Physics-informed deep learning for modelling particle aggregation and breakage processes

Hidden fluid mechanics: Learning velocity and pressure fields from flow visualizations

(2020) Maziar Raissi et al.   SCIENCE

A DEM-PBM multiscale coupling approach for the prediction of an impact pin mill

(2020) Xizhong Chen et al.   POWDER TECHNOLOGY

Numerical Methods for the Solution of Population Balance Equations Coupled with Computational Fluid Dynamics

(2020) Mohsen Shiea et al.   Annual Review of Chemical and Biomolecular Engineering

AI Feynman: A physics-inspired method for symbolic regression

(2020) Silviu-Marian Udrescu et al.   Science Advances

Scale-up procedure of parameter estimation in selection and breakage functions for impact pin milling

(2020) Zhipeng Li et al.   ADVANCED POWDER TECHNOLOGY

A meshless Radial Basis Method (RBM) for solving the detailed population balance equation

(2020) Samer Alzyod et al.   CHEMICAL ENGINEERING SCIENCE

Quantifying total uncertainty in physics-informed neural networks for solving forward and inverse stochastic problems

(2019) Dongkun Zhang et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Learning data-driven discretizations for partial differential equations

(2019) Yohai Bar-Sinai et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Surrogate modeling for fluid flows based on physics-constrained deep learning without simulation data

(2019) Luning Sun et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

Hidden physics models: Machine learning of nonlinear partial differential equations

(2018) Maziar Raissi et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Solving high-dimensional partial differential equations using deep learning

(2018) Jiequn Han et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations

(2018) M. Raissi et al.   JOURNAL OF COMPUTATIONAL PHYSICS

Meta-modeling game for deriving theory-consistent, microstructure-based traction–separation laws via deep reinforcement learning

(2018) Kun Wang et al.   COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING

A compartmental CFD-PBM model of high shear wet granulation

(2016) Xi Yu et al.   AICHE JOURNAL

Simulation of droplet breakage in turbulent liquid–liquid dispersions with CFD-PBM: Comparison of breakage kernels

(2016) Zhengming Gao et al.   CHEMICAL ENGINEERING SCIENCE

Discovering governing equations from data by sparse identification of nonlinear dynamical systems

(2016) Steven L. Brunton et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Determination of the milling parameters of a platinum group minerals ore to optimize product size distribution for flotation purposes

(2012) Ngonidzashe Chimwani et al.   MINERALS ENGINEERING

Three-dimensional CFD-PBM coupled model of the temperature fields in fluidized-bed polymerization reactors

(2011) Xi-Zhong Chen et al.   AICHE JOURNAL