Data-driven modeling methods and techniques for pharmaceutical processes
Y Dong, T Yang, Y Xing, J Du, Q Meng - Processes, 2023 - mdpi.com
As one of the most influential industries in public health and the global economy, the
pharmaceutical industry is facing multiple challenges in drug research, development and …
pharmaceutical industry is facing multiple challenges in drug research, development and …
[HTML][HTML] Recovery mechanisms and formation influencing factors of miscible CO2 huff-n-puff processes in shale oil reservoirs: A systematic review
Y Wan, C Jia, W Lv, N Jia, L Jiang… - Advances in Geo-Energy …, 2024 - yandy-ager.com
Shale oil production is vital for meeting the rising global energy demand, while primary
recovery rates are poor due to the ultralow permeability. CO2 huff-n-puff can boost yields by …
recovery rates are poor due to the ultralow permeability. CO2 huff-n-puff can boost yields by …
Materials processing model-driven discovery framework for porous materials using machine learning and genetic algorithm: A focus on optimization of permeability …
T Yasuda, S Ookawara, S Yoshikawa… - Chemical Engineering …, 2023 - Elsevier
This study proposes a material discovery framework for porous materials to identify design
variable recipes and the corresponding material structures that can be utilized to improve …
variable recipes and the corresponding material structures that can be utilized to improve …
Intensification of catalytic reactors: a synergic effort of multiscale modeling, machine learning and additive manufacturing
M Bracconi - Chemical Engineering and Processing-Process …, 2022 - Elsevier
The intensification of catalytic reactors is expected to play a crucial role to address the
challenges that the chemical industry is facing in the transition to more sustainable …
challenges that the chemical industry is facing in the transition to more sustainable …
Modeling the 4D discharge of lithium-ion batteries with a multiscale time-dependent deep learning framework
The lithium-ion battery (LIB) field is moving towards the direction of investigating spatially
resolved physical phenomena in the 3D porous microstructure of electrodes. These pore …
resolved physical phenomena in the 3D porous microstructure of electrodes. These pore …
From computational fluid dynamics to structure interpretation via neural networks: an application to flow and transport in porous media
The modeling of flow and transport in porous media is of the utmost importance in many
chemical engineering applications, including catalytic reactors, batteries, and CO2 storage …
chemical engineering applications, including catalytic reactors, batteries, and CO2 storage …
[HTML][HTML] Prediction of local concentration fields in porous media with chemical reaction using a multi scale convolutional neural network
The study of solute transport in porous media is of interest in many chemical engineering
systems. Some example applications include packed bed catalytic reactors, filtration …
systems. Some example applications include packed bed catalytic reactors, filtration …
Hierarchical homogenization with deep‐learning‐based surrogate model for rapid estimation of effective permeability from digital rocks
Effective permeability is a key physical property of porous media that defines its ability to
transport fluid. Digital rock physics (DRP) combines modern tomographic imaging …
transport fluid. Digital rock physics (DRP) combines modern tomographic imaging …
[HTML][HTML] Adaptive weighting of Bayesian physics informed neural networks for multitask and multiscale forward and inverse problems
In this paper, we present a novel methodology for automatic adaptive weighting of Bayesian
Physics-Informed Neural Networks (BPINNs), and we demonstrate that this makes it …
Physics-Informed Neural Networks (BPINNs), and we demonstrate that this makes it …
A 3D reconstruction method of porous media based on improved WGAN-GP
T Zhang, Q Liu, X Wang, X Ji, Y Du - Computers & Geosciences, 2022 - Elsevier
The reconstruction of porous media is important to the development of petroleum industry,
but the accurate characterization of the internal structures of porous media is difficult since …
but the accurate characterization of the internal structures of porous media is difficult since …