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Cited by
All
Since 2019
Citations
31
31
h-index
2
2
i10-index
2
2
0
12
6
2021
2022
2023
2024
3
6
11
11
Public access
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2 articles
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Co-authors
Sayan Ghosh
Senior Engineer at GE Aerospace Research
Verified email at ge.com
Steven Atkinson
Amazon
Verified email at atkinson.mn
Piyush Pandita
Staff Engineer, GE Aerospace
Verified email at ge.com
Valeria Andreoli
Aerodynamics Engineer, GE Research
Verified email at ge.com
Nicholas Zabaras
Professor, Cornell University
Verified email at nd.edu
Xu Han
AIAA
Verified email at wustl.edu
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Cheng Peng
University of Notre Dame
, Applied Mathematics and Computational Statistics
Verified email at nd.edu -
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Deep learning
Bayesian Neural Network
Uncertainty Quantification
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Year
Inverse aerodynamic design of gas turbine blades using probabilistic machine learning
S Ghosh, G Anantha Padmanabha, C Peng, V Andreoli, S Atkinson, ...
Journal of Mechanical Design 144 (2), 021706
, 2022
19
2022
Pro-ML IDeAS: A probabilistic framework for explicit inverse design using invertible neural network
S Ghosh, GA Padmanabha, C Peng, S Atkinson, V Andreoli, P Pandita, ...
AIAA Scitech 2021 Forum, 0465
, 2021
11
2021
Development of a One-Equation Turbulence Model Based on k-ϵ Closure and its Extension for Computing Transitional Flows by Including an Intermittency Transport Equation
C Peng
1
2019
A Probabilistic Machine Learning Framework for Explicit Inverse Design of Industrial Gas Turbine Blades
S Ghosh, V Andreoli, GA Padmanabha, C Peng, S Atkinson, P Pandita, ...
Turbo Expo: Power for Land, Sea, and Air 85031, V09BT27A003
, 2021
2021
Development of a Transition Model Based on One-Equation k-ϵ Closure
C Peng, RK Agarwal
AIAA Aviation 2019 Forum, 3324
, 2019
2019
A New One Equation Turbulence Model Based on k-ϵ Closure with Elliptic Blending
C Peng, X Han, RK Agarwal
AIAA Scitech 2019 Forum, 1880
, 2019
2019
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