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Prediction of the Local Particle Velocity in the Spout Region of Cylindrical Spouted Beds Using an Artificial Neural Network | ||
| Chemical Process Design | ||
| مقالات آماده انتشار، پذیرفته شده، انتشار آنلاین از تاریخ 06 بهمن 1404 اصل مقاله (1.01 M) | ||
| نوع مقاله: Research Article | ||
| شناسه دیجیتال (DOI): 10.22111/cpd.2026.54525.1083 | ||
| نویسندگان | ||
| Agheel Muaid Ali؛ Seyyed Hossein Hosseini* ؛ Mohammadreza Valizadeh* | ||
| Department of Chemical Engineering, Ilam University, Ilam, 69315-516, Iran | ||
| چکیده | ||
| The local particle velocity is an important hydrodynamic parameter in the design and optimization of gas-solid systems, such as the spouted beds. Predicting the particle velocity in the spout region is often complex, and developing a simple and reliable method for estimating this parameter is both valuable and highly beneficial for engineers and system designers. In the present study, the intelligent predictive approach of a multi-layer perceptron neural network (MLP-NN) is used for the first time to investigate the feasibility of measuring the local particle velocity within the spout region of spouted beds. Accordingly, 224 measured data points are collected, covering a broad range of factors such as bed diameter, inlet diameter, static bed height, cone angle, minimum spouting velocity, and inlet gas velocity for Geldart D particles with varying densities and diameters. The data are then used for training, validating, and testing the intelligence-based model. The MLP-NN-based model shows a strong predictive capability for estimating particle velocity in the spouted bed, with an Average Absolute Relative Error (AARE) of 13.32%, an R2 value of 0.9842, and a Root Mean Squared Error (RMSE) of 0.033 for the test dataset. In addition, for all data, the model achieves an AARE of 6.30%, an RMSE of 0.0098, and an R2 value of 0.9942. Furthermore, in the present study, a sensitivity analysis is conducted on the data to determine the degree of influence of the input parameters on the target function. | ||
| کلیدواژهها | ||
| Hydrodynamics؛ Spouted beds؛ Particle velocity؛ Multilayer perceptron algorithm | ||
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آمار تعداد مشاهده مقاله: 44 تعداد دریافت فایل اصل مقاله: 40 |
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