| Uncertainty Quantification and Model Validation of Fatigue Crack Growth Prediction S Sankararaman, Y Ling, S Mahadevan Engineering Fracture Mechanics 78 (7), 1487-1504, 2011 | 149 | 2011 |
| Likelihood-based representation of epistemic uncertainty due to sparse point data and/or interval data S Sankararaman, S Mahadevan Reliability Engineering & System Safety 96 (7), 814-824, 2011 | 113 | 2011 |
| Separating the contributions of variability and parameter uncertainty in probability distributions S Sankararaman, S Mahadevan Reliability Engineering & System Safety 112, 187-199, 2013 | 89 | 2013 |
| Significance, interpretation, and quantification of uncertainty in prognostics and remaining useful life prediction S Sankararaman Mechanical Systems and Signal Processing 52, 228-247, 2015 | 88 | 2015 |
| Uncertainty quantification in remaining useful life prediction using first-order reliability methods S Sankararaman, MJ Daigle, K Goebel IEEE Transactions on Reliability 63 (2), 603-619, 2014 | 74 | 2014 |
| Model validation under epistemic uncertainty S Sankararaman, S Mahadevan Reliability Engineering & System Safety 96 (9), 1232-1241, 2011 | 60 | 2011 |
| Integration of model verification, validation, and calibration for uncertainty quantification in engineering systems S Sankararaman, S Mahadevan Reliability Engineering & System Safety 138, 194-209, 2015 | 54 | 2015 |
| Bayesian methodology for diagnosis uncertainty quantification and health monitoring S Sankararaman, S Mahadevan Structural Control and Health Monitoring, 2011 | 54 | 2011 |
| Likelihood-based approach to multidisciplinary analysis under uncertainty S Sankararaman, S Mahadevan Journal of Mechanical Design 134 (3), 031008, 2012 | 52 | 2012 |
| Condition-based prediction of time-dependent reliability in composites J Chiachío, M Chiachío, S Sankararaman, A Saxena, K Goebel Reliability Engineering & System Safety 142, 134-147, 2015 | 48 | 2015 |
| Bayesian model selection and parameter estimation for fatigue damage progression models in composites J Chiachío, M Chiachío, A Saxena, S Sankararaman, G Rus, K Goebel International Journal of Fatigue 70, 361-373, 2015 | 45 | 2015 |
| Analytical algorithms to quantify the uncertainty in remaining useful life prediction S Sankararaman, M Daigle, A Saxena, K Goebel 2013 IEEE Aerospace Conference, 1-11, 2013 | 44 | 2013 |
| Uncertainty Quantification and Integration in Engineering Systems S Sankararaman Vanderbilt University, 2012 | 44 | 2012 |
| Uncertainty Quantification in Fatigue Crack Growth Prognosis S Sankararaman, Y Ling, C Shantz, S Mahadevan International Journal of Prognostics and Health Management 2 (1), 15, 2011 | 44 | 2011 |
| Uncertainty quantification in fatigue damage prognosis S Sankararaman, Y Ling, C Shantz, S Mahadevan 1st Annual Conference of the Prognostics and Health Management Society, 2009 | 43 | 2009 |
| 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 | 42 | 2011 |
| Why is the Remaining Useful Life Prediction Uncertain? S Sankararaman, K Goebel Annual Conference of the Pr ognostics and Health Management Society, USA, 2013 | 41 | 2013 |
| 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 | 39 | 2011 |
| Test resource allocation in hierarchical systems using Bayesian networks S Sankararaman, K McLemore, S Mahadevan, SC Bradford, LD Peterson AIAA journal 51 (3), 537-550, 2013 | 35 | 2013 |
| Methodologies for system-level remaining useful life prediction H Khorasgani, G Biswas, S Sankararaman Reliability Engineering & System Safety 154, 8-18, 2016 | 32 | 2016 |
Sankaran MahadevanJohn R. Murray Sr. Professor of EngineeringVerified email at vanderbilt.edu