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FE Modeling for Single Spark in EDM Considering Plasma Flushing Efficiency

机译:考虑等离子体冲洗效率的EDM中单火花的FE模型

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Due to complex nature of single spark phenomenon in EDM, the removal mechanism needs better comprehension and clarity. In this context, this work presents a finite element simulation of a single spark during electrical discharge machining taking into consideration significant aspects such as temperature dependency of material properties, Gaussian distribution of heat flux, plasma channel radius varying with current and discharge duration, and variability in factors such as cathode energy fraction, and plasma flushing efficiency. Such a model can offer a better prediction of the crater profile obtained on the work surface which enables it to be extended to multi-spark scenarios for predicting the surface texture obtained through EDM process. FE simulations showed that the crater radius and crater depth increases with increasing values of the operating parameters such as discharge current and pulse on-time. It is also observed that the crater aspect ratio (r_c/d_c), which is the ratio between crater radius and crater depth, shows a high value at low values of discharge current and pulse on-time. This is due to feeble penetration of heat through the cathode body for low values of the operating parameters. The validation of the FE model is made against experiments and it was found that the model displays improved prediction at high values of the operating parameters. The error in prediction of r_c/d_c by the model varies from 9.1 to 13.4% which represents a good prediction of crater profile by the model.
机译:由于EDM中单火花现象的复杂性,去除机制需要更好的理解和清晰度。在这种情况下,在考虑到诸如材料特性的温度依赖性的显着方面,在电气放电加工过程中,该工作呈现了单个火花的有限元模拟,例如材料特性的温度依赖性,加热通量的高斯分布,等离子体通道半径随电流和放电持续时间而变化,以及可变性在阴极能量分数等因素中,等离子体冲洗效率。这种模型可以提供更好地预测工作表面上获得的火山口曲线,这使得它能够扩展到多个火花场景,以预测通过EDM过程获得的表面纹理。 FE模拟表明,火山口半径和火山口深度随着操作参数的增加而增加,例如放电电流和脉冲。还观察到,该火山口纵横比(R_C / D_C),即火山口半径和火山口深度之间的比率,显示出在低放电电流和脉冲的低值下的高值。这是由于热量通过阴极体的弱渗透,以用于操作参数的低值。 FE模型的验证是针对实验进行的,发现该模型在操作参数的高值下显示改进的预测。模型的R_C / D_C预测的错误变化从9.1到13.4%,这代表了模型的良好预测火山口谱。

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