| A single-loop kriging surrogate modeling for time-dependent reliability analysis Z Hu, S Mahadevan Journal of Mechanical Design 138 (6), 061406, 2016 | 320 | 2016 |
| Time-dependent reliability analysis with joint upcrossing rates Z Hu, X Du Structural and Multidisciplinary Optimization 48, 893-907, 2013 | 264 | 2013 |
| Mixed efficient global optimization for time-dependent reliability analysis Z Hu, X Du Journal of Mechanical Design 137 (5), 051401, 2015 | 243 | 2015 |
| A comprehensive review of digital twin—part 1: modeling and twinning enabling technologies A Thelen, X Zhang, O Fink, Y Lu, S Ghosh, BD Youn, MD Todd, ... Structural and Multidisciplinary Optimization 65 (12), 354, 2022 | 212 | 2022 |
| Global sensitivity analysis-enhanced surrogate (GSAS) modeling for reliability analysis Z Hu, S Mahadevan Structural and Multidisciplinary Optimization 53, 501-521, 2016 | 202 | 2016 |
| Uncertainty quantification and management in additive manufacturing: current status, needs, and opportunities Z Hu, S Mahadevan The International Journal of Advanced Manufacturing Technology 93, 2855-2874, 2017 | 180 | 2017 |
| First order reliability method for time-variant problems using series expansions Z Hu, X Du Structural and Multidisciplinary Optimization 51, 1-21, 2015 | 159 | 2015 |
| A sampling approach to extreme value distribution for time-dependent reliability analysis Z Hu, X Du Journal of Mechanical Design 135 (7), 071003, 2013 | 155 | 2013 |
| Reliability analysis for hydrokinetic turbine blades Z Hu, X Du Renewable Energy 48, 251-262, 2012 | 149 | 2012 |
| Uncertainty quantification in prediction of material properties during additive manufacturing Z Hu, S Mahadevan Scripta materialia 135, 135-140, 2017 | 120 | 2017 |
| Simulation-based time-dependent reliability analysis for composite hydrokinetic turbine blades Z Hu, H Li, X Du, K Chandrashekhara Structural and Multidisciplinary Optimization 47, 765-781, 2013 | 112 | 2013 |
| First order reliability method with truncated random variables X Du, Z Hu | 102 | 2012 |
| Deep transfer convolutional neural network and extreme learning machine for lung nodule diagnosis on CT images X Huang, Q Lei, T Xie, Y Zhang, Z Hu, Q Zhou Knowledge-Based Systems 204, 106230, 2020 | 101 | 2020 |
| A comprehensive review of digital twin—part 2: roles of uncertainty quantification and optimization, a battery digital twin, and perspectives A Thelen, X Zhang, O Fink, Y Lu, S Ghosh, BD Youn, MD Todd, ... Structural and multidisciplinary optimization 66 (1), 1, 2023 | 95 | 2023 |
| A data-driven approach for process optimization of metallic additive manufacturing under uncertainty Z Wang, P Liu, Y Xiao, X Cui, Z Hu, L Chen Journal of Manufacturing Science and Engineering 141 (8), 081004, 2019 | 95 | 2019 |
| A sequential calibration and validation framework for model uncertainty quantification and reduction C Jiang, Z Hu, Y Liu, ZP Mourelatos, D Gorsich, P Jayakumar Computer Methods in Applied Mechanics and Engineering 368, 113172, 2020 | 91 | 2020 |
| Uncertainty quantification in machine learning for engineering design and health prognostics: A tutorial V Nemani, L Biggio, X Huan, Z Hu, O Fink, A Tran, Y Wang, X Zhang, ... Mechanical Systems and Signal Processing 205, 110796, 2023 | 87 | 2023 |
| Research on fluid-structure interaction for piston/cylinder tribopair of seawater hydraulic axial piston pump in deep-sea environment S Nie, M Guo, F Yin, H Ji, Z Ma, Z Hu, X Zhou Ocean Engineering 219, 108222, 2021 | 75 | 2021 |
| Resilience assessment based on time-dependent system reliability analysis Z Hu, S Mahadevan Journal of Mechanical Design 138 (11), 111404, 2016 | 69 | 2016 |
| R2-RRT*: Reliability-based robust mission planning of off-road autonomous ground vehicle under uncertain terrain environment C Jiang, Z Hu, ZP Mourelatos, D Gorsich, P Jayakumar, Y Fu, M Majcher IEEE Transactions on Automation Science and Engineering 19 (2), 1030-1046, 2021 | 67 | 2021 |
Sankaran MahadevanJohn R. Murray Sr. Professor of EngineeringVerified email at vanderbilt.edu
