Dynamic Bayesian network for aircraft wing health monitoring digital twin C Li, S Mahadevan, Y Ling, S Choze, L Wang Aiaa Journal 55 (3), 930-941, 2017 | 423 | 2017 |
An efficient modularized sample-based method to estimate the first-order Sobol׳ index C Li, S Mahadevan Reliability Engineering & System Safety 153, 110-121, 2016 | 106 | 2016 |
Role of calibration, validation, and relevance in multi-level uncertainty integration C Li, S Mahadevan Reliability Engineering & System Safety 148, 32-43, 2016 | 92 | 2016 |
A dynamic Bayesian network approach for digital twin C Li, S Mahadevan, Y Ling, L Wang, S Choze 19th AIAA Non-Deterministic Approaches Conference, 1566, 2017 | 52 | 2017 |
Relative contributions of aleatory and epistemic uncertainty sources in time series prediction C Li, S Mahadevan International Journal of Fatigue 82, 474-486, 2016 | 52 | 2016 |
A non-parametric method to determine basic probability assignment for classification problems P Xu, X Su, S Mahadevan, C Li, Y Deng Applied intelligence 41, 681-693, 2014 | 49 | 2014 |
Efficient approximate inference in Bayesian networks with continuous variables C Li, S Mahadevan Reliability Engineering & System Safety 169, 269-280, 2018 | 38 | 2018 |
Sensitivity analysis of a Bayesian network C Li, S Mahadevan ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B …, 2018 | 29 | 2018 |
Application of conservative surrogate to reliability based vehicle design for crashworthiness F Pan, P Zhu, W Chen, C Li Journal of Shanghai Jiaotong University (Science) 18, 159-165, 2013 | 17 | 2013 |
Optimal selection of calibration and validation test samples under uncertainty J Mullins, C Li, S Mahadevan, A Urbina Model Validation and Uncertainty Quantification, Volume 3: Proceedings of …, 2014 | 14 | 2014 |
Uncertainty quantification and output prediction in multi-level problems C Li, S Mahadevan 16th AIAA Non-Deterministic Approaches Conference, 0124, 2014 | 13 | 2014 |
Global Sensitivity Analysis Using an Auxiliary Variable Approach C Li, S Mahadeven 16th AIAA Non-Deterministic Approaches Conference, American Institute of …, 2015 | 12 | 2015 |
Probabilistic integration of validation and calibration results for prediction level uncertainty quantification: Application to structural dynamics J Mullins, C Li, S Sankararaman, S Mahadevan, A Urbina AIAA Paper, 2013 | 11 | 2013 |
Uncertainty quantification using multi-level calibration and validation data J Mullins, C Li, S Sankararaman, S Mahadevan, A Urbina 54th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials …, 2013 | 11 | 2013 |
Robust test resource allocation using global sensitivity analysis C Li, S Mahadevan 18th AIAA Non-Deterministic Approaches Conference, 0952, 2016 | 8 | 2016 |
Sensitivity analysis and uncertainty integration for system diagnosis and prognosis C Li | 5 | 2016 |
Sensitivity Analysis for Test Resource Allocation C Li, S Mahadevan Model Validation and Uncertainty Quantification, Volume 3: Proceedings of …, 2015 | 4 | 2015 |
钢制车轮弯曲疲劳寿命的影响因素 李忱钊, 郭永进, 朱平, 孟瑾, 石磊 机械设计与研究 27 (2), 44-47, 2011 | 4 | 2011 |
Confidence in the prediction of unmeasured system output using roll-up methodology K Neal, C Li, Z Hu, S Mahadevan, J Mullins, B Schroeder, A Subramanian Model Validation and Uncertainty Quantification, Volume 3: Proceedings of …, 2019 | 3 | 2019 |
Robust Resource Allocation for Calibration and Validation Tests C Li, S Mahadevan Journal of Verification, Validation and Uncertainty Quantification 2 (2), 021004, 2017 | 2 | 2017 |