Year |
Citation |
Score |
2017 |
Gel A, Shahnam M, Subramaniyan AK. Quantifying uncertainty of a reacting multiphase flow in a bench-scale fluidized bed gasifier: A Bayesian approach Powder Technology. 311: 484-495. DOI: 10.1016/J.Powtec.2017.01.034 |
0.336 |
|
2017 |
Ananthasayanam B, Loghin A, Subramaniyan AK. An efficient framework for rapid life assessment in industrial applications: Fatigue crack growth Engineering Fracture Mechanics. 181: 7-28. DOI: 10.1016/J.Engfracmech.2017.06.016 |
0.321 |
|
2016 |
Gel A, Shahnam M, Musser J, Subramaniyan AK, Dietiker J. Nonintrusive Uncertainty Quantification of Computational Fluid Dynamics Simulations of a Bench-Scale Fluidized-Bed Gasifier Industrial & Engineering Chemistry Research. 55: 12477-12490. DOI: 10.1021/Acs.Iecr.6B02506 |
0.347 |
|
2016 |
Loghin A, Ananthasayanam B, LeMonds J, Subramaniyan A, Viana F. Fatigue Crack Growth Life Assessment for Industrial Applications using Re-meshing and Bayesian Hybrid Techniques Procedia Structural Integrity. 2: 2487-2494. DOI: 10.1016/J.Prostr.2016.06.311 |
0.307 |
|
2015 |
Srivastava A, Subramaniyan AK, Wang L. Hybrid Bayesian solution to NASA Langley Research Center multidisciplinary uncertainty quantification challenge Journal of Aerospace Information Systems. 12: 114-139. DOI: 10.2514/1.I010266 |
0.306 |
|
2010 |
Subramaniyan AK, Sun CT. Temperature dependent effective embedded atom method potential for steady state high temperature applications Journal of Computational and Theoretical Nanoscience. 7: 176-181. DOI: 10.1166/Jctn.2010.1343 |
0.31 |
|
2009 |
Subramaniyan AK, Sun CT. Nanoscale design of Ni-Al shape memory alloys. Nanotechnology. 20: 085703. PMID 19417464 DOI: 10.1088/0957-4484/20/8/085703 |
0.431 |
|
2008 |
Subramaniyan AK, Sun CT. Engineering molecular mechanics: an efficient static high temperature molecular simulation technique. Nanotechnology. 19: 285706. PMID 21828740 DOI: 10.1088/0957-4484/19/28/285706 |
0.461 |
|
Low-probability matches (unlikely to be authored by this person) |
2016 |
Zhang G, Le Q, Loghin A, Subramaniyan A, Bobaru F. Validation of a peridynamic model for fatigue cracking Engineering Fracture Mechanics. 162: 76-94. DOI: 10.1016/J.Engfracmech.2016.05.008 |
0.296 |
|
2008 |
Subramaniyan AK, Sun CT. Continuum interpretation of virial stress in molecular simulations International Journal of Solids and Structures. 45: 4340-4346. DOI: 10.1016/J.Ijsolstr.2008.03.016 |
0.294 |
|
2017 |
Srivastava A, Subramaniyan AK, Wang L. Analytical global sensitivity analysis with Gaussian processes Artificial Intelligence For Engineering Design, Analysis and Manufacturing. 31: 235-250. DOI: 10.1017/S0890060417000142 |
0.287 |
|
2007 |
Subramaniyan AK, Sun CT. Toughening polymeric composites using nanoclay: Crack tip scale effects on fracture toughness Composites Part a: Applied Science and Manufacturing. 38: 34-43. DOI: 10.1016/J.Compositesa.2006.01.021 |
0.282 |
|
2017 |
Biyik E, D'Amato FJ, Subramaniyan A, Sun C. A Reduced Order Modeling Methodology for Steam Turbine Clearance Control Design Journal of Engineering For Gas Turbines and Power-Transactions of the Asme. 139: 92604. DOI: 10.1115/1.4036062 |
0.273 |
|
2014 |
Subramaniyan AK, Kumar NC, Wang L. Probabilistic validation of complex engineering simulations with sparse data Proceedings of the Asme Turbo Expo. 7. DOI: 10.1115/GT2014-26257 |
0.252 |
|
2006 |
Subramaniyan AK, Sun CT. Enhancing compressive strength of unidirectional polymeric composites using nanoclay Composites Part a: Applied Science and Manufacturing. 37: 2257-2268. DOI: 10.1016/J.Compositesa.2005.12.027 |
0.225 |
|
2008 |
Subramaniyan AK, Sun CT. Interlaminar fracture behavior of nanoclay reinforced glass fiber composites Journal of Composite Materials. 42: 2111-2122. DOI: 10.1177/0021998308094550 |
0.21 |
|
2013 |
Kumar NC, Subramaniyan AK, Wang L, Wiggs G. Calibrating transient models with multiple responses using bayesian inverse techniques Proceedings of the Asme Turbo Expo. 7. DOI: 10.1115/GT2013-95857 |
0.199 |
|
2016 |
Shahnam M, Gel A, Dietiker J, Subramaniyan AK, Musser J. The Effect of Grid Resolution and Reaction Models in Simulation of a Fluidized Bed Gasifier Through Nonintrusive Uncertainty Quantification Techniques Journal of Verification, Validation and Uncertainty Quantification. 1. DOI: 10.1115/1.4035445 |
0.191 |
|
2015 |
Srivastava A, Subramaniyan AK, Wang L. Variance based global sensitivity analysis for uncorrelated and correlated inputs with Gaussian processes Proceedings of the Asme Turbo Expo. 7. DOI: 10.1115/GT2015-43693 |
0.186 |
|
2012 |
Ravishankar B, Singh G, Wang L, Subramaniyan AK. Probabilistic validation metrics for industrial engineering analysis models Collection of Technical Papers - Aiaa/Asme/Asce/Ahs/Asc Structures, Structural Dynamics and Materials Conference. |
0.177 |
|
2011 |
Subramaniyan AK, Wang L, Beeson D, Nelson J, Berg R, Cepress R. A comparative study on accuracy and efficiency of metamodels for large industrial datasets Proceedings of the Asme Turbo Expo. 6: 759-769. DOI: 10.1115/GT2011-46610 |
0.169 |
|
2010 |
Wang L, Subramaniyan AK, Beeson D. Efficient probabilistic analysis and design optimization using data classification decision boundaries Asme International Mechanical Engineering Congress and Exposition, Proceedings (Imece). 11: 161-172. DOI: 10.1115/IMECE2010-39921 |
0.16 |
|
2011 |
Wang L, Fang X, Subramaniyan A, Jothiprasad G, Gardner M, Kale A, Akkaram S, Beeson D, Wiggs G, Nelson J. Challenges in uncertainty, calibration, validation and predictability of engineering analysis models Proceedings of the Asme Turbo Expo. 6: 747-758. DOI: 10.1115/GT2011-46554 |
0.146 |
|
2012 |
Kumar NC, Subramaniyan AK, Wang L. Improving high-dimensional physics models through bayesian calibration with uncertain data Proceedings of the Asme Turbo Expo. 7: 407-416. DOI: 10.1115/GT2012-69058 |
0.14 |
|
2021 |
Mc Cartney AM, Mahmoud M, Jochum M, Agustinho DP, Zorman B, Al Khleifat A, Dabbaghie F, K Kesharwani R, Smolka M, Dawood M, Albin D, Aliyev E, Almabrazi H, Arslan A, Balaji A, ... ... Subramaniyan A, et al. An international virtual hackathon to build tools for the analysis of structural variants within species ranging from coronaviruses to vertebrates. F1000research. 10: 246. PMID 34621504 DOI: 10.12688/f1000research.51477.1 |
0.104 |
|
2014 |
Srivastava A, Subramaniyan AK, Wang L. A hybrid bayesian solution to NASA langley multidisciplinary uncertainty quantification challenge 16th Aiaa Non-Deterministic Approaches Conference. |
0.067 |
|
2012 |
Singh G, Viana FAC, Subramaniyan AK, Wang L, DeCesare DG, Khan GKMK, Wiggs G. Multimodal particle swarm optimization: Enhancements and applications 12th Aiaa Aviation Technology, Integration and Operations (Atio) Conference and 14th Aiaa/Issmo Multidisciplinary Analysis and Optimization Conference. |
0.062 |
|
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