On the modelling of abrasive waterjet cutting

Abrasive waterjet cutting operates by the impingement of a high-velocity abrasive-laden waterjet against the workpiece. The jet is formed by mixing abrasive particles with high-velocity water in mixing tubes and is forced through a tiny sapphire orifice. The accelerated jet exiting the nozzle travels at more than twice the speed of sound and cuts as it passes through the workpiece.This cutting process is being developed as a net-shape and near-net-shape machining process for cutting many metals and hard-to-machine materials. The narrow kerf produced by the stream results in neither delimitation nor stresses along the cutting path. This new technology offers significant advantages over traditional processes for its ability to cut through most sections of dense or hard materials without the need for secondary machining, to produce contours, and to be integrated into computer-controlled systems.The abrasive waterjet cutting process involves a large number of process and material parameters which are related to the waterjet, the abrasive particles, and workpiece material. Those parameters are expected to effect the material removal rates and the depth of cut. The purpose of the present work is to propose a model which is capable of predicting the maximum depth of cut for different types of materials using different process parameters. A comparison of the results of the proposed model and the models reported in the literature is introduced along with a discussion of the limitations of those models.On leave from: Mechanical Engineering Department, Suez Canal University, Egypt.On leave from: Industrial Production Engineering Department, Mansoura University, Egypt.On leave from: Mechanical Power Engineering Department, Alexandria University, Egypt.     

磨料水射流切割混凝土的深度预测模型

在对磨料水射流切割混凝土分析基础上,应用BP人工神经网络理论,建立磨料水射流切割基于射流压力、靶距、磨料粒径、磨料流量、磨料喷嘴直径、磨料喷嘴长度及横移速度等射流参数的深度模型,通过模型预测结果与实验结果的比较,验证模型具有一定的精度,为实际运用和进一步研究提供参考。     

Effects of process parameters on surface roughness in abrasive waterjet cutting of aluminium

Abrasive waterjet cutting is a novel machining process capable of processing wide range of hard-to-cut materials. Surface roughness of machined parts is one of the major machining characteristics that play an important role in determining the quality of engineering components. This paper shows the influence of process parameters on surface roughness (R_a) which is an important cutting performance measure in abrasive waterjet cutting of aluminium. Taguchi’s design of experiments was carried out in order to collect surface roughness values. Experiments were conducted in varying water pressure, nozzle traverse speed, abrasive mass flow rate and standoff distance for cutting aluminium using abrasive waterjet cutting process. The effects of these parameters on surface roughness have been studied based on the experimental results.     

Computational fluid analysis of abrasive waterjet cutting head

Waterjet cutting is an appealing technology for cutting thick materials with zones that must not be affected by heat. This paper presents computational fluid dynamics (CFD) and theoretical analyses to optimize the mixing of components by the multi-phase approach. Water, air, and abrasives are mixed in a mixing chamber. This modeling is used to predict the influence of air and abrasives on the mixing at different distances within the mixing tube. At the same time, particle tracking was conducted to monitor the erosion rate density at the nozzle wall. Results show that nozzle length has an effect on the mixing of water, air, and the abrasives, and that the velocity of the waterjet influences the erosion rate at the nozzle wall. The k-ɛ turbulence model was used for simulation of the abrasive coupled with air. This investigation reveals that the erosion in the nozzle body is higher at the initial zone and that as the length of the nozzle length increases, the volume fraction of air increases accordingly. The entrance of the orifice is affected by a highly pressurized water stream (with minimal particulate matter), which causes chipping at the leading edge. To reduce the turbulence inside the mixing chamber, the use of a vacuum assist could be helpful, but precautions should be taken in order that the abrasives do not escape from the mixing chamber.     

磨料水射流切割质量的神经网络预测

磨料水射流切割质量影响因素较多,难以建立有效的理论模型,结合实验结果,建立磨料水射流切割质量的神经网络预测模型。结果表明,对于所给定切割参数,该模型能快速、准确、可靠地预测出切割质量。     

Fracture mechanics-based model of abrasive waterjet cutting for brittle materials

Advanced engineering ceramic materials such as silicon carbides and silicon nitride have been used in many engineering applications. The abrasive waterjet is becoming the most recent cutting technique of such materials because of its inherent advantages.In the present study, two elastic-plastic erosion models are adopted to develop an abrasive waterjet model for cutting brittle materials. As a result, two cutting models based on fracture mechanics are derived and introduced. The suggested models predict the maximum depth of cut of the target material as a function of the fracture toughness and hardness as well as the process parameters.It is found that both models predict the same depth of cut within a maximum of 11%, for the practical range of process parameters used in the present study. The maximum depth of cut predicted by the suggested models are compared with published experimental results for three types of ceramics. The effect of process parameters on the maximum depth of cut for a given ceramic material is also studied and compared with experimental work. The comparison reveals that there is a good agreement between the models' predictions and experimental results, where the difference between the predicted and experimental value of the maximum depth of cut is found to be an average value of 10%.Nomenclature C abrasive efficiency factor, see equation (16) - C ₁,C ₂ c ₁/4/3, c₂/4/3 - c ₁,c ₂ erosion models constants, see equations (1) and (2) - d _a local effective jet diameter - d _j nozzle diameter - d _S infinitesimal length along the kerf - f ₁ ( _E ) function defined by equation (7) - f ₂ ( _E ) function defined by equation (8) - f ₃ ( _e ) function defined by equation (14) - g ₁ ( _E ) f ₁( _e )/f ₃ ² ( _e ) - g ₂ ( _e ) f ₂( _e /f ₃ ² ( _e ) - H Vickers hardness of the target material - h maximum depth of cut - K _c fracture toughness of target material - k kerf constant - M linear removal rate, dh/dt - m mass of a single particle - abrasive mass flow rate - water mass flow rate - P water pressure - Q total material removal rate, see equation (11) - R abrasive to water mass flow rates - r particle radius - S kerf length - u traverse speed - V material volume removal rate (erosion rate) - V idealised volume removal by an individual abrasive particle - particle impact velocity - ₀ initial abrasive particle velocity - x,y kerf coordinates - local kerf angle, Fig. 1 - _E jet exit angle at the bottom of the workpiece, Fig. 1 - particle density - _w water density On leave from: Mechanical Engineering Department, Suez Canal University, Egypt.On leave from: Mechanical Power Engineering Department, Alexandria University, Egypt.     

A study of abrasive waterjet cutting of alumina ceramics with controlled nozzle oscillation

This paper presents and discusses an experimental investigation of abrasive waterjet (AWJ) cutting of alumina ceramics with controlled nozzle oscillation. Particular attention is paid to the effect of small oscillation angles on the various cutting performance measures. It is found that nozzle oscillation at small angles can equally improve the major cutting performance measures, if the cutting parameters are correctly selected. However, under high water pressures, high nozzle traverse speeds and large oscillation frequencies, nozzle oscillation may cause a decrease in some major cutting performance measures, such as surface finish. Plausible trends of cutting performance with respect to the process parameters are further considered. Finally, a predictive mathematical model for the depth of cut is developed and verified.     

Experiment on carbon fiber–reinforced plastic cutting by abrasive waterjet with specific emphasis on surface morphology

In the machining of carbon fiber–reinforced plastic by abrasive waterjet, the surface morphology of the cutting front directly reflects the processin     

An investigation on use of colemanite powder as abrasive in abrasive waterjet cutting (AWJC)

In the present study, the cutting performance outputs (surface roughness, surface waviness and kerf taper angle) of colemanite powder as abrasive in abrasive waterjet cutting (AWJC) with varying traverse rate and abrasive flow rate were investigated experimentally. The performance outputs were compared to that of garnet which is in common use in industry as abrasive in AWJC industry. Al7075, marble, glass, Ti6Al4V and a composite material were selected as sample materials in the experiments. Furthermore, colemanite powder was mixed with garnet powder at certain proportions and the obtained surface characteristics were compared with those cut with pure garnet powder. It is found experimentally that in spite of higher amount of colemanite powder consumption with respect to garnet to perform the same cutting action, the colemanite powder could be an alternative powder for AWJC process.     

Depth of cut models for multipass abrasive waterjet cutting of alumina ceramics with nozzle oscillation

An experimental study of the depth of cut in multipass abrasive waterjet (AWJ) cutting of alumina ceramics with controlled nozzle oscillation is presented. It is found that this cutting technique can significantly increase the depth of cut by an average of 50.8% as compared to single pass cutting without nozzle oscillation under the corresponding cutting conditions and within the same cutting time. Predictive models for the depth of cut are then developed. The modelling process starts with single pass cutting using a dimensional analysis technique and the particle erosion theories applied to alumina ceramics, before progressing to the development of the models for multipass cutting. The models are finally assessed both qualitatively and quantitatively with experimental data. It is shown that the model predictions are in good agreement with the experimental data with the average deviations of about 1%.     

Depth of cut models for multipass abrasive waterjet cutting of alumina ceramics with nozzle oscillation

An experimental study of the depth of cut in multipass abrasive waterjet (AWJ) cutting of alumina ceramics with controlled nozzle oscillation is presented. It is found that this cutting technique can significantly increase the depth of cut by an average of 50.8% as compared to single pass cutting without nozzle oscillation under the corresponding cutting conditions and within the same cutting time. Predictive models for the depth of cut are then developed. The modelling process starts with single pass cutting using a dimensional analysis technique and the particle erosion theories applied to alumina ceramics, before progressing to the development of the models for multipass cutting. The models are finally assessed both qualitatively and quantitatively with experimental data. It is shown that the model predictions are in good agreement with the experimental data with the average deviations of about 1%.     

Influence of clamping force on the machined surface in abrasive finishing

On the basis of the Preston hypothesis, it is possible to establish variation of the clamping force in the course of machining such that the contact pressure is stabilized and the productivity is increased. In the finishing of planes with different initial microrelief, the time dependence of the contact area is found to be exponential. The assumptions made in the analysis are experimentally verified in abrasive finishing on a Rastr 220 machine. With exponential variation in the force — that is, variation analogous to that of the contact area in abrasive finishing—the productivity is increased by a factor of 2.5–3.     

Predictive depth of jet penetration models for abrasive waterjet cutting of alumina ceramics

A study of the depth of jet penetration (or depth of cut) in abrasive waterjet (AWJ) cutting of alumina ceramics with controlled nozzle oscillation is presented and discussed. An experimental investigation is carried out first to study the effects of nozzle oscillation at small angles on the depth of cut under different combinations of process parameters. Based on the test conditions, it is found that nozzle oscillation at small angles can improve the depth of cut by as much as 82% if the cutting parameters are correctly selected. Depending on the other cutting parameters in this study, it is found that a high oscillation frequency (10–14 Hz) with a low oscillation angle (4–6°) can maximize the depth of cut. Using a dimensional analysis technique, predictive models for jet penetration when cutting alumina ceramics with and without nozzle oscillation are finally developed and verified. It is found that the model predictions are in good agreement with the experimental results with the average percentage errors of less than 2.5%.     

淹没磨料射流对金属材料切割性能影响的实验研究

在完全淹没条件下,以Q235号钢板为例,对射流压力、横移速度、靶距、磨料目数、喷嘴型号等主要切割参数进行了考察,分析了这些参数对金属。料切割深度的影响,为水下切割技术提供一些有价值的参考。     

Artificial neural network and regression models for performance prediction of abrasive waterjet in rock cutting

An experimental study is carried out for modeling the rock cutting performance of abrasive waterjet. Kerf angle (KA) is considered as a performance criteria and modeled using artificial neural network (ANN) and regression analysis based on operating variables. Three operating variables, including traverse speed, standoff distance, and abrasive mass flow rate, are studied for obtaining different results for the KA. Data belonging to the trials are used for construction of ANN and regression models. The developed models are then tested using a test data set which is not utilized during construction of models. Additionally, the regression model is validated using various statistical approaches. The results of regression analysis are also used to determine the significant operating variables affecting the KA. Furthermore, the performances of derived models are compared for showing the accuracy levels in prediction of the KA. As a result, it is concluded that both ANN and regression models can give adequate prediction for the KA with an acceptable accuracy level. The compared results reveal also that the corresponding ANN model is more reliable than the regression model. On the other hand, the standoff distance and traverse speed are statistically determined as dominant operating variables on the KA, respectively.     

微通道反应器沟槽底面的磨料水射流抛光研究

针对燃料电池微通道反应器的沟槽底面抛光技术难题,开展磨料水射流沟槽抛光仿真与试验研究.采用FLUENT软件,对不同工艺参数下沟槽底部剪切力分布进行了数值模拟;根据仿真结果进行316L不锈钢材料的单沟槽抛光工艺试验,检测分析不同抛光参数下单沟槽底面形貌、材料去除率以及表面粗糙度的变化规律;根据单沟槽底面几何精度和表面粗糙...     

Numerical simulation of single particle acceleration process by SPH coupled FEM for abrasive waterjet cutting

The existing numerical simulations of hydrodynamic characteristics of abrasive waterjet in a cutting head were mainly based on Eulerian grid or arbitrary Lagrange–Eulerian grid method to establish computational fluid dynamics models. However, using these two methods, the abrasive and water were premixed and given an identical initial velocity, which were different from the mixing and acceleration processes of abrasive in the cutting head. This paper presents a more suitable numerical model that the abrasive particle enters into the mixing chamber in a low velocity and is accelerated in the focus tube by a high-speed waterjet from the orifice. In order to model this mixing-and-acceleration process of abrasive and high-speed waterjet, the smooth particle hydrodynamics (SPH) coupled finite element method (FEM) is adopted, in which SPH particles are used to model the high-speed waterjet to adapt its extremely large deformation and FEM is applied to model the discrete abrasive particle, cutting head, and workpiece. As a result, evolution of abrasive and waterjet velocities along focus tube is analyzed; trajectory of single abrasive particle in focus tube is sighted; the relationships between abrasive particle velocities and different water pressures are described; the rule of outlet velocities of abrasive particle vs. dimensionless ratio of diameter is conducted; depth of penetration caused by single abrasive particle impact is obtained. The current model is validated by the existing theoretical and experimental data.     

An adaptive control strategy for the abrasive waterjet cutting process with the integration of vision-based monitoring and a neuro-genetic control strategy

This paper presents an integrated approach for the monitoring and control of abrasive waterjet (AWJ) cutting process. A machine-vision-based monitoring approach was proposed to obtain the bore diameter of the focusing nozzle from time to time. A neuro-genetic approach, proposed by Srinivasu and Ramesh Babu (Appl Soft Comput 8(1):809–819, 2008) was employed as a control strategy to modify the process parameters, such as water pressure, abrasive flow rate, and jet traverse rate, so as to maintain the desired depth of cut, with changes in the diameter of the focusing nozzle monitored with a machine vision system. By combining the monitoring and control strategies, an integrated approach for adaptive control of AWJ cutting process is realized. The effectiveness of the proposed integrated approach for adaptive control of AWJ cutting process was shown by comparing the results obtained from the experiments with the process parameters suggested by the control strategy to achieve the desired depth of cut. From the results of the study, it is seen that the proposed monitoring system is capable of monitoring the focusing nozzle diameter with a mean absolute deviation of 0.05 mm and that the neuro-genetic strategy is capable of modifying the controllable process parameters to maintain the desired depth of cut with a mean absolute deviation of 0.87 mm.     

ANFIS modeling of surface roughness in abrasive waterjet machining of carbon fiber reinforced plastics

Journal of Mechanical Science and Technology - This study discusses the development of an Adaptive neuro–fuzzy inference system (ANFIS) model for determining the surface roughness (Ra) during...