activity
20132024
most citedDeep neural operators can serve as accurate surrogates for shape optimization: A case study for airfoils

3 citations · 8 across the 7 of their papers we have counts for

collaborators

8 papers

physics.flu-dyn2024

Hypersonic Boundary Layer Transition and Heat Loading

Ahmad Peyvan, Luis Bravo, Anindya Ghoshal +2

Hypersonic boundary layer transition using high-order methods for direct numerical simulations (DNS) is largely unexplored, although a few references exist in the literature. Exper…

physics.flu-dyn2024

Deep operator learning-based surrogate models for aerothermodynamic analysis of AEDC hypersonic waverider

Khemraj Shukla, Jasmine Ratchford, Luis Bravo +4

Neural networks are universal approximators that traditionally have been used to learn a map between function inputs and outputs. However, recent research has demonstrated that dee…

physics.flu-dyn2023★ 2 cited

Characterization of partial wetting by CMAS droplets using multiphase many-body dissipative particle dynamics and data-driven discovery based on PINNs

Elham Kiyani, Mahdi Kooshkbaghi, Khemraj Shukla +6

The molten sand, a mixture of calcia, magnesia, alumina, and silicate, known as CMAS, is characterized by its high viscosity, density, and surface tension. The unique properties of…

physics.flu-dyn2023

Deposition of sand particles on a solid substrate in a high-temperature subsonic flow

Rahul Babu Koneru, Luis Bravo, Muthuvel Murugan +2

Ingestion of sand particles into gas turbine engines has been observed to cause damage to engine components and in some cases leads to catastrophic failure. One such mechanism resp…

physics.flu-dyn2023

Dynamic spreading and infiltration of a molten sand droplet on a porous surface

Rahul Babu Koneru, Garrett Foresman, Alison Flatau +5

Compared to smooth surfaces, droplet spreading on porous surfaces is more complex and has relevance in many engineering applications. In this work, we investigate the infiltration…

physics.flu-dyn2023★ 3 cited

Deep neural operators can serve as accurate surrogates for shape optimization: A case study for airfoils

Khemraj Shukla, Vivek Oommen, Ahmad Peyvan +5

Deep neural operators, such as DeepONets, have changed the paradigm in high-dimensional nonlinear regression from function regression to (differential) operator regression, paving…

cond-mat.soft2021★ 3 cited

Theory and simulation of electrokinetic fluctuations in electrolyte solutions at the mesoscale

Mingge Deng, Faisal Tushar, Luis Bravo +3

Electrolyte solutions play an important role in energy storage devices, whose performance highly relies on the electrokinetic processes at sub-micron scales.\ Although fluctuations…

cond-mat.mtrl-sci2013

Inherent Symmetry and Microstructure Ambiguity in Micromechanics

Kuang C. Liu, Anindya Ghoshal

The computational cost of micromechanics for heterogeneous materials can be reduced in certain cases where symmetric boundary conditions are applicable. We derived an eighth symmet…