Journal papers

(student advised by Prof. Zhao, * corresponding author)

2024

  1. Diao, X.*, Zhao, Y., Vaddi, P.K., Pietrykowski, M., Khafizov, M. and Smidts, C., 2024. Multiple aspects maintenance ontology-based intelligent maintenance optimization framework for safety-critical systems. AI EDAM, 38, p.e3.
  2. Diao, X.*, Zhao, Y., Smidts, C., Vaddi, P.K., Li, R., Lei, H., Chakhchoukh, Y., Johnson, B. and Le Blanc, K., 2024. Dynamic probabilistic risk assessment for electric grid cybersecurity. Reliability Engineering & System Safety, 241, p.109699.

2023

  1. Zhao, Y., Vaddi, P.K., Pietrykowski, M., Khafizov, M. and Smidts, C.*, 2023. An empirical study of the added value of the sequential learning of model parameters to industrial system health monitoring. Reliability Engineering & System Safety, 240, p.109592.

Before 2023

  1. Zhao, Y.* and Smidts, C., 2022. Reinforcement learning for adaptive maintenance policy optimization under imperfect knowledge of the system degradation model and partial observability of system states. Reliability Engineering & System Safety, 224, p.108541.
  2. Zhao, Y.*, 2022. A Bayesian approach to comparing human reliability analysis methods using human performance data. Reliability Engineering & System Safety, 219, p.108213.
  3. Zhao, Y.*, Gao, W. and Smidts, C., 2021. Sequential Bayesian inference of transition rates in the hidden Markov model for multi-state system degradation. Reliability Engineering & System Safety, 214, p.107662.
  4. Zhao, Y.* and Smidts, C., 2021. CMS-BN: a cognitive modeling and simulation environment for human performance assessment, part 1 – methodology. Reliability Engineering & System Safety, 213, p.107776.
  5. Zhao, Y.* and Smidts, C., 2021. CMS-BN: a cognitive modeling and simulation environment for human performance assessment, part 2 – application. Reliability Engineering & System Safety, 213,107775.
  6. Zhao, Y., Tong, J. and Zhang, L.*, 2021. Rapid source term prediction in nuclear power plant accidents based on dynamic Bayesian networks and probabilistic risk assessment. Annals of Nuclear Energy, 158, p.108217.
  7. Wang, Q.*, Diao, X., Zhao, Y., Chen, F.*, Yang, G. and Smidts, C.*, 2021. An expert-based method for the risk analysis of functional failures in the fracturing system of unconventional natural gas. Energy, 220, p.119570.
  8. Vaddi, P.K.*, Pietrykowski, M.C., Kar, D., Diao, X., Zhao, Y., Mabry, T., Ray, I. and Smidts, C., 2020. Dynamic bayesian networks based abnormal event classifier for nuclear power plants in case of cyber security threats. Progress in Nuclear Energy, 128, p.103479.
  9. Gao, W., Zhao, Y. and Smidts, C.*, 2020. Component detection in piping and instrumentation diagrams of nuclear power plants based on neural networks. Progress in Nuclear Energy, 128, p.103491.
  10. Zhao, Y.*, Huang, L., Smidts, C. and Zhu, Q., 2020. Finite-horizon semi-Markov game for time-sensitive attack response and probabilistic risk assessment in nuclear power plants. Reliability Engineering & System Safety, 201, p.106878.
  11. Zhao, Y.* and Smidts, C., 2020. A control-theoretic approach to detecting and distinguishing replay attacks from other anomalies in nuclear power plants. Progress in Nuclear Energy, 123, p.103315.
  12. Zhao, Y., Tong, J., Zhang, L.* and Wu, G., 2020. Diagnosis of operational failures and on-demand failures in nuclear power plants: an approach based on dynamic Bayesian networks. Annals of Nuclear Energy, 138, p. 107181.
  13. Shirley, R.B.*, Smidts, C. and Zhao, Y., 2020. Development of a quantitative Bayesian network mapping objective factors to subjective performance shaping factor evaluations: An example using student operators in a digital nuclear power plant simulator. Reliability Engineering & System Safety, 194, p.106416.
  14. Zhao, Y.*, Diao, X., Huang, J. and Smidts, C., 2019. Automated Identification of Causal Relationships in Nuclear Power Plant Event Reports. Nuclear Technology, 205(8), pp.1021-1034.
  15. Zhao, Y.* and Smidts, C., 2019. A method for systematically developing the knowledge base of reactor operators in nuclear power plants to support cognitive modeling of operator performance. Reliability Engineering & System Safety, 186, pp.64-77.
  16. Wu, G., Tong, J., Zhang, L.*, Zhao, Y. and Duan, Z., 2018. Framework for fault diagnosis with multi-source sensor nodes in nuclear power plants based on a Bayesian network. Annals of Nuclear Energy, 122, pp.297-308.
  17. Diao, X.*, Zhao, Y., Pietrykowski, M., Wang, Z., Bragg-Sitton, S. and Smidts, C., 2018. Fault Propagation and Effects Analysis for Designing an Online Monitoring System for the Secondary Loop of the Nuclear Power Plant Portion of a Hybrid Energy System. Nuclear Technology, 202(2-3), pp.106-123.
  18. Wu, G., Tong, J., Gao, Y., Zhang, L.* and Zhao, Y., 2018. Uncertainty analysis of containment dose rate for core damage assessment in nuclear power plants. Nuclear Engineering and Technology, 50(5), pp.673-682.
  19. Zhao, Y., Tong, J., Zhang, L.* and Zhang, Q., 2015. Pilot study of dynamic Bayesian networks approach for fault diagnostics and accident progression prediction in HTR-PM. Nuclear Engineering and Design, 291, pp.154-162.
  20. Zhao, Y., Zhang, L. and Tong, J.*, 2015. Development of rapid atmospheric source term estimation system for AP1000 nuclear power plant. Progress in Nuclear Energy, 81, pp.264-275.
  21. Zhao, Y., Tong, J., Zhang, L.*, Zhang, Q., Liu, T. and Qu, J., 2015. Comparative study of aerosol decontamination factor in containment during light water reactor plant accident. Atomic Energy Science and Technology, 49(6), pp.1095-1100.
  22. Zhao, Y., Zhang, L.*, Tong, J., Zhang, Q. and Qu, J., 2014. Preliminary study on application of BP neural network in AP1000 nuclear power plant accident diagnosis. Atomic Energy Science and Technology, 48(suppl.), pp.480-484.
  23. Gao, Y., Zhao, Y., Zhang, L.­*, Tong, J. and Qu, J., 2014. Study on spent fuel accident source term estimation method. Atomic Energy Science and Technology, 48(suppl.), pp.352-356.