E-LIB Suche - Ergebnisse für: Rao Vadlamani, Nagabhushana

1

Riblet Performance Beneath Transitional and Turbulent Bound..:

Malathi Ananth, Sivaramakrishnan ; Vaid, Aditya ; Rao Vadlamani, Nagabhushana...
AIAA Journal. , 2023

Link: https://doi.org/10.2514/..

2

Scalar and Directional Localized Artificial Diffusivity Met..:

, In: Advances in Theoretical and Applied Mechanics; Lecture Notes in Mechanical Engineering,

Kumar, Ritu Raj ; Vadlamani, Nagabhushana Rao - p. 91-101 , 2024

Link: https://doi.org/10.1007/..

3

Entropy damping and Bulk Viscosity based artificial compres..:

AbdulGafoor, C.P. ; Rajananda, Aman ; Shankar, Achu.
Computers & Fluids. 279 (2024) - p. 106328 , 2024

Link: https://doi.org/10.1016/..

4

Efficacy of line-based explicit and compact high-order fini..:

Savsani, Vizan ; Govindarajan, Bharath ; Vadlamani, Nagabhushana Rao
Computers & Fluids. 250 (2023) - p. 105700 , 2023

Link: https://doi.org/10.1016/..

5

Surface Roughness Effects on Cavity Flows:

Nampelly, Ganesh ; Malathi, Ananth Sivaramakrishnan ; Vaid, Aditya...
Flow, Turbulence and Combustion. 109 (2022) 4 - p. 1215-1239 , 2022

Link: https://doi.org/10.1007/..

6

On the use of high order central difference schemes for dif..:

Kakumani, Hemanth Chandra Vamsi ; Vadlamani, Nagabhushana Rao ; Tucker, Paul Gary
Computers & Fluids. 248 (2022) - p. 105666 , 2022

Link: https://doi.org/10.1016/..

7

Application of Machine Learning Techniques in Temperature F..:

, In: 2022 21st IEEE International Conference on Machine Learning and Applications (ICMLA),

Arasu, Adrin Issai ; Modani, Manish ; Vadlamani, Nagabhushana Rao - p. 513-518 , 2022

Link: https://doi.org/10.1109/..

8

Deep neural networks to correct sub-precision errors in CFD:

Haridas, Akash ; Vadlamani, Nagabhushana Rao ; Minamoto, Yuki
Applications in Energy and Combustion Science. 12 (2022) - p. 100081 , 2022

Link: https://doi.org/10.1016/..

9

Quasi 3D Nacelle Design to Simulate Crosswind Flows: Merits..:

Yeung, Alex ; Vadlamani, Nagabhushana Rao ; Hynes, Tom.
International Journal of Turbomachinery, Propulsion and Power. 4 (2019) 3 - p. 25 , 2019

Link: https://doi.org/10.3390/..

10

Hierarchical geometry modelling using the immersed boundary..:

Ma, Yunfei ; Cui, Jiahuan ; Vadlamani, Nagabhushana Rao.
Computer Methods in Applied Mechanics and Engineering. 355 (2019) - p. 323-348 , 2019

Link: https://doi.org/10.1016/..

11

Effect of Fan on Inlet Distortion: Mixed-Fidelity Approach:

Ma, Yunfei ; Cui, Jiahuan ; Vadlamani, Nagabhushana Rao.
AIAA Journal. 56 (2018) 6 - p. 2350-2360 , 2018

Link: https://doi.org/10.2514/..

12

Distributed Roughness Effects on Transitional and Turbulent..:

Vadlamani, Nagabhushana Rao ; Tucker, Paul G. ; Durbin, Paul
Flow, Turbulence and Combustion. 100 (2017) 3 - p. 627-649 , 2017

Link: https://doi.org/10.1007/..

13

Effect of Fan on Inlet distortion: A Mixed fidelity Approac:

Ma, Yunfei ; Cui, Jiahuan ; Rao Vadlamani, Nagabhushana.
hal-02369305. , 2017

Link: https://hal.archives-ouv..

14

Artificial Neural Networks and Guided Gene Expression Progr..:

Kurhade, Nachiketa Narayan ; Vadlamani, Nagabhushana Rao ; Haridas, Akash
http://arxiv.org/abs/2306.08294. , 2023

Link: http://arxiv.org/abs/230..

15

Deep neural networks to correct sub-precision errors in CFD:

Akash Haridas ; Nagabhushana Rao Vadlamani ; Yuki Minamoto
http://www.sciencedirect.com/science/article/pii/S2666352X22000243. , 2022

Link: https://doi.org/10.1016/..