| Continuum interpretation of virial stress in molecular simulations AK Subramaniyan, CT Sun International Journal of Solids and Structures 45 (14-15), 4340-4346, 2008 | 525 | 2008 |
| Enhancing compressive strength of unidirectional polymeric composites using nanoclay AK Subramaniyan, CT Sun Composites Part A: Applied Science and Manufacturing 37 (12), 2257-2268, 2006 | 196 | 2006 |
| Validation of a peridynamic model for fatigue cracking G Zhang, Q Le, A Loghin, A Subramaniyan, F Bobaru Engineering Fracture Mechanics 162, 76-94, 2016 | 150 | 2016 |
| Generating Recommendations Based on Semantic Knowledge Capture P Jethwa, AK Subramaniyan, AN Iankoulski US Patent App. 16/162,783, 2019 | 118 | 2019 |
| Toughening polymeric composites using nanoclay: crack tip scale effects on fracture toughness AK Subramaniyan, CT Sun Composites Part A: applied science and manufacturing 38 (1), 34-43, 2007 | 110 | 2007 |
| A survey of Bayesian calibration and physics-informed neural networks in scientific modeling FAC Viana, AK Subramaniyan Archives of Computational Methods in Engineering 28 (5), 3801-3830, 2021 | 52 | 2021 |
| Generating natural language recommendations based on an industrial language model X Zhu, AK Subramaniyan, H Zhao, XU Zhengjie US Patent 10,872,204, 2020 | 51 | 2020 |
| Interlaminar fracture behavior of nanoclay reinforced glass fiber composites AK Subramaniyan, CT Sun Journal of Composite Materials 42 (20), 2111-2122, 2008 | 40 | 2008 |
| Improving high-dimensional physics models through Bayesian calibration with uncertain data NC Kumar, AK Subramaniyan, L Wang Turbo Expo: Power for Land, Sea, and Air 44731, 407-416, 2012 | 35 | 2012 |
| Calibrating transient models with multiple responses using Bayesian inverse techniques NC Kumar, AK Subramaniyan, L Wang, G Wiggs Turbo Expo: Power for Land, Sea, and Air 55263, V07AT28A007, 2013 | 28 | 2013 |
| Challenges in uncertainty, calibration, validation and predictability of engineering analysis models L Wang, X Fang, A Subramaniyan, G Jothiprasad, M Gardner, A Kale, ... Turbo Expo: Power for Land, Sea, and Air 54662, 747-758, 2011 | 27 | 2011 |
| The effect of grid resolution and reaction models in simulation of a fluidized bed gasifier through nonintrusive uncertainty quantification techniques M Shahnam, A Gel, JF Dietiker, AK Subramaniyan, J Musser Journal of Verification, Validation and Uncertainty Quantification 1 (4), 041004, 2016 | 23 | 2016 |
| Effect of nanoclay on compressive strength of glass fiber composites AK Subramaniyan, Q Bing, D Nakima, CT Sun CD Proceedings of the 18th Annual Technical Conference of American Society …, 2003 | 23 | 2003 |
| Nonintrusive uncertainty quantification of computational fluid dynamics simulations of a bench-scale fluidized-bed gasifier A Gel, M Shahnam, J Musser, AK Subramaniyan, JF Dietiker Industrial & Engineering Chemistry Research 55 (48), 12477-12490, 2016 | 22 | 2016 |
| Engineering molecular mechanics: an efficient static high temperature molecular simulation technique AK Subramaniyan, CT Sun Nanotechnology 19 (28), 285706, 2008 | 21 | 2008 |
| 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 |
| Enhancing high-dimensional physics models for accurate predictions with bayesian calibration AK Subramaniyan, NC Kumar, L Wang, D Beeson, G Wiggs Propulsion-Safety and Affordable Readiness Conference, March, 2012 | 14 | 2012 |
| Analytical global sensitivity analysis with Gaussian processes A Srivastava, AK Subramaniyan, L Wang AI EDAM 31 (3), 235-250, 2017 | 13 | 2017 |
| Quantifying uncertainty of a reacting multiphase flow in a bench-scale fluidized bed gasifier: A Bayesian approach A Gel, M Shahnam, AK Subramaniyan Powder Technology 311, 484-495, 2017 | 13 | 2017 |
| Hybrid bayesian solution to NASA langley research center multidisciplinary uncertainty quantification challenge A Srivastava, AK Subramaniyan, L Wang Journal of Aerospace Information Systems 12 (1), 114-139, 2015 | 13 | 2015 |
