, Jussi & Suuronen, Jarkko & Eskola, Roope & Roininen, Lassi & Koiranen, Tuomas, 2022. "Modelling of a continuous veneer drying unit of industrial scale and model-based ANOVA of the energy efficiency," Energy, Elsevier, vol. 244(PA).
    3. Duc-Phi Do & Ngoc-Tuyen Tran & Dashnor Hoxha & Minh-Ngoc Vu & Gilles Armand, 2022. "Time-Dependent Behavior of Callovo-Oxfordian Claystone for Nuclear Waste Disposal: Uncertainty Quantification from In-Situ Convergence Measurements," Sustainability, MDPI, vol. 14(14), pages 1-17, July.

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