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 …

[HTML][HTML] Deep neural network-based heat radiation modelling between particles and between walls and particles

J Tausendschön, S Radl - International Journal of Heat and Mass Transfer, 2021 - Elsevier
Abstract We present a Deep Neural Network (DNN)-based view factor model to calculate
radiative heat transfer rates between particles, as well as between particles and walls in …

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 …

Mass flow rate prediction of screw conveyor using artificial neural network method

E Kalay, ME Boğoçlu, B Bolat - Powder Technology, 2022 - Elsevier
Screw conveyors are widely used in granular transportation to provide an efficient and
steady flow rate. DEM is a numerical method used to predict flow behaviors of granular …

[HTML][HTML] Machine Learning for heat radiation modeling of bi-and polydisperse particle systems including walls

J Tausendschön, G Stöckl, S Radl - Particuology, 2023 - Elsevier
We investigated the ability of four popular Machine Learning methods ie, Deep Neural
Networks (DNNs), Random Forest-based regressors (RFRs), Extreme Gradient Boosting …

Calculating the view factor of randomly dispersed multi-sized particles using hybrid GRU-LSTM recurrent neural networks regression

A Kianimoqadam, J Lapp - International Journal of Heat and Mass Transfer, 2023 - Elsevier
This study presents three novel methods for the computational acceleration of simulations of
high temperature radiative heat transfer in particulate media. The paper presents a novel …

Radiative view factor correlations in particulate media from ray tracing simulations and data-driven modeling

Z Chen, RB Chandran - International Journal of Heat and Mass Transfer, 2023 - Elsevier
Thermal radiation has been extensively modeled in static particulate media with effective
radiative properties or with statistical ray tracing techniques. However, these techniques are …

Deep learning-based prediction of the remaining time and future distribution of pebble flow from real-scene images

M Wu, L Bin, N Gui, X Yang, J Tu, S Jiang - Chemical Engineering Science, 2024 - Elsevier
Pebble flow dynamics is a crucial issue for designing and operating pebble bed reactors.
The existing experimental or simulation methods are often associated with high time …