Predicting pressure drop in venturi scrubbers with artificial neural networks

In this study a new approach based on artificial neural networks (ANNs) has been used to predict pressure drop in venturi scrubbers. The main parameters affecting the pressure drop are mainly the gas velocity in the throat of venturi scrubber (V(g)(th)), liquid to gas flow rate ratio (L/G), and axial distance of the venturi scrubber (z). Three sets of experimental data from five different venturi scrubbers have been applied to design three independent ANNs. Comparing the results of these ANNs and the calculated results from available models shows that the results of ANNs have a better agreement with experimental data.     

THEORETICAL STUDY OF NONUNIFORM DROPLETS CONCENTRATION DISTRIBUTION ON VENTURI SCRUBBER PERFORMANCE

A new three-dimensional dispersion model has been developed and was used to study particulate removal operations in a venturi type scrubber. The model takes into account the effect of nonuniform droplets concentration distribution on the particulate removal efficiency of the scrubber of Brink and Contant (1958). Experimental data was used to test the results of the mathematical model. The results from the model are in good agreement with the experimental data. After validating the model, it was used to predict the effect of parameters such as liquid to gas flow rate ratio, gas throat velocity, and angle of the divergent section and nozzle diameter on the extent of nonuniformity of drops. Removal efficiency will increase with increasing uniformity of droplets concentration distribution. Thus, any factor that increases removal efficiency increases uniformity and vice versa. The factors affecting uniformity are: droplet diameter, liquid jet penetration length and size of scrubber.     

Simulation of an orifice scrubber performance based on Eulerian/Lagrangian method

A mathematical model based on Eulerian/Lagrangian method has been developed to predict particle collection efficiency from a gas stream in an orifice scrubber. This model takes into account Eulerian approach for particle dispersion, Lagrangian approach for droplet movement and particle-source-in-cell (PSI-CELL) model for calculating droplet concentration distribution. In order to compute fluid velocity profiles, the normal k− turbulent flow model with inclusion of body force due to drag force between fluid and droplets has been used. Experimental data of Taheri et al. [J. Air Pollut. Control Assoc. 23 (11) (1973) 963] have been used to test the results of the mathematical model. The results from the model are in good agreement with the experimental data. After validating the model the effect of operating parameters such as liquid to gas flow rate ratio, gas velocity at orifice opening, and particle diameter were obtained on the collection efficiency.     

音速喷嘴一元流动模型详解及其激波计算

针对文丘里音速喷嘴,阐述了如临界背压比等概念,指出了ISO 9300中背压比定义存在容易造成歧义的缺陷。然后基于一元等熵流动理论,从数学上证明了：当文丘里喷嘴喉部压力与上游滞止压力之比达到临界压比时,喉部产生音速,通过喷嘴的质量流量达到最大值;推导了实际条件下喷嘴的流量公式,导出的流量公式相较于ISO 9300给出的相应公式,增加了喉部状态参数下的压缩性系数修正项■。最后从气体动力学基本方程出发,讨论了在较大背压比范围内,喷嘴扩散段中产生激波的机理,给出了激波产生的位置、激波前、后的压力和马赫数的一元流动计算模型,并运用数值模拟方法对计算结果进行了验证,同时还与Craig A的实验数据作了对比。对最小出口压比对比的结果显示,一元流动模型与实验数据的最大误差≤17%。     

Performance evaluation of a new micro gas cyclone using simulation and experimental studies to capture indoor fine particles

The aim of this study was evaluating a micro gas cyclone performance with a body diameter of 10?mm to collect indoor fine particles. The design of a cyclone requires minimizing the pressure drop and maximizing the separation efficiency. Overall and grade efficiencies, pressure drops, and cut sizes have been investigated through a theoretical model, simulation, and experimental studies. The experimental part was conducted using an Electrical Low-Pressure Impactor (ELPI) device to measure particle concentration for flow rates of 10–13.3 (l/min). In order to study the pressure drop and velocity behavior for different flow rates, COMSOL software was utilized. The obtained results from experimental work have met the theoretical and simulation outcomes adequately. It has been confirmed by all the obtained results that by increasing the flow rate and subsequently inlet velocity, the particle collection efficiency and pressure drop increase while the cut size decreases.     

Enhancement of air purification by unique W-plate structure in two-stage electrostatic precipitator: A novel design for efficient capture of fine particles

In this paper, a novel W-plate two-stage ESP was developed and investigated systematically through the experimental and simulated process. Numerical models and available calculation procedure of solving coupling electrostatic field, fluid field, and particle dynamics were established, whose accuracy was validated by experiments. The relationship among collection efficiency, gas velocity, and particle diameter was studied, and the distribution of electrostatic field, the evolution of EHD flow and fluid field, and particle dynamics, including particle charging, particle trajectory, transverse velocity, and particle concentration, were also investigated thoroughly. Results showed that W-plate two-stage ESP exhibited excellent number-based collection efficiency for fine particles which benefited from the reasonable structure design and the exceeding weak influence of EHD flow. Besides, the particle charging process suggested that the diameter decided the dominant charging mechanism, and the trajectory also played an important role in controlling the charging action. Compared with the behavior of each particle injected at different inlet positions, fine particles injected near the discharge wire got more charging number and quicker capture. Importantly, W-plate structure could exert its crucial role in capturing particles with the help of fluid field and inertial effect when inlet gas velocity increased rapidly. W-plate two-stage ESP had more than 90% number-based collection efficiency for >3 μm diameter particles and more than 75% number-based collection efficiency for 0.3–1 μm diameter submicron particles at 2 m/s gas velocity in both experimental and simulated investigations.     

THEORY OF THE FRACTIONAL COLLECTION EFFICIENCY FOR THE AXIAL FLOW CYCLONE DUST COLLECTOR

A cyclone dust collector is a simple device with no moving parts, so it is applied in many industrial fields. However there is still no satisfied theory to estimate the collection efficiency for a given cyclone with high reliability since it is very difficult to predict the movement of the fine solid particles in the three dimensional turbulent rotational flows in the cyclone. A new model of the fractional collection efficiency including the diffusion effect of the solid particles and the decay effect of the tangential velocity of gas flow along the concave wall surface has been derived. In order to confirm this model, a simplified axial flow cyclone of body diameter D₁ = 99 mm has been constructed and fly-ash particles were used as a test dust. The experimental results of collection efficiency were compared those predicted by the Ogawa model and the Fuchs model.     

Experimental and numerical studies on a bubble-induced inverse gas-liquid-solids fluidized bed

Hydrodynamics in a newly invented bubble-induced inverse gas–liquid-solids three-phase fluidized bed has been studied via both experimental and numerical methods. With experiments in a 3.0 m column of 0.153 m in diameter, four fluidization regimes including a fixed bed regime, a bed expansion regime, a complete fluidization regime, and a freeboard regime have been identified with the increase in the superficial gas velocity. A three-phase Eulerian-Eulerian CFD model was developed to simulate the hydrodynamics in the inverse three-phase fluidized bed and the simulation results have a good agreement with the experimental data. The effects of the particle property and solids loading on the transitions across the flow regimes were numerically studied. A higher solids loading and/or a larger particle density are reported to contribute to an easier fluidization and a faster flow development to the complete fluidization regime. The radial flow structure becomes less uniform with increased inner circulation of the liquid after introducing more bubbles into the column.     

Fluidization using pseudoplastic liquids – Elutriation and ANN modeling

Experimental work on elutriation of irregularly shaped sand particles (0.538–2.03 mm diameter) was carried out in three different Perspex columns (47 mm, 72 mm and 92.3 mm) using different non-Newtonian pseudoplastic liquids (0.4–0.8 kg/m³ SCMC solution). The effects of operating parameters, column diameter, bed weight, particle diameter, particle sphericity, liquid rheological properties on the minimum elutriation velocity were examined. The statistically accepted empirical correlation was developed. ANN model could predict the experimental data of minimum elutriation velocity with a correlation coefficient of 0.9951.     

Prediction of hopper discharge rate using combined discrete element method and artificial neural network

An Artificial Neural Network (ANN) was developed to predict the mass discharge rate from conical hoppers. By employing Discrete Element Method (DEM), numerically simulated flow rate data from different internal angles (20°–80°) hoppers were used to train the model. Multi-component particle systems (binary and ternary) were simulated and mass discharge rate was estimated by varying different parameters such as hopper internal angle, bulk density, mean diameter, coefficient of friction (particle-particle and particle-wall) and coefficient of restitution (particle-particle and particle-wall). The training of ANN was accomplished by feed forward back propagation algorithm. For validation of ANN model, the authors carried out 22 experimental tests on different mixtures (having different mean diameter) of spherical glass beads from different angle conical hoppers (60° and 80°). It was found that mass discharge rate predicted by the developed neural network model is in a good agreement with the experimental discharge rate. Percentage error predicted by ANN model was less than ±13%. Furthermore, the developed ANN model was also compared with existing correlations and showed a good agreement.     

Simulation of a spray scrubber performance with Eulerian/Lagrangian approach in the aerosol removing process

In this study, a mathematical model has been developed to simulate the performance of a spray scrubber in an industrial ammonium nitrate plant. The model is based on the Lagrangian approach for the droplets movement and particle source in cell (PSI-CELL) model for calculating the droplet concentration distribution. Consequently, unlike former research, the emphasis is on the droplet dynamic behavior. In the current study, for approaching a realistic model, a droplet size distribution rather than average diameter, and also liquid film formation rather than uniform and constant droplet flow rate has been applied. Also, the Eulerian method has been used for the calculation of the particles removal efficiency and energy balance has been applied on the gas to estimate the droplet size distribution. In the experimental section, the concentration of particles and their size distribution in both inlet and outlet gas of the studied scrubber has been measured for the validation of the predicted particles collection efficiency. In addition, the temperature of the gas at inlet, outlet and in the middle of the tower has been measured for the confirmation of the predicted droplet size distribution in the tower. A good consistency between the model and data has been observed. After the model is validated, it is used to investigate the various variable profiles such as liquid film, total projected surface area of the droplets, velocity profile of the droplets and some of the other parameters in the spray scrubbers.     

文氏管对气液两相脉冲爆轰发动机工作过程影响的数值模拟

为研究文氏管对脉冲爆轰发动机内雾化混合和爆轰过程的影响,建立了气液两相爆轰的欧拉-拉格朗日模型,其中气相采用时空守恒元与求解元方法求解,液相采用四阶龙格库塔法求解。计算结果表明:文氏管能加快液滴雾化、两相混合,缩短点火起爆距离和时间;并且喷嘴安装在文氏管喉部时点火起爆距离和时间最短。研究结果可为脉冲爆轰发动机的优化设计提供参考。     

Experimental and modeling studies on mixing behavior of binary mixtures in a spout-fluid bed

Experimental and modeling studies have been performed to determine mixing characteristics of binary mixtures in a spout-fluid bed. Spherical glass beads of diameters (3.075, 1.7, 1.2, and 0.75?mm) and air as fluidizing medium have been used in the study. Effect of various system parameters, namely, initial static bed height, gas velocity, diameter ratio, mixture composition, and sampling time on mixing of binary particles has been experimentally investigated. A dimensionless correlation has been developed for mixing index. Mixing behavior has been modeled using artificial neural networks (ANNs). Training of ANN was performed using the Levenberg–Marquardt (LM) backpropagation algorithm to predict the mixing index. The predictions of the ANN were found to be in good agreement with the experimental results and predictions from developed correlations.     

On the characteristics of the equations of motion for a bubbly flow and the related problem of critical flow

Summary For the study of transients in gas-liquid flows, the equations of the so-called separated flow model are inadequate, because they possess, in the general case where gas and liquid move at different velocities, complex characteristics. This paper is concerned with the equations of motion for bubbly flow. The equations are discussed with emphasis on the aspects of relative motion and the characteristics are calculated. It is found that all characteristics are real. The results are used to establish a relation between gas velocity, liquid velocity, void fraction and sound velocity at critical flow. This relation agrees very well with experimental data for these quantities as measured by Muir and Eichhorn in the throat of a converging-diverging nozzle.On leave of absence from Istituto di Fisica, Universitá Degli Studi, Milano, Italy.     

ANN–GA approach for predictive modeling and optimization of NOx emission in a tangentially fired boiler

An artificial neural network (ANN) and genetic algorithm (GA) approach to predict NOx emission of a 210 MW capacity pulverized coal-fired boiler and combustion parameter optimization to reduce NOx emission in flue gas, is proposed. The effects of oxygen concentration in flue gas, coal properties, coal flow, boiler load, air distribution scheme, flue gas outlet temperature, and nozzle tilt were studied. The data collected from parametric field experiments was used to build a feed-forward back-propagation neural net. The coal combustion parameters were used as inputs and NOx emission as outputs of the model. The ANN model was developed for full load conditions and its predicted values were verified with the actual values. The algebraic equation containing weights and biases of the trained net was used as fitness function in GA. The genetic search was used to find the optimum level of input operating conditions corresponding to low NOx emission. The results proved that the proposed approach could be used for generating feasible operating conditions.     

Computational simulation of thermally sprayed WC–Co powder

WC–Co cemented carbides are a class of hard composite materials of great technological importance. They are widely used as tool materials in a large variety of applications that have high demands on hardness and toughness, including mining, turning, cutting and milling. The HVOF (high velocity oxygen fuel) technology has been very successful in spraying wear resistant WC–Co coatings with higher density, superior bond strengths and less decarburization than many other thermal spray processes, attributed mainly to its high particle impact velocities and relatively low peak particle temperatures. The degree of decomposition and bond strength is directly related to relevant particle parameters such as velocity, temperature and state of melting or solidification. These are consecutively related to process parameters such as powder particle size distribution, carrier gas flow rate, and fuel type employed. To obtain detailed particle data important for thermal spraying, mathematical models are developed in the present paper to predict the particle dynamic behavior in a liquid fuelled HVOF thermal spray gun. The particle transport equations are coupled with the three-dimensional, chemically reacting, turbulent gas flow, and solved in a Lagrangian manner. The melting and solidification within the particles as a result of heat exchange with the surrounding gas flow is solved numerically. The in-flight characteristics of WC–Co particles are studied and the effects of carrier gas parameters on particle behavior are examined. The results demonstrate that WC–Co particles smaller than 5 μm in diameter undergo melting and solidification prior to impact while most particles never reach liquid state during the HVOF thermal spraying. The flow rate of carrier gas has considerable influence on particle dynamics as well as deposition on substrate. At higher flow rate the powder particles are redirected further away from the substrate center, while smaller flow rate results in better heating, higher impact velocity and deposition closer to the substrate center.     

The effect of particle humidity on separation efficiency for an axial cyclone separator

The objective of this study is to investigate the effects of particle humidity on the inlet particle size distribution, overall efficiency, grade efficiency and cut size diameter for an axial cyclone separator with inner diameter of 150?mm. The collection and grade efficiencies of the cyclone separator were measured by on-line method for inlet velocities, particle concentration and particle humidity in the ranges of 12–18?m/s, 30–500?mg/m³ and 8–30‰, respectively. By employing a set of fixed parameters for inlet velocity and particle concentration, the effect of particle humidity on separation efficiency was investigated. The experimental results show that the volume ratio of larger particle increases with the increasing of particle humidity due to particle agglomeration. When the inlet velocity and particle humidity remain constant, the collection and grade efficiencies improve greatly as the increasing of the particle concentration because of the particle aggregation. However, it was noticed that the grade efficiencies did not always increased with the increasing of particle humidity under the same conditions of inlet velocity and particle concentration. The trends of grade efficiency curves for different particle humidity change at the particle diameter of approximately 10?μm. The grade efficiency improves with the increasing of particle humidity when the particle diameter is larger than 10?μm, while a contrary tendency is observed when the particle diameter is smaller than 10?μm.     

Modeling constitutive relationship of Ti40 alloy using artificial neural network

Constitutive relationship equation reflects the highly non-linear relationship of flow stress as function of strain, strain rate and temperature. It is a necessary mathematical model that describes basic information of materials deformation and finite element simulation. In this paper, based on the experimental data obtained from Gleeble-1500 Thermal Simulator, the constitutive relationship model for Ti40 alloy has been developed using back propagation (BP) neural network. The predicted flow stress values were compared with the experimental values. It was found that the absolute relative error between predicted and experimental data is less than 8.0%, which shows that predicted flow stress by artificial neural network (ANN) model is in good agreement with experimental results. Moreover, the ANN model could describe the whole deforming process better, indicating that the present model can provide a convenient and effective way to establish the constitutive relationship for Ti40 alloy.     

Preparation and evaluation of high drug content particles

To determine how to prepare high drug content particles using a Wurster fluidized bed to determine realizing the miniaturization of solid dosage forms, aspirin was selected as the model drug and granulated without any additive. In this study, the emphasis was on evaluating the key operation factors of airflow rate and atomizing flow volume. The properties of the resulting particles, such as the average diameter, particle strength, appearance, and compressibility using different airflow rates and atomizing flow volumes, were investigated. Furthermore, detailed optimization of the operation conditions was conducted by artificial neural network (ANN) analysis. The relationship between the controlling factors (powder supplied, concentration of spray liquid, the amount of consumed spray liquid, and spray rate) and the response variables (product yield, median diameter, angle of repose, and degradation of aspirin) was investigated after evaluating the airflow rate and atomizing flow volume effects. The resulting granules under optimum operation conditions showed excellent physicochemical properties such as particle size uniformity, flowability, and compressibility.