Advanced progress of numerical simulation in drum drying process: Gas–solid flow model and simulation of flow characteristics

M Kang, J Bian, B Li, X Fan, Y Xi, Y Wang, Y Liu… - … Communications in Heat …, 2024 - Elsevier
Numerical simulation, also known as computer simulation, uses an electronic computer to
investigate and solve engineering problems, physical problems, and a wide range of other …

Two-dimensional particle shapes modelling for DEM simulations in engineering: A review

J Kafashan, J Wiącek, N Abd Rahman, J Gan - Granular Matter, 2019 - Springer
Abstract The Discrete Element Method/Modelling (DEM) is a well-elaborated method for
modelling the dynamical behaviour of particulate systems. The term “DEM” refers to a family …

Optimization of the aero-engine thermal management system with intermediate cycle based on heat current method

J Liu, M Li, TY Zhang, Y Wang, Z Cao, W Shao… - Applied Thermal …, 2024 - Elsevier
Reliability and efficiency of the aero-engine thermal management system (ATMS) is of great
importance to ensure the required working condition. Conventional methods on modeling …

Prediction of random packing density and flowability for non-spherical particles by deep convolutional neural networks and Discrete Element Method simulations

R Hesse, F Krull, S Antonyuk - Powder Technology, 2021 - Elsevier
Non-spherical particles can be found in many industrial processes. Unfortunately, scalar
shape parameters are often insufficient to predict their complex behavior. Therefore, this …

[HTML][HTML] Erosive wear and particle attrition in multi-stage solar particle receivers and screw conveyors: A CFD-DEM approach with machine learning and artificial …

STW Kuruneru, JS Kim - Chemical Engineering Science, 2024 - Elsevier
A coupled finite volume and discrete element method (CFD-DEM) numerical model is
developed to unravel the fundamental mechanisms of granular transport, surface erosive …

Prediction of particle mixing in rotary drums by a DEM data-driven PSO-SVR model

W Wu, K Chen, E Tsotsas - Powder Technology, 2024 - Elsevier
Particle mixing in rotary drums is of significant industrial importance, but very complex.
Detailed simulation can be achieved using the discrete element method (DEM), but the …

Nuclear accident source term estimation using kernel principal component analysis, particle swarm optimization, and backpropagation neural networks

Y Ling, Q Yue, C Chai, Q Shan, D Hei, W Jia - Annals of Nuclear Energy, 2020 - Elsevier
Rapid estimation of the release rate of source items after a nuclear accident is very important
for nuclear emergency and decision making. A source term estimation method, based on the …

Image-based prediction of granular flow behaviors in a wedge-shaped hopper by combing DEM and deep learning methods

Z Liao, Y Yang, C Sun, R Wu, Z Duan, Y Wang, X Li… - Powder Technology, 2021 - Elsevier
Granular flow has solid-, liquid-, or even gas-like behaviors, which can be described through
discrete element method (DEM)-based simulations. Although the DEM simulation has …

[HTML][HTML] Prediction of the remaining time and time interval of pebbles in pebble bed HTGRs aided by CNN via DEM datasets

M Wu, X Liu, N Gui, X Yang, J Tu, S Jiang… - Nuclear Engineering and …, 2023 - Elsevier
Prediction of the time-related traits of pebble flow inside pebble-bed HTGRs is of great
significance for reactor operation and design. In this work, an image-driven approach with …

Calibration of Small-Grain Seed Parameters Based on a BP Neural Network: A Case Study with Red Clover Seeds

X Ma, M Guo, X Tong, Z Hou, H Liu, H Ren - Agronomy, 2023 - mdpi.com
In order to enhance the accuracy of discrete element numerical simulations in the
processing of small-seed particles, it is essential to calibrate the parameters of seeds within …