• Energy Research

Fig. 11. Comparison of the time averaged tangential and axial velo city between the LDA measurements, Hoekstra [65] and the current Reynolds stress model (RSM) results at z=94.25 cm from cyclone bottom. From left to right tangential velocity and axial velocity, Dx/D=0.5. the published article, by mistake, the right hand and left hand figures are identical. The comments and analysis based on the figure are unchanged. The publisher would like to apologise for any inconvenience this may have caused to the authors of this article and readers of the journal.

Abstract The pressure drop is an important performance parameter to evaluate and design cyclone separators. In order to accurately predict the complex non linear relationships between pressure drop and geometrical dimensions, a radial basis neural network (RBFNN) is developed and employed to model the pressure drop for cyclone separators. The neural network has been trained and tested by experimental data available in literature. The result demonstrates that artificial neural networks can offer an alternative and powerful approach to model the cyclone pressure drop. Four mathematical models (Muschelknautz method “MM”, Stairmand, Ramachandran and Shepherd & Lapple) have been tested against the experimental values. The residual error (the difference between the experimental value and the model value) of the MM model is the lowest. The analysis indicates the significant effect of the vortex finder diameter Dx and the vortex finder length S, the inlet width b and the total height Ht. The response surface methodology has been used to fit a second order polynomial to the RBFNN. The second order polynomial has been used to get a new optimized cyclone for minimum pressure drop using the Nelder–Mead optimization technique. A comparison between the new design and the standard Stairmand design has been performed using CFD simulation. CFD results show that the new cyclone design is very close to the Stairmand high efficiency design in the geometrical parameter ratio, and superior for low pressure drop at nearly the same cut-off diameter. The new cyclone design results in nearly 75% of the pressure drop obtained by the old Stairmand design at the same volume flow rate.

This article aims to improve the system cooling capacity of an adsorption chiller working with a silica gel/water pair by an allocation of the optimum cycle time at different operating conditions. A mathematical model was established and validated with the literature experimental data to predict the optimum cycle time for a wide range of hot (55°C–95°C), cooling (25°C–40°C), and chilled (10°C–22°C) water inlet temperatures. The optimum and conventional chiller performances are compared at different operating conditions. Enhancement ratio of the system cooling capacity was tripled as the cooling water inlet temperature increased from 25°C to 40°C at constant hot and chilled water inlet temperatures of 85°C and 14°C, respectively. Applying the concept of the optimum cycle time allocation, the system cooling capacity enhancement ratio can reach 15.6% at hot, cooling, and chilled water inlet temperatures of 95°C, 40°C, and 10°C, respectively.

Abstract The low-mass loading gas cyclone separator has two performance parameters, the pressure drop and the collection efficiency (cut-off diameter). In this paper, a multi-objective optimization study of a gas cyclone separator has been performed using the response surface methodology (RSM) and CFD data. The effects of the inlet height, the inlet width, the vortex finder diameter and the cyclone total height on the cyclone performance have been investigated. The analysis of design of experiment shows a strong interaction between the inlet dimensions and the vortex finder diameter. No interaction between the cyclone height and the other three factors was observed. The desirability function approach has been used for the multi-objective optimization. A new set of geometrical ratios (design) has been obtained to achieve the best performance. A numerical comparison between the new design and the Stairmand design confirms the superior performance of the new design. As an alternative approach for applying RSM as a meta-model, two radial basis function neural networks (RBFNNs) have been used. Furthermore, the genetic algorithms technique has been used instead of the desirability function approach. A multi-objective optimization study using NSGA-II technique has been performed to obtain the Pareto front for the best performance cyclone separator.

AbstractThe effect of the cyclone inlet dimensions on the performance and flow field pattern has been investigated computationally using the Reynolds stress turbulence model (RSM) for five cyclone separators. The results show that, the maximum tangential velocity in the cyclone decreases with increasing the cyclone inlet dimensions. No acceleration occurs in the cyclone space (the maximum tangential velocity is nearly constant throughout the cyclone). Increasing the cyclone inlet dimensions decreases the pressure drop. The cyclone cut-off diameter increases with increasing cyclone inlet dimension (consequently, the cyclone overall efficiency decreases due to weakness of the vortex strength). The effect of changing the inlet width is more significant than the inlet height especially for the cut-off diameter. The optimum ratio of inlet width to inlet height b/a is from 0.5 to 0.7.

Abstract Gas cyclones have many industrial applications for separation of solids and liquids from gases. The geometry of the cyclone is the most influential parameter for its performance. This study investigates the effect of presence of an inner cone located at the bottom of the cyclone on the performance of the cyclone separator. Several CFD simulations in cyclones with inner cones with different diameters and heights were performed using the Reynolds stress turbulence model (RSM). The collection efficiency of the cyclone was studied using the Eulerian-Lagrangian approach. The results showed that the maximum tangential velocity is 1.6–1.7 times the inlet velocity. On the other hand, in the radial sections crossing the inner cone, the gradients of the axial and tangential velocities are zero. The maximum axial and tangential velocities occurred in the region between the top of the inner cone to the vortex finder. It was found that by increasing the inner cone height at constant diameter, the cyclone collection performance improves. An increase in the diameter of the inner cone, however, leads to a decrease in the cyclone performance. In overall, with an increase in the inner cone height and diameter, the pressure loss decreases. Finally, the erosion study was conducted using the Det Norske Veritas (DNV) erosion model. It was found that the value of coefficient of restitution affects the predicted erosion rate. In addition, the collection efficiency decreases when the erosion effect was included in the CFD model especially for higher velocities.

AbstractEmission abatement cyclone performance is improved by increasing collection effectiveness or decreasing energy consumption. The object of this study was to quantify the pressure drop and fine particulate (PM2.5) collection of 1D3D cyclones (H=4Dc, h=1Dc) at inlet velocities from 8 to 18ms−1 (Stk=0.7–1.5) using heterogeneous particulate as a test material at inlet concentrations from 3 to 75gm−3. Cyclone exhaust was passed through filters. Laser diffraction particle size distribution analysis was used to estimate PM2.5 emissions. Response surface models showed a strong correlation between cyclone pressure loss (Euler number) and inlet velocity and predicted a 46% reduction in pressure loss for a 25% reduction in inlet velocity (Stokes number). The model for PM2.5 emissions was less definitive and, surprisingly, predicted a 31% decrease in PM2.5 emissions when operating 25% below the design inlet velocity. Operating below the design inlet velocity (at a lower Stokes number) to reduce pressure losses (Euler number) would reduce both the financial and the environmental cost of procuring electricity. The unexpected co-benefit suggested by these trials was that emission abatement may improve at the same time, though other empirical trials have shown emissions to be independent of inlet velocity and Stokes number.

Abstract The present study is aimed at optimizing the performance of multi-inlet gas cyclones. The current contribution is threefold. First, a design of experiments (DoE) has been conducted for three variables viz. the flow rate through the secondary inlet, the (square) cross-sectional area of the secondary inlet and the location of the top of the main inlet from cyclone roof. Second, the numerical simulations are performed using large eddy simulation (LES) to predict the Euler number, cut-off size and the collection efficiency for different combinations of the independent variables. The CFD simulation results are used to train an artificial neural network for three responses, namely the Euler number, the cut-off diameter and the overall collection efficiency. Moreover, the simulation results explain how the variations of the design variables affect the flow pattern and performance. Furthermore, the fitted surrogate model demonstrates that the most significant factors are the ratio of flow rates and the area ratio. Third, single-objective and multi-objective optimization studies are carried out using artificial neural network. The optimum design results in better performance than the conventional cyclones.