6 citations · 6 across the 2 of their papers we have counts for
3 papers
GIMLET: Generalizable and Interpretable Model Learning through Embedded Thermodynamics
Suguru Shiratori, Elham Kiyani, Khemraj Shukla +1
We develop a data-driven framework for discovering constitutive relations in models of fluid flow and scalar transport. Under the assumption that velocity and/or scalar fields are…
Surrogate models for the magnitude of convection in droplets levitated through EML, ADL, and ESL methods
Takuro Usui, Suguru Shiratori, Kohei Tanimoto +5
Fluid flow and heat transfer in levitated droplets were numerically investigated. Three levitation methods: electro-magnetic levitation (EML), aerodynamic levitation (ADL), and ele…
Physics-informed neural network applied to surface-tension-driven liquid film flows
Yo Nakamura, Suguru Shiratori, Ryota Takagi +4
A physics-informed neural network (PINN), which has been recently proposed by Raissi et al [J. Comp. Phys. 378, pp. 686-707 (2019)], is applied to the partial differential equation…