IntroductionTop

Separation, purification, and the ability to handle grains and powders are the prominent aspects of industrial processes (Burtally et al., 2002). The application of separation chambers is the separation of harvested pods and seeds from carrier air in products-harvesting machines such as chickpea, lentil, bean, etc. The problem of harvesting such products is challenging and researches have been carried out in this field (Zhao et al., 2011; Gharakhani et al., 2017). A detailed study of the chambers was conducted, proving the fact that improvement of design variables can increase the collection performance (Golpira et al., 2013). Nowadays, the separation efficiency of the chambers used in chickpea harvesting machines is about 80%. Accordingly, separation efficiency improvement can bring many benefits, including economic aspects along with adequate efficiency (Motlagh et al., 2018). To design the most efficient and cost-effective separation chamber (maximum separation, minimum required airflow, and minimum pressure drop), a piece of detailed information about the effect of different chamber design variables on the flow path characteristics is needed. These variables can include suction condition and flow path deviation. Since the effect of design parameters has not been studied on the fluid flows and optimum performance of the separation chambers, a comprehensive investigation is required. An experimental study may determine the status of particle movement, but in order to obtain some conclusive results, numerical simulation techniques along with experimental tests should be conducted. Numerical simulations can progress an inexpensive way for predicting the results as well as the geometric optimization process.

Accordingly, extensive studies have been conducted considering separation and purification in various fields. Many studies have been conducted to expand the application of hydrocyclones by optimizing the effective variables and conditions (Tian et al., 2018). Furthermore, separation methods and instruments have been developed in which a set of geometrical ratios has been optimized in cyclones to achieve the least pressure drop (Elsayed Khairy & Lacor, 2010). Also, membrane techniques, including both liquid and non-liquid membranes, have been investigated (Chen et al., 2018). Generally, gas-solid separation is applied in segregation chambers, air filters, bag filters, cyclone separators, impingement separators, electrostatic and high -tension precipitators (Miller, 2014). On the other hand, for separation of comparatively large particles, segregation chambers, inertial separators, and cyclones are the most suitable choices (Krupińska et al., 2018).

However, segregation chambers are the oldest and simplest equipment for separating the particles from an air stream without implementing any excessive filters in which the segregating factor is the air stream. Noteworthy, increment of the cross-section area at the chamber entrance reduces the airspeed in X direction of the stream so the particles would be segregated (Panasiewicz et al., 2012). The advantages of segregation chambers include convenient construction, no moving parts, low investment and maintenance cost, and low pressure drop. The most crucial factors that affect the performance of the segregation chambers include the dimensions of the chamber, the uniformity of input material feeding, the velocity and relative humidity of air stream (Emami et al., 2007; Krupińska et al., 2018).

On the other hand, granular segregation is presented in different processes for many industries, including chemical, pharmaceutical, mining, food, agriculture, and different natural phenomena (Wei et al., 2017). In the segregation method, air velocity is decreased at a particular part of the path flow. Accordingly, the particles are segregated from the air flow due to imbalances between particle density and air pressure. Möbius et al. (2001) found that particle density has a significant effect on the separation process, and the density dependence is sensitive to the background air pressure.

Different aspects of the particle removal from the gas stream have been studied in the segregation chamber. Chen et al. (2017) stated that dimensions, shape, weight, density, and adhesiveness should be calculated in addition to the concentration of the segregated particles. Various studies have been conducted to complete the separation and purification performance of the segregation chambers (Molerus & Glückler, 1996). Collection efficiency and pressure drop of two single cyclones with central hopper and side wall beside twin cyclone were evaluated by Ha et al. (2011). The separation efficiency was carried out using DMT (Deutche Montan Technologie) test.

Computational fluid dynamics (CFD) is a numerical technique that is widely used for the simulation of complex flows and has been included as an essential tool for the engineering design goals to predict the performance of newly proposed designs or processes before manufacturing (Rezvanivand Fanayi & Nikbakht, 2015; Devarrewaere et al., 2016). A multiphase CFD model (mixed model) with sub-modules was used to simulate the performance of the hydrocyclones and predict velocity field extracted from the Large Eddy Simulation (LES) and Differential Reynolds Stress (DRSM) turbulence models and subsequently is compared with the Laser Doppler Anemometry (LDA) measurements (Narasimha et al., 2012). Also, CFD was used to optimize a cyclone type spray chamber with a flow spoiler, designed to provide satisfactory efficiency (Schaldach et al., 2003). Furthermore, CFD simulation was employed to investigate the effect of including the vertical baffle at the feed section of a separation tank for the improvement of solid segregation in potable water treatment (Goula et al., 2008). Gebrehiwot et al. (2010) used the CFD technique to examine the flow configuration inside the combined cleaning chamber. Olatunde et al. (2017) used CFD to investigate the airflow distribution inside a rice bin storage system with different grain mass configurations. Moreover, Scotto di Perta et al. (2016) studied wind tunnel configurations effects with CFD simulation on the aerodynamic performances of the wind tunnels. A hybrid Euler–Lagrange approach was used for numerical simulation of a dense solid particle flow inside a cyclone separator. The simulations were performed for various inlet velocities of the gaseous phase and mass particle loadings. In addition, the influences of several sub-model variables on the results were studied (Kozołub et al., 2017). Also, a novel computational framework entitled “System Coupling” was developed at ANSYS Inc. that simulates complex multi-physics coupled problems and prepares comprehensive validation and verification researches (Chimakurthi et al., 2018). Characteristics of a percussive gas-solid separator as an experimental study and numerical simulation were studied and conducted, increasing both inlet velocity and negative pressure of the exhaust gas outlet improves separation efficiency (Wu et al., 2018). Huang & Kuo (2017, 2018) simulated a rotating drum by CFD, and proposed the bed surface fitting (BSF) method to specify the suitable solid phase kinetic viscosities of granular flows. In the sugar beet processing of a sugar factory, a thermo-vapor-compressor simulation was studied to reduce energy consumption in the crystallization section. In this study, dead steam was recovered by a thermo-compressor and reused in the processing units (Rezvanivand-Fanaei et al., 2019). CFD also used as a numerical method to energy saving in a processing unit (Rezvanivand-Fanaei et al., 2021). However, a comprehensive CFD simulation has not been performed to investigate the airflow distribution in agricultural separation chambers.

According to the comprehensive literature review, scientific literature lacks on investigating a proper separation chamber configuration from theoretical and experimental viewpoints. Accordingly, this paper assesses different conf igurations of the separation chambers through comprehensive CFD-based numerical and empirical investigations. Therefore, the main novelties and objectives of this study may be summarized as to: i) examine four innovative platforms for performance comparison purpose and eventually selecting the most favorable design; ii) compare separation and purification efficiency, energy consumption and pressure drop for the proposed concepts; iii) deep understand the airflow circumstances within the separation chambers; iv) study the effects of the suction condition and flow path on increasing and decreasing the losses and energy consumption of the systems; and v) investigate comprehensively CFD to examine precisely the separation and purification processes in agricultural equipments.

Material and methodsTop

The proposed configurations were comprehensively analyzed and modeled to compare the corresponding performance of the separation chambers.

 

Separation chamber

The separation and purification chamber performance rely on the principle that the airflow transfers particles across a path which dimensions are larger than the dimensions of the other parts. Consequently, airspeed is decreased, and the particles are separated from the carrier air. Achieving a better separation performance relies on several specified conditions, which must be considered properly. In this regard, dimensions of the settling chamber, length (L) and height (H) of the chamber should be defined (Krupińska et al., 2018). Accordingly, the separation chamber used in this work was constructed in accordance with the geometric variables proposed by Matin (1991). For this purpose, the pertinent dimensions were calculated using the following equations:

 

 

 

 

where a = square dimension of chamber (m), L = length of chamber (m), Q = airflow (m3/s), Vw = air velocity (m/s), µ = air dynamic viscosity (Ns/m2), D = pods diameter (m), ρs = pods density (kg/m3) and g = gravity acceleration (m/s2). The corresponding chamber has a main suction duct (in the direction of the moving particles) and twofold side suction ducts (in the lower part of the chamber). In addition, in the compartment input field, an adjustable blade (0 to 90°) was placed to deviate the flow path. Moreover, a strong suction was provided implementing three high-pressure centrifugal fans. The main fan was mounted on the main suction duct, and two auxiliary side fans were used to enhance the suction performance. Meanwhile, the side fans were embedded inside the structure and the positioning of the fans was limited due to constraints in the geometry of the facility. To assess the suction circumstance and deviation of the streamline, four novel configurations of separation chamber were considered (Fig. 1) on the pre-experienced operation of the system: the chamber with main suction which supplies the required airflow (configuration I); the chamber with main suction and guide blade to deviate the f low path (configuration II); the chamber with main suction and twofold side suction ‒ the side suctions can split the unswerving airstream (configuration III); and the chamber with main suction, flow deflective blade, and twofold side suctions, which is the combination of the above-mentioned configurations (configuration IV).

 

 

Separation efficiency and relative purification

Flow characteristics and required airflow were analyzed and compared in all the configurations. In addition, separation efficiency was calculated as:

 

where η = separation efficiency, Ss = sedimented pods and St = total feed pods to the chamber. To calculate the separation efficiency, 100 samples of pods were fed to the chamber (see Fig. 2a), after sedimentation of the pods, the numbers of separated pods counted and were inserted into Eq. (3). Furthermore, relative purification may be defined as:

 

where RP = relative purification, Pe = eliminated hollow pods and Pt = total hollow pods. To calculate the relative purification, 100 samples of pods were selected, including 90 full pods and 10 hollow pods. The actual situation of harvested pods is presumed for the considered proportion, which has been illustrated in Fig. 2b.

 

Figure 1.  Proposed novel configurations for the separation chambers.

 

 

Experimental setup

An experimental investigation was carried out to compare the performance of the four proposed configurations of the separation chamber. Accordingly, the extracted velocity and pressure values were used to validate the numerical models. Fig. 3 shows the experimental setup consisting of the material transfer path, the main separation chamber, the main suction fan, the side fans, and the flow deflective blade. The fan was driven by an electrical motor (3.0 kW and 3000 rpm), and the rotational speed was adjusted by an inverter (LG-5A). Subsequently, the flow velocity and pressure were measured by a portable hot wire anemometer (MODEL 8465- TSI, resolution of 0.07 m/s, working range of 0.125–50 m/s) and a differential pressure meter (Model CPE310s- KIMO).

Meanwhile, four cross-sections were chosen for measuring the flow velocity and pressure at the position of x=5 cm, x=15 cm, x=25 cm, and x=35 cm as indicated in Fig. 4 with the numbers 1 to 4 along the x-axis. Furthermore, four points along the related height (y-axis) were investigated at the position of y=5 cm (points 1, 5, 9, and 13), y=15 cm (points 2, 6, 10, and 14), y=25 cm (points 3, 7, 11, and 15), and y=35 cm (points 4, 8, 12, and 16) from the top of the chamber to the bottom. For each point (overall 16 points), three measuring points were considered (along the z-axis) at the position of z=5, 15, and 25 (internal points). Moreover, the experimental results indicated a good agreement between z=5 and 25 cm since the axis-symmetric of these points concludes a similar outcome. Additionally, the measurements were conducted in advance of the main chamber for which three cross-sections were considered for the material transfer path, at the position of 1/4 (point 17), 2/4 (point 18), and 3/4 (point 19) of the transfer path length. The measurements were performed sufficiently away from the perforated walls to prevent the results from being affected because of the local effects of the embedded holes on the streamline. The final values were considered to be the mean value of three replicated velocity and pressure values. The dimen-sions of the separation chamber and specifications of the system components are listed in Table 1.

 

 

Figure 2.  Experimental assessment: (a) separated chickpea pods, (b) hollow and full chickpea pods.

 

 

Figure 3.  Proposed chamber and components of the experimental setup: (a) diffe-rential pressure meter, (b) inverter, (c) main fan, (d) side fans, (e) sedimentation chamber, and (f) anemometer.

 

 

 

Grid division

Fig. 5 depicts the tetrahedral mesh generated for the chamber for simulation purposes. Grid independence test was also scrutinized to ensure grid independency of the outcomes and also to ascertain the medium-sized grid for fast and efficient convergence. In order to attain accurate results, finer grids were generated for the deflective blade and side fans.

 

 

CFD modeling

In order to assess the internal airflow pattern, the propo-sed concepts of the separation chamber were analyzed by CFD simulation. Ansys Fluent package was used to solve the correlated equations for the whole proposed concepts. The coupled solver is recommended for transonic and supersonic flows. On the other hand, the segregated solver is much fas-ter for low-speed flows and is more appropriate for incom-pressible flows, showing good performance for simulating subsonic compressible flows; so, it was used in this study (Ansys Fluent, 2013). A flowchart describing the simulation procedure in Ansys Fluent is showed in Fig. S1 [suppl.].

 

Figure 4.  A schematic view of points (a) and side fans position (b).

 

 

 

 

Governing equations and turbulence model

For the flow simulation purpose, continuity and momentum equations were solved in three dimensions for the superficial air velocities and pressure distribution.

Continuity equation:

 

Momentum equation:

 

where ρ = density (kg/m3), t = time (s), ui and uj are the average superficial velocity component in i and j directions, respectively (m/s), p = pressure (Pa), gi = accelera-tion due to gravity (m/s2), μ = viscosity (Pa·s) and i, j = 1, 2, 3 (x, y, z).

The inlet Reynolds number of the flow was found higher than 5000 in all proposed separation chamber con-figurations. Accordingly, the k− ε model, one of the most common and widely used turbulence models, was used. The k−ε model is supported by two equations:

— Turbulent kinetic energy (k) equation:

 

— Dissipation (ε ) equation:

 

where ui = velocity component in corresponding direction (m/s), Cμ , C1σ , C2ε , σk and σε = constants, Eij = component of rate of deformation (1/s), σ = turbulent based on Prandtl number, and σt = mean turbulent vis-cosity. For a better convergence, the residuals have been stabilized at 10-4 for the equations of continuity and momentum. The values of these constants have been arrived by numerous iterations of data fitting for a wide range of turbulent flows as (Ansys Fluent, 2013): Cμ = 0.09; σk = 1.00; σσ =1.30; C1ε =1.44; C2ε =1.92.

 

Table 1. Specifications of the separation and purification system.

D

 

Figure 5.  Generated tetrahedral grid for the chamber in Gambit software.

 

 

Discretization scheme

The entire separation chamber was considered as a control volume to perform a 3D numerical assessment for the proposed configurations. To ensure the grid indepen-dency results, three grid domains were tested in our pre-liminary computation i.e., fine (541,286 cells), medium (314,520 cells), and coarse (185,126 cells). The difference in the results was less than 5% for the pressure results. In this regard, computational domain considered having 314,520 cells (medium size grid) for the generated grid. Meanwhile, the entire computational domain was genera-ted using tetrahedral volume cells and the discretization was conducted based on the most satisfactory grid reso-lution required for the RANS simulation. Noteworthy, to have a satisfactory accuracy, a fine grid was generated for the zones near the employed fans and the separation part. On the other hand, for the other parts of the domain, me-dium size grid was generated accordingly.

 

 

Boundary conditions

Getting accurate results from the CFD model strongly depends on the correct definition of the boundary condi-tions. Accordingly, three different boundary conditions were used in this work: inlet velocity, outlet pressure, and the walls. For all simulations, the outlet pressure was fixed as atmospheric pressure for the outlet boundary. No-slip conditions were assumed for the corresponding walls. In order to have a reliable turbulence simulation near the walls, finer elements were used in the boundary layer (Rong et al., 2011).

 

 

Validation

We used velocity and pressure data to validate the experimental data with CFD simulations. Moreover, the pods behavior was better observed by the High Speed Photography (HSPh) technique in all configu-rations. In order to eliminate the effect of pod sizes on motion trajectory, tracking experiments were repeated three times for each configuration. To validate results, Lan et al. (1999) and Panning et al. (2000) used op-toelectronic sensors, and Karayel et al. (2006) and Zhan et al. (2010) applied smoke tests and high-speed camera system sensors.