Structural and Multidisciplinary Optimization

, Volume 60, Issue 4, pp 1619–1644 | Cite as

Review of statistical model calibration and validation—from the perspective of uncertainty structures

  • Guesuk Lee
  • Wongon Kim
  • Hyunseok OhEmail author
  • Byeng D. YounEmail author
  • Nam H. Kim
Review Article


Computer-aided engineering (CAE) is now an essential instrument that aids in engineering decision-making. Statistical model calibration and validation has recently drawn great attention in the engineering community for its applications in practical CAE models. The objective of this paper is to review the state-of-the-art and trends in statistical model calibration and validation, based on the available extensive literature, from the perspective of uncertainty structures. After a brief discussion about uncertainties, this paper examines three problem categories—the forward problem, the inverse problem, and the validation problem—in the context of techniques and applications for statistical model calibration and validation.


Forward problem Inverse problem Validation problem Uncertainty quantification Statistical model calibration Validity check 


Funding information

This work was supported by a grant from the Institute of Advanced Machinery and Design at Seoul National University (SNU-IAMD) and the Korea Institute of Machinery and Materials (Project No.: NK213E).

Compliance with ethical standards

Conflict of interest

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Mechanical and Aerospace EngineeringSeoul National UniversitySeoulSouth Korea
  2. 2.School of Mechanical EngineeringGwangju Institute of Science and TechnologyGwangjuSouth Korea
  3. 3.Department of Mechanical and Aerospace Engineering & Institute of Advanced Machines and DesignSeoul National UniversitySeoulSouth Korea
  4. 4.OnePredict Inc.SeoulSouth Korea
  5. 5.Department of Mechanical and Aerospace EngineeringUniversity of FloridaGainesvilleUSA

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