A parametric study of the drying process of polypropylene particles in a pilot-scale fluidized bed dryer using Computational Fluid Dynamics
Graphical abstract
Introduction
A considerable range of industrial products in different sectors experience the drying process at some stages of their production. A wide range of industrial dryers for materials with different characteristics are introduced in the literature, including fluidized bed dryers (Hovmand, 1995), indirect dryers (Devahastin and Mujumdar, 2007), drum dryers (Tang et al., 2003), spray dryers (Baker and McKenzie, 2005), rotatory dryers (Baker, 1988), spouted bed dryers (Szafran et al., 2005), solar dryers (Pangavhane et al., 2002), freeze dryers (Tang et al., 2005), microwave (Manickavasagan et al., 2006), dielectric dryers (Schiffmann, 1995), infrared dryers (Sadin et al., 2014), pneumatic dryers (Korn, 2001), conveyor dryers (Hepbasli et al., 2010), superheated dryers (Mujumdar, 1995), and impingement dryers (Aust et al., 1997). To design an industrial dryer, an adequate understanding of the system such as chemical and physical reactions as well as properties and characteristics of materials are mandatory. Usually, these critical parameters are obtained from extensive experiments, usually from pilot plant scales and analyzed to optimize the design and process conditions for real industrial cases. Nevertheless, the aforementioned approach requires extensive trial and errors, manpower with high running costs and could impose health, safety and environmental risk.
Fluidized Bed Dryers (FBD) are in particular applied in different industries such as chemicals production, foodstuff, biomaterials, polymer production, and carbohydrates to dry powders and granular products. One of the most important advantages of these dryers is that in the process of drying, proper mixing occurs which improves the efficiency of drying. Another advantage is their thermal efficiency in comparison with other drying techniques, making them somewhat easier to control. Despite all the advantages, these dryers have high electrical power consumption and have limitations on particles size (100−2000 μm) (Mujumdar, 2006)
Polypropylene is one of the thermoplastic polymers that can be used in different industries, such as plastic manufacturing, textiles, and medical devices. To demonstrate its importance, it should be noted that this material is the world’s second-most widely produced synthetic plastic (Pubns, 1996). Polypropylene production is costly, and also a challenging process, which can be carried out with different procedures. Catalysts deactivation, finding appropriate mixing time, test designing to achieve the best mixing phenomenon, and finding the best operational conditions are among those challenges. Regardless of the method of production, one of the steps of most polypropylene processes is to deactivate catalyst residuals and strip out the dissolved monomer in the polymer using the steamer and dryer units, before they are transferred to the polymer powders silos. Nevertheless, it is widely accepted that the performance of the dryer unit has significant effects on the quality of the final products (Pasquini and Addeo, 2005; Pubns, 1996).
The effects of different operating conditions on fluid flow within a pilot-plant dryer should be extensively investigated before the manufacturing stage. Although a pilot-plant dryer can provide valuable information, some parameters cannot be obtained due to operational limitations. For example, different gas distributors cannot be readily examined using a pilot-plant dryer because it could be a costly process. To analyze different operating conditions, including high-temperature conditions and different velocity injection cases, it is necessary to stop the system and test all designed scenarios, which is not possible at an industrial unit. To overcome this challenge, modelling approaches can be implemented to simulate the drying process in a plant with a much lower cost in comparison with experiments.
Numerous studies have been devoted to investigating fluid flow within dryers primarily using Computational Fluid Dynamics (CFD) methods. An extensive review study was conducted by (Jamaleddine and Ray, 2010) to demonstrate the importance and popularity of CFD methods in drying industries. The Eulerian–Eulerian approach was implemented by (Antony and Shyamkumar, 2016) to simulate the drying of sand particles using fluidized bed dryers. The impacts of inlet air temperature on the efficiency of the dryer were investigated, and it was observed that increasing inlet temperature reduces the drying time. Mass and heat transfer in a spouted bed dryer was predicted by (Szafran and Kmiec, 2004) using CFD method. They observed a good agreement between their Eulerian–Eulerian simulation results and the experimental data. This agreement demonstrated the capability of the Eulerian–Eulerian approach to address this kind of problem. (Szafran et al., 2005) investigated fluid flow in a spouted-bed dryer with a draft tube. Their numerical solution captured the flow behavior of experimental data. (Wang et al., 2008) studied a complex air-solid flow within a batch fluidized bed dryer using mathematical modeling, CFD methods, and Electrical Capacitance Tomography (ECT) measurement. The results of these techniques were compared with the available experimental data, and an acceptable agreement was observed. They also presented an online process control system using CFD and ECT methods. The Eulerian–Lagrangian method was implemented by (Fries et al., 2011) to investigate fluid dynamics in a fluidized bed. The collision behavior was taken into consideration, and the effects of granulator configurations with different residence time were studied. Three-dimensional gas-solid flow in spouted beds was studied by (Zhonghua and Mujumdar, 2008) using the Eulerian–Eulerian approach. Flow instabilities and their reasons were investigated, and it was recommended that these analyses could provide valuable insight into the process design. (Khomwachirakul et al., 2016) combined CFD methods with the discrete element method (DEM) to simulate gas-solid flow within an impinging stream dryer. The results of this CFD-DEM method were compared with the conventional CFD method and experimental data. It was observed that there is a better agreement between CFD-DEM methods and experimental data because this method considers solid-solid interactions. Generally, CFD-DEM is a more complicated and costly approach that is at the moment suitable for in-depth study of simple configurations, while based on currently available computational power CFD is could be a better choice for large and complicated geometries with the multiphase flow. (Arastoopour et al., 2017) presented comprehensive study and reported that Kinetic Theory of Granular Flow (KTGF) could be adequate for simulating fluid-solid problems using Eulerian–Eulerian approach. A circulating fluidized bed (CFB) reacting loop was studied numerically using CFD methods considering gas-solid flow by (Ghadirian et al., 2019). KTGF was used to consider solid particles motion, where excellent agreement between the numerical simulations and experimental was observed. In addition to particle-fluid systems, Eulerian–Eulerian approach based on KTGF was also used for particle segregation in a rotating drum by (Huang and Kuo, 2018) and granulation process within a high shear mixer granulator by (Ng et al., 2009). A good agreement between experimental results and numerical simulations was observed. Overall, it can be concluded that Eulerian–Eulerian approach could adequately address solid-gas systems, where full Eulerian– Lagrangian approach would be costly and inefficient.
In this study, a three-dimensional pilot-plant fluidized bed dryer was investigated both experimentally and numerically. This research is an optimization study of a specific industrial drying plant working in a petrochemical unit. To the best of our knowledge, no previous work on this particular dryer has been reported, particularly on the simulation study of three-phase flow in the drying process of polymerization. A numerical simulation based on CFD was developed to investigate the effects of different operating conditions related to the injecting gas phase. First, the accuracy of this proposed numerical solution was verified by the experimental data obtained from a pilot-plant fluidized bed dryer. In the next step, the effects of initial temperature, initial moisture, the velocity of the injecting gas, and two different types of gas distributors were analyzed. These parameters are playing crucial roles, and significantly affect the efficiency of a dryer plant. The combination of this numerical simulation with the experimental pilot plant data can be used to design and optimize an industrial dryer plant.
Section snippets
Methodology
In this study, a three-dimensional numerical scheme using CFD method was developed to analyze multiphase flow within a fluidized bed dryer plant, and the accuracy of these numerical simulations was verified against experimental data. After verification, sets of numerical simulations were conducted to analyze the critical parameters to propose an optimum operating condition.
Experimental setup
In the experimental study, the drying process was observed, and the required outputs were recorded. In the following, the dryer plant and the process conditions are described.
Experimental data
The experiment was conducted under the abovementioned operating conditions (Table 1), and two specific outputs were measured. The first one is the bed expansion inside the dryer. This parameter was determined using a gamma transmitter, which can locate particles inside the system. This dryer was also equipped with two thermometers at different locations (Fig. 2a), which were used to determine the temperature inside the system. These data were used to verify simulations' results in the following
Conclusion
Experimental and numerical analyses were conducted to analyze and optimize the drying process within a pilot-plant fluidized bed dryer. To this end, the Computational Fluid Dynamics (CFD) was used to simulate fluid flow in a pilot-plant fluidized bed dryer. The model was validated by comparison with the experimental data. In particular, the bed expansion velocity was compared with the numerical results, where approximately 5% error was observed. After verification, an optimization study was
Declaration of interest
None.
Acknowledgement
This work was supported by Petrochemical Research and Technology Company (NPC-RT) (Contract no. 08/712/94/821).
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