Fast prediction of temperature and chemical species distributions in pulverized coal boiler using POD reduced-order modeling for CFD
X Chen, W Zhong, T Li - Energy, 2023 - Elsevier
This study aims to develop a fast prediction method of 3D temperature and chemical species
distributions in pulverized coal boilers for real-time combustion monitoring and optimization …
distributions in pulverized coal boilers for real-time combustion monitoring and optimization …
Digital twins based on bidirectional LSTM and GAN for modelling the COVID-19 pandemic
The outbreak of the coronavirus disease 2019 (COVID-19) has now spread throughout the
globe infecting over 150 million people and causing the death of over 3.2 million people …
globe infecting over 150 million people and causing the death of over 3.2 million people …
Feasibility analysis of a POD-based reduced order model with application in Eulerian–Lagrangian simulations
G Duan, S Li, M Sakai - Industrial & Engineering Chemistry …, 2023 - ACS Publications
Computational fluid dynamics coupled with the discrete element method (CFD-DEM) is
widely employed for simulating multiphase flows involving particles, but the heavy …
widely employed for simulating multiphase flows involving particles, but the heavy …
Research, Application and Future Prospect of Mode Decomposition in Fluid Mechanics
In fluid mechanics, modal decomposition, deeply intertwined with the concept of symmetry,
is an essential data analysis method. It facilitates the segmentation of parameters such as …
is an essential data analysis method. It facilitates the segmentation of parameters such as …
Modeling transient flow dynamics around a bluff body using deep learning techniques
The significance of understanding the flow past a bluff body (BB) lies in its relevance to
ocean, structural, and environmental applications. Capturing the transient flow behaviors …
ocean, structural, and environmental applications. Capturing the transient flow behaviors …
[HTML][HTML] Proper orthogonal decomposition and physical field reconstruction with artificial neural networks (ANN) for supercritical flow problems
The development of mathematical models, and the associated numerical simulations, are
challenging in higher-dimensional systems featuring flows of supercritical fluids in various …
challenging in higher-dimensional systems featuring flows of supercritical fluids in various …
Numerical Assessment of a Nonintrusive Surrogate Model Based on Recurrent Neural Networks and Proper Orthogonal Decomposition: Rayleigh–Bénard Convection
Recent developments in diagnostic and computing technologies offer to leverage numerous
forms of nonintrusive modelling approaches from data where machine learning can be used …
forms of nonintrusive modelling approaches from data where machine learning can be used …
Numerical Study of Flow Field and Mixing Performance of a New Curved-Sheet Blade-Folded Static Mixer
Y Qiao, L Zheng, K Guo, H Liu, B Zhang… - Industrial & …, 2024 - ACS Publications
Mixing is an important unit of operation in the process industry. A static mixer is a device
commonly used for liquid mixing in a pipe or channel. This study proposes a new curved …
commonly used for liquid mixing in a pipe or channel. This study proposes a new curved …
On Fostering Predictions in Data-Driven Reduced Order Model for Eulerian–Lagrangian Simulations: Decision of Sufficient Training Data
The development of a data-driven surrogate model (SM) is extensively studied in Eulerian–
Lagrangian simulations for its advantage of high computational speed. However, in the …
Lagrangian simulations for its advantage of high computational speed. However, in the …
Parameter optimization of the bio-inspired robot propulsion through the deep learning based reduced order fluid-structure interaction model
Z Ying, L Wang, R Melnik - Ocean Engineering, 2022 - Elsevier
In this paper, an effective model (POD-NIROM) is proposed, which makes full use of Long
short-term memory Neural Network (LSTM NN) and proper orthogonal decomposition (POD) …
short-term memory Neural Network (LSTM NN) and proper orthogonal decomposition (POD) …