INTRODUCTION Plant protection activities are most important practices during crop production. The application of fungicides, herbicides, and insecticides is one of the most recurrent and significant tasks in agriculture. For orchard crops, air-assisted, mist blowers and air blast sprayers are now frequently utilised. In recent days, sprayers of various sizes are being imported from overseas which are poorly designed and also, the power consumption and power required to operate the sprayers are very high. The optimised design is a crucial for obtaining improved performance. In the power operated sprayers like mist sprayers cum duster have fans and impellers that supply air at a required high velocity but at less static pressure (Wagh et al., 2014). Three crucial components make up a centrifugal blower: the impeller, casing, and air intake duct. Air is pulled axially into the impeller of a centrifugal blower and is propelled radially through the impeller. Blowers have a rotating element (called an impeller) through which air passes and its angular momentum changes, resulting in an increase in pressure, head, and velocity of air (Wilson et al., 2006). Axial blowers and centrifugal blowers are two common varieties of blowers or fans. In a centrifugal blower, air is moved by centrifugal force, which causes the impeller blades to actually push the air out of their boundaries and create suction inside the impeller. The blower shaft drives the impeller which adds a velocity component to the air by centrifugally throwing of air away from the impeller vane tips (Zainal et al., 2021). The pressure rises and flow rate in centrifugal blowers depend on the peripheral speed (Yahya, 2010). A blower is a type of general machinery that is widely and fully utilized in agricultural fields for spraying operations. Nowadays, the design demands a detailed understanding of internal flow during design and off-design operating conditions. From the various reviews, it is found that Computational Fluid Dynamics (CFD) has successfully contributed to the prediction of flow-through blowers and enhancement of their design (Sreekanth et al., (2021). For improvement of impeller efficiency, CFD is used to predict the results of static pressure generated at the impeller's entry (Keyur et al., 2013). The impeller's optimum design is essential and significant for the effective operation of a blower (Matlakala et al., 2019). The speed and diameter of the impeller determine the air volume or pressure that the blower can generate. The air will move much faster toward the vane tip and absorb more energy as a result of the larger size impellers or speed of rotation (Addison, 1995). If impeller's diameter is decreased from the original design, pressure, air flow, and power consumption will be decreased (Chunxi et al., 2011). Therefore, impeller's trimming shouldn't be greater than 75% of the pump's original diameter. The inlet radius had a major impact on the flow rate of the centrifugal blower. Too small or too large of the inlet radius will result in a noticeable loss in flow rate. The total pressure rise and flow rate curves can be obtained as well as detailed information about flow of the fan, which can be helpful for analysis and design (Meakhail and Park 2005). Accordingly, the results are very useful in choosing the right impeller design based on the considered operating flow conditions. It also involves in evaluating the influence of the diameter and the speed of the impeller on the configuration of the blower. However, no publication has evaluated the influence of blower performance on impeller trimming. As a result, attention must be paid to how speed and impeller trimming affect blower performance. However, some works has proposed empirical formulae for determining the flow rate, and pressure. To determine the performance of centrifugal pumps affinity laws are used. The variation equations of fan performance influenced by the increased impeller diameter are suggested by analysis of these measures. The primary objective of this research is to study the blower's performance using CFD analysis. MATERIALS AND METHODS For this study closed type impeller is selected because of its highest efficiency due to its tight clearances against the internal casing but also between impeller blades. In this type of impeller, the air is drawn into the impeller eye (centre) before centrifugal forces direct air through blades, then directed axially and expelled through the outlet. Impellers were designed with two different diameters of 95 mm and115 mm using 3 D modelling (solid works) software was presented in Fig. 1. The designed impellers were tested at varying of different speeds (24000, 30000 and 36000 rpm). For each speed and impeller diameter, the power consumption and air volume flow rate, the pressure developed were computed. Affinity Laws for Centrifugal pump. If the impeller diameter or total head (or pressure) are adjusted, the affinity laws can be used to anticipate how the blower would perform (Jones et al., 2011; Matlaka, 2019). The efficiency is used to estimate the affinity laws which describe mathematical relationship between the variables involved in blower performance, such as flow, pump speed, and the total head and power. Dimensionless pump numbers and affinity laws. The laws reflect the fact that Dimensionless pump characteristics like flow rate Q (m3 /s), head, H (m), and power, P (W) to the speed, N (rpm) and to the impeller diameter, D (m), of the pump. The calculated values are presented in the Table 2. The flow capacity is expressed as Q_1/Q_2 = N_1/N_2 ⨯ D_1/D_2 The head capacity is expressed as H_1/H_2 =(N_1/N_2 )^2⨯(D_1/D_2 )^2 The power required is expressed as P_1/P_2 =(N_1/N_2 )^3⨯(D_1/D_2 )^3 These equations can be very useful in the design stage. The results shows that an impeller with a 115mm diameter gives a higher air flow rate at 36000 rpm as compared to 24000 rpm and 30000 rpm. Furthermore, it shows that the expanded portion of blades in the fan with a larger impeller significantly increases total pressure. Euler's equation, states that the energy of the air produced by the fan is proportional to the fan's diameter (Chunxi et al., 2011). Modelling and meshing of blowers. SOLIDWORKS is used to design the blowers' impeller and 3D modelling (Myaing et al., 2014). The design consists of an impeller, suction cover, and casing. These models were designed in solid works. The unstructured grid type is used to mesh the entire centrifugal blower domain. In unstructured grids, triangles in 2D and tetrahedral in 3D are utilized. Unstructured grid systems have the benefit of being highly automated and requiring minimal human effort and time (Pathak et al., 2012). An sysfluent is used for meshing. Tetrahedral meshes often offer a more automated method for volume meshing, with the option to add mesh controls to enhance the accuracy in crucial areas and they maintain good quality for complex shapes (Wagh et al., 2014; Jayapragasan et al., 2014). The mesh element size for the volute casing was kept constant throughout the analysis. Some undesirable curves and surfaces that would have affected the meshing quality have been trimmed, and others were added. The blowers are meshed using tetrahedral elements since they maintain good quality for complex shapes (Ahmad, 2011). After grid generation, the mesh independency tests were carried out. Simulation of blower. Computational Fluid Dynamics (CFD) approach is the effective method of solving non-linear partial differential equations that governs fluid flow, heat transfer and turbulence of flow (Bhatti et al., 2020). The blower performance was simulated using the CFD to examine the impact of impeller diameter. Boundary conditions play an important role in CFD analysis (Kumaran et al., 2017). Understanding the energy losses occurring in blower requires a study of the fluid flow pattern within the assembly, which can be obtained through flow analysis by CFD (Manivel et al., 2018). Statistical analysis. The Pearson correlation often referred to as Pearson's r, is a popular statistic for assessing the degree to which two variables are correlated. The correlation coefficient (r) is a dimensionless numerical variable with a range of -1 to +1 (Kim et al., 2015). As a result, the correlation significance is determined by coefficient value. A correlation value of 0 shows that two variables do not have a linear relationship. If the coefficient is 1 or extremely close to 1, the two variables are related in a positive linear manner (Schober et al., 2018). r=(∑_(i=1)^n▒〖(xi-x)(yi-y̅)〗)/√(Σ(xi-x ̅ )^2 Σ〖(yi-y̅)〗^2 ) where r is the correlation coefficient and xi and yi are the values of the individual variables. 𝑥 and c𝑦 mean values of the time series data. The relationship between rotational speed and discharge is determined using the Pearson correlation coefficient. RESULTS AND DISCUSSION Computational Fluid Dynamics (CFD).A 3D model has been created using experimental information that has been collected regarding dimensions of the impeller, casing, blade profile and guide vane etc. For the purpose of pre-processing the simulation, geometry model of the blower assembly is imported into ANSYS workbench. To create flow simulations, CFD is employed. The impeller region is operating in a rotating frame of reference and the casing region operates in a stationary frame of reference. Based on the simulation, the results of airflow through different volute geometries were investigated. The simulation of a 115mm diameter impeller with 36000 rpm was presented in Fig. 5 to 7. The velocity contours reveal that when the flow coefficient rises, the velocity at outflow also rises as shown in Figure 5. This is because the opening area is similar for all cases, so as the mass flow rate is increased the velocities will also increase. A high-velocity contour is observed near the impeller region. Similar outcomes are also reported (Choi et al., 2003). This is because of the rotation of the impeller. High-velocity contours become less pronounced due to distance away from the impeller. The velocity is seen to be reduced from the impeller to exit due to the conversion of velocity into the pressure. The turbulent kinetic energy (Fig. 6) is a result of an analysis and it shows that kinetic energy can be minimized through sophisticated design, which also results in a decrease of noise emission (Breier, 2005). Figure 7 shows the contours of pressure. It is observed that the static pressure rises as it is moved from suction to exit. This result of pressure rise is due to the conversion of velocity into pressure that takes place in the casing. This is the process of pressure recovery occurred in the casing. CFD was carried out using Ansys software and the results were presented in Tables 3 and 4. The results indicate that increases in blower speed and impeller diameter (115 mm) result in a substantial increase in flow rate. The increase in blower speed from 24000 rpm to 36000 rpm, the flow rate increases by more than 21 %, while increasing the diameter of impeller from 95m to 115 mm increases flow velocity by 15% increase for speed of 36000rpm. This indicates that by increasing the impeller diameter and speed to an optimum level the performance of the blower will be increased as stated (Chunxi, et al., 2011). The results indicated that the air velocity at blower outlet varies from 8.06 to 12.09 m/s at the speed of 24000 rpm to 36000 rpm for an impeller of 95 mm diameter whereas for 115 mm diameter, there was an increase in air velocity from 9.75 to 14.63 m/s at the speed of 24000 rpm to 36000 rpm respectively.From Table 4, it is found that the mean discharge of 30.5 m3/hr, 38.18 m3/hr,45.81 m3/hr, mean nozzle pressure of 380 Pa, 592 Pa,853 pa for a blower speed of 24000 to 36000rpm with respect to 95 mm diameter impeller. The mean discharge of 36.9 m3/hr, 46.2 m3/hr, 55.45 m3/hr, mean nozzle pressure of 555 Pa, 1034 Pa, 1250 Pa for a blower speed from 24000 to 36000 rpm with respect to 115 mm diameter impeller. It also indicates that the impeller diameter at 115mm with speed of 30000 rpm gives approximately the same air output of 46.2 m3/hr and with 95 mm diameter and 36000 rpm gives 45.81 m3/hr. This suggest that if decrease in diameter of impeller there should be an increase in speed to get better output. The pressure rise at nozzle and air discharge parameters of two impellers at three different speeds are presented in Fig. 8. Effect of power and discharge. Power output is analysed to understand the changes in the system performance according to various operating conditions. Regarding power consumption as shown in Fig. 9, results indicate that the mean power consumption of 72.46 W,142 W,245 W for blower with 24000 rpm, 30000 rpm,36000 rpm of 95 mm diameter impeller, The mean power consumption of 128 watts, 251 watts, 433 watts for blower with 24000 rpm,30000 rpm,36000 rpm of 115 mm diameter impeller. Similar result of power consumption rises gradually as the impeller diameter rises as reported (Mwinuka, 2016). This increase might be due to an increase in inertia load, diameter, speed and change in air flow dynamics. The design or redesign of manufactured blowers may benefit greatly from these findings. The effect of speed and diameter of impeller on blower efficiency is shown in Fig 10. The result suggests that as blower speed increased, operating at 36,000 rpm as compared to 24000 rpm of 115mm diameter blower efficiency declined by 27%. This might be caused by lateral gap volumetric and impeller frictional losses. The blower may have been less efficient as a result of running at faster speed. As the blower speed increased, the efficiency is decreased. Similar results were observed by Dhande et al. (2016). This could be as a result of decrease in static pressure at the casing caused by an increase in air discharge. The linear relationship between discharge and rotational speed has been found using a scatter diagram as shown in Fig. 11. The correlation coefficient (R2) is determined to be 0.87, suggesting a positive strong link among discharge and speed. The results were considered to be more optimistic when they were compared with similar research.