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Department of Mechanical Engineering
PostDoc researcher

Dr. Chao Dang

 

Email: chao.dang@tu-dortmund.de

Room: Maschinenbaugebäude 1, Raum U04

Google Scholar:  Link

ResearchGate:  Link

© CRE

Research interests

  • Structural reliability analysis
  • Bayesian inference 
  • Bayesian active learning
  • Bayesian probabilistic numeric
  • Stochastic structural dynamics
  • Imprecise random fields

Teaching

Further information

  • Apr 2024-now: Postdoctoral Researcher, Chair for Reliability Engineering, TU Dortmund University, Germany

  • Apr 2020-Oct 2023: Doctoral Student, Institute for Risk and Reliability, Leibniz University Hannover, Germany

  • Sep 2016-Jun 2019: Master Student, College of Civil Engineering, Hunan University, China

  • Sep 2012-Jun 2016: Bachelor Student, College of Civil Engineering, Hunan University, China

Awards and Honors

  • Nov 2020: Excellent Master Thesis of Hunan Province.
     Excellent Master Thesis of Hunan University

Journal Paper:

  1. Dang C., Cicirello A., Valdebenito M., Faes M., Wei P., Beer M. (2024). Structural reliability analysis with extremely small failure probabilities: A quasi-Bayesian active learning method. Probabilistic Engineering Mechanics, 103613.

  2. Dang C., Beer M. (2024). Semi-Bayesian active learning quadrature for estimating extremely low failure probabilities. Reliability Engineering & System Safety, 246, 110052.

  3. Dang C., Faes, M. G., Valdebenito, M. A., Wei, P., & Beer, M. (2024). Partially Bayesian active learning cubature for structural reliability analysis with extremely small failure probabilities. Computer Methods in Applied Mechanics and Engineering, 422, 116828.

  4. Dang C.,  Valdebenito M. A., Faes M. G., Song J., Wei, P., Beer M. (2023). Structural reliability analysis by line sampling: A Bayesian active learning treatment. Structural Safety, 104, 102351.

  5. Dang C., Valdebenito M. A., Song J., Wei, P., Beer M. (2023).  Estimation of small failure probabilities by partially Bayesian active learning line sampling: Theory and algorithm. Computer Methods in Applied Mechanics and Engineering, 412, 116068.

  6. Dang C., Valdebenito M. A.,  Faes M. G., Wei P., Beer M. (2022). Structural reliability analysis: A Bayesian perspective. Structural Safety, 99, 102259. 

  7. Dang C., Wei P, Faes M. G., Valdebenito M. A.,  Beer M. (2022). Parallel adaptive Bayesian quadrature for rare event estimation. Reliability Engineering & System Safety, 225,108621.

  8. Dang C., Wei P., Faes M. G., Beer M. (2022). Bayesian probabilistic propagation of hybrid uncertainties: Estimation of response expectation function, its variable importance and bounds.  Computers & Structures, 270, 106860.

  9. Dang C., Wei P., Faes M. G., Valdebenito M. A.,  Beer M. (2022). Interval uncertainty propagation by a parallel Bayesian global optimization method. Applied Mathematical Modelling, 108, 220-235.

  10. Dang C., Wei P., Song J., Beer M. (2021). Estimation of Failure Probability Function under Imprecise Probabilities by Active Learning–Augmented Probabilistic Integration. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 7(4), 04021054.

  11. Dang C., Wei P., Beer M. (2021). An approach to evaluation of EVD and small failure probabilities of uncertain nonlinear structures under stochastic seismic excitations. Mechanical Systems and Signal Processing, 152, 107468.

  12. Dang C., Xu J. (2020). A mixture distribution with fractional moments for efficient seismic reliability analysis of nonlinear structures.  Engineering Structures, 208, 109912.