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Pranay Seshadri
Pranay Seshadri
未知所在单位机构
在 cantab.ac.uk 的电子邮件经过验证
标题
引用次数
引用次数
年份
Effectively subsampled quadratures for least squares polynomial approximations
P Seshadri, A Narayan, S Mahadevan
SIAM/ASA Journal on Uncertainty Quantification 5 (1), 1003-1023, 2017
67*2017
Leakage Uncertainties in Compressors: The Case of Rotor 37
P Seshadri, GT Parks, S Shahpar
AIAA Journal of Propulsion and Power 31 (1), 2015
622015
Turbomachinery active subspace performance maps
P Seshadri, S Shahpar, P Constantine, G Parks, M Adams
Journal of Turbomachinery 140 (4), 041003, 2018
602018
Robust compressor blades for desensitizing operational tip clearance variations
P Seshadri, S Shahpar, GT Parks
Turbo Expo: Power for Land, Sea, and Air 45608, V02AT37A043, 2014
542014
AeroVR: An immersive visualisation system for aerospace design and digital twinning in virtual reality
SK Tadeja, P Seshadri, PO Kristensson
The Aeronautical Journal 124 (1280), 1615-1635, 2020
502020
Numerical evaluation of entropy generation in isolated airfoils and Wells turbines
T Ghisu, F Cambuli, P Puddu, N Mandas, P Seshadri, GT Parks
Meccanica 53, 3437-3456, 2018
472018
A density-matching approach for optimization under uncertainty
P Seshadri, P Constantine, G Iaccarino, G Parks
Computer Methods in Applied Mechanics and Engineering, 2016
41*2016
Dimension reduction via gaussian ridge functions
P Seshadri, S Yuchi, GT Parks
SIAM/ASA Journal on Uncertainty Quantification 7 (4), 1301-1322, 2019
332019
Effective-Quadratures (EQ): Polynomials for Computational Engineering Studies
P Seshadri, G Parks
The Journal of Open Source Software 2 (11), 2017
302017
Understanding micro air vehicle flapping-wing aerodynamics using force and flowfield measurements
P Seshadri, M Benedict, I Chopra
Journal of Aircraft 50 (4), 1070-1087, 2013
292013
Discovering a one-dimensional active subspace to quantify multidisciplinary uncertainty in satellite system design
X Hu, GT Parks, X Chen, P Seshadri
Advances in space research 57 (5), 1268-1279, 2016
252016
Sensitivity Analysis of a Coupled Hydrodynamic-Vegetation Model Using the Effectively Subsampled Quadratures Method
TS Kalra, A Aretxabaleta, P Seshadri, NK Ganju, A Beudin
Geosci. Model Dev., 2017
232017
Digital twin assessments in virtual reality: An explorational study with aeroengines
SK Tadeja, Y Lu, P Seshadri, PO Kristensson
2020 IEEE aerospace conference, 1-13, 2020
202020
Automatic borescope damage assessments for gas turbine blades via deep learning
CY Wong, P Seshadri, GT Parks
AIAA Scitech 2021 Forum, 1488, 2021
172021
Bayesian Assessments of Aeroengine Performance with Transfer Learning
P Seshadri, AB Duncan, G Thorne, G Parks, RV Dıaz, M Girolami
Data-Centric Engineering 3 (E29), 2022
152022
Uncertainty quantification for data-driven turbulence modelling with Mondrian forests
A Scillitoe, P Seshadri, M Girolami
Journal of Computational Physics 430, 110116, 2021
152021
Spatial flow-field approximation using few thermodynamic measurements—Part I: Formulation and area averaging
P Seshadri, D Simpson, G Thorne, A Duncan, G Parks
Journal of Turbomachinery 142 (2), 021006, 2020
152020
Gradient-enhanced least-square polynomial chaos expansions for uncertainty quantification and robust optimization
T Ghisu, DI Lopez, P Seshadri, S Shahpar
AIAA AVIATION 2021 FORUM, 3073, 2021
142021
Discussion on “Performance analysis of Wells turbine blades using the entropy generation minimization method” by Shehata, AS, Saqr, KM, Xiao, Q., Shahadeh, MF and Day, A.
T Ghisu, P Puddu, F Cambuli, N Mandas, P Seshadri, GT Parks
Renewable Energy 118, 386-392, 2018
142018
Extremum sensitivity analysis with polynomial Monte Carlo filtering
CY Wong, P Seshadri, G Parks
Reliability Engineering & System Safety 212, 107609, 2021
13*2021
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