Iranian Journal of Chemical Engineering (IJChE)

Abstract This research aims to study the mixing dynamics of granular materials in the Triaxe mixer and compare the effect of operating conditions on the quality of mixing. The discrete element method was used to simulate the mixer and track the motion of particles. The Johnson-Kendall-Robinson model was used for the simulation of the contact of cohesive particles. The results indicate that the most influential parameter on the mixing performance is the rotational speed since raising the rotational speed increases the transferred momentum to the grains. In the specific design of the mixer, the dead zones are reduced, so the fill-level does not have a considerable impact on the homogeneity. Also, the quality of mixing of large particles in this blender is better than the same for smaller particles. The mixer's performance for blending cohesive grains was similar to that for the non-cohesive particles. For both types of solids, the relative standard deviation reached approximately 35% after 70 s. Mixing performances of two sizes of the mixer were compared based on two criteria, the constant impeller speed and constant power per volume of the mixer. The results show that the case of the constant impeller speed can predict the mixing performance of the larger mixer more accurately.

Abstract This paper presents a machine learning-based approach for accurately predicting pyrolysis product yields. Methods such as Linear Regression (LR), K-Nearest Neighbors (KNN), Decision Tree (DT), Support Vector Regression (SVR), Random Forest (RF), and Neural Networks (NN) leverage operating conditions and/or ultimate/proximate analysis data, eliminating the need for reaction kinetics. This innovative approach offers a broader range and higher accuracy of feedstock compared to traditional kinetics-based methods. The KNN model demonstrated superior performance, achieving a correlation coefficient greater than 0.998 and an RMSE of 0.64. These findings provide valuable insights for engineers and practitioners, facilitating the efficient design and operation of pyrolysis units.The selectivity exhibited a notable increase from 2.46 to 5.27. This improvement in selectivity can primarily be attributed to the significantly higher increase in the solubility coefficient of CO₂ compared to that of CH₄.

Abstract The effect of adding isopropanol (ISP) to nitrogen as the fluidizing gas on the hydrodynamics of the fluidization of hydrophilic titanium nanoparticles was studied. It was shown by the pressure drop method that adding ISP reduces the minimum fluidization velocity. Wavelet transform of the pressure fluctuations of the bed was employed to identify the hydrodynamic structures. The energy of hydrodynamic structures was evaluated in each fluidization mode. It was shown that ISP reduces the inter-particle attractive forces by replacing the hydroxyl group of the hydrophilic nanoparticles with an alkyl group. Energy and recurrence analyses were used to define the characteristics of fluidization when adding ISP to nitrogen gas. The energy of macro structures increased when using ISP, having indicated a decrease in the number of bubbles and an increase in the bubble size due to the reduction of inter-particle attractive forces. The increase of the white local areas in the recurrence plots also showed the increase of the bubble size. The recurrence quantification analysis showed the increase of the larger-scale phenomena (i.e. bubbles) in the bed.

Abstract The attrition of 300 µm natural zeolite particles was studied in a laboratory scale draft tube spouted bed (DTSB) and spout-fluid bed (DTSFB). It has been shown that the attrition rate decreases with time and reaches to an almost constant value. The results show that the prevailing attrition mechanism under the conditions of this work is the surface abrasion which occurs due to the collisions between particles. It has been found that increasing the cone angle from 30º to 60º in the DTSB, causes a decrease in the extent of attrition. In addition, by increasing the spouting air velocity and the height of the entrainment zone in the DTSB, the extent of attrition increases due to a more energetic collision between particles as well as the increased circulation rate of solids. Increasing the auxiliary air velocity in the DTSFB increases the rate of attrition. A comparison between the attrition in the DTSB and DTSFB has been conducted and has indicated that applying the auxiliary air flow causes up to a 6 % increase in the extent of attrition. An empirical correlation is derived for evaluating the extent of the attrition in the DTSB and DTSFB. This empirical correlation is in good agreement with the experimental data.

Abstract A mathematical model is developed for describing the dynamic behavior of the gas phase ethylene polymerization reactor. The model is based on the dynamic two-phase concept of fluidization in which the bubbles may contain solid particles and the emulsion is capable of containing more gas than that of minimum fluidization. The fluidized bed reactor is divided into several serial sections consisting of bubble and emulsion phases. Flow of the gas is considered as plug flow through the bubbles and perfectly mixed through the emulsion phase. Polymerization reactions occur in both emulsion and bubble phases. Variation of the process variables as well as the polymer properties were studied as a function of operating time. The bed height was controlled by the product withdrawal rate with a PID controller. The results of the model were compared with the experimental data and a good agreement was observed between the model prediction and actual data. The simulation results indicate that a significant amount of polymer production (roughly 12%) takes place in the bubbles.