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

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

18 July 2023
Elham Kiyani
M. Kooshkbaghi
K. Shukla
R. Koneru
Zhen Li
L. Bravo
A. Ghoshal
George Karniadakis
M. Karttunen
    AI4CE
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Papers citing "Characterization of partial wetting by CMAS droplets using multiphase many-body dissipative particle dynamics and data-driven discovery based on PINNs"

3 / 3 papers shown
Title
A toolkit for data-driven discovery of governing equations in high-noise
  regimes
A toolkit for data-driven discovery of governing equations in high-noise regimes
Charles B. Delahunt
J. Nathan Kutz
30
18
0
08 Nov 2021
B-PINNs: Bayesian Physics-Informed Neural Networks for Forward and
  Inverse PDE Problems with Noisy Data
B-PINNs: Bayesian Physics-Informed Neural Networks for Forward and Inverse PDE Problems with Noisy Data
Liu Yang
Xuhui Meng
George Karniadakis
PINN
170
755
0
13 Mar 2020
MCMC using Hamiltonian dynamics
MCMC using Hamiltonian dynamics
Radford M. Neal
132
3,260
0
09 Jun 2012
1