| 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 | 421 | 2017 |
| Uncertainty quantification and model validation of fatigue crack growth prediction S Sankararaman, Y Ling, S Mahadevan Engineering Fracture Mechanics 78 (7), 1487-1504, 2011 | 261 | 2011 |
| Quantitative model validation techniques: New insights Y Ling, S Mahadevan Reliability Engineering & System Safety 111, 217-231, 2013 | 188 | 2013 |
| Integration of structural health monitoring and fatigue damage prognosis Y Ling, S Mahadevan Mechanical Systems and Signal Processing 28, 89-104, 2012 | 142 | 2012 |
| Selection of model discrepancy priors in Bayesian calibration Y Ling, J Mullins, S Mahadevan Journal of Computational Physics 276, 665-680, 2014 | 119 | 2014 |
| Separation of aleatory and epistemic uncertainty in probabilistic model validation J Mullins, Y Ling, S Mahadevan, L Sun, A Strachan Reliability Engineering & System Safety 147, 49-59, 2016 | 94 | 2016 |
| Uncertainty quantification in fatigue crack growth prognosis S Sankararaman, Y Ling, C Shantz, S Mahadevan International Journal of Prognostics and Health Management 2 (1), 2011 | 65 | 2011 |
| Stochastic prediction of fatigue loading using real-time monitoring data Y Ling, C Shantz, S Mahadevan, S Sankararaman International Journal of Fatigue 33 (7), 868-879, 2011 | 62 | 2011 |
| Uncertainty quantification in fatigue damage prognosis S Sankararaman, Y Ling, C Shantz, S Mahadevan Annual Conference of the Prognostics and Health Management Society, 2009 | 61 | 2009 |
| 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 | 54 | 2017 |
| Inference of equivalent initial flaw size under multiple sources of uncertainty S Sankararaman, Y Ling, C Shantz, S Mahadevan International Journal of Fatigue 33 (2), 75-89, 2011 | 51 | 2011 |
| Statistical inference of equivalent initial flaw size with complicated structural geometry and multi-axial variable amplitude loading S Sankararaman, Y Ling, S Mahadevan International Journal of Fatigue 32 (10), 1689-1700, 2010 | 45 | 2010 |
| Expected-Improvement-Based Methods for Adaptive Sampling in Multi-Objective Optimization Problems J Kristensen, Y Ling, I Asher, L Wang ASME 2016 International Design Engineering Technical Conferences and …, 2016 | 28 | 2016 |
| An intelligent sampling framework for multi-objective optimization in high dimensional design space Y Ling, S Ghosh, I Asher, J Kristensen, K Ryan, L Wang 2018 AIAA/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials …, 2018 | 19 | 2018 |
| Methods and systems for implementing a data reconciliation framework IM Asher, AR Cerrone, Y Ling, A Srivastava, AK Subramaniyan, F Viana, ... US Patent 10,394,770, 2019 | 18 | 2019 |
| A gaussian process modeling approach for fast robust design with uncertain inputs KM Ryan, J Kristensen, Y Ling, S Ghosh, I Asher, L Wang Turbo Expo: Power for Land, Sea, and Air 51135, V07AT32A012, 2018 | 18 | 2018 |
| Bayesian multi-source modeling with legacy data S Ghosh, I Asher, J Kristensen, Y Ling, K Ryan, L Wang 2018 AIAA Non-Deterministic Approaches Conference, 1663, 2018 | 14 | 2018 |
| Uncertainty quantification in time-dependent reliability analysis Y Ling Vanderbilt University, 2013 | 14 | 2013 |
| Two-stage planar approximation of non-planar crack growth VK Hombal, Y Ling, KA Wolfe, S Mahadevan Engineering Fracture Mechanics 96, 147-164, 2012 | 14 | 2012 |
| Calibration of multi-physics computational models using Bayesian networks Y Ling, J Mullins, S Mahadevan arXiv preprint arXiv:1206.5015, 2012 | 11 | 2012 |
Sankaran MahadevanJohn R. Murray Sr. Professor of Engineeringبريد إلكتروني تم التحقق منه على vanderbilt.edu