Papers by Author: Yasser M. Ali

Abstract: An experimental study of a radial-mode abrasive waterjet (AWJ) turning of AISI4340 high tensile steel is presented. The major process parameters, i.e. feed speed, waterjet pressure, abrasive flow rate, nozzle tilt angle, and workpiece surface speed, are considered in a statistical experimental design. The advantages of the radial-mode AWJ turning over the offset-mode turning include maximum jet energy utilization, high surface speed, a variety of nozzle tilt angles and small nozzle standoff distance, to enable high material removal rate (MRR). It is found that the depth of cut is considerably increased when large nozzle tilt angle and high surface speed are used. It also shows that feed speed and waterjet pressure are the two most significant parameters to control the MRR. This preliminary study suggests that the radial-mode AWJ turning is feasible and can yield high material removal rates. Future research to advance the knowledge about this new machining process is also proposed.

Abstract: Most existing models for abrasive jet machining (AJM) are based on erosion models for either ductile or brittle materials. This classification imposes some limitations, because most materials are neither absolutely ductile nor absolutely brittle, but lay within the continuous spectrum between those two idealizations. This work reports recent progress in the modeling of erosion processes for real materials, and discusses the implications of a new model in estimating the performance of AJM. The new model is more capable in explaining the effects of jet velocity, abrasive particle size, and various material properties on the efficiency of the cutting process.

Abstract: Owing to its various distinct advantages over the other machining technologies, abrasive jet machining has become a promising machining technology for brittle and hard-to-machine materials. An experimental study is presented on the micro-grooving of quartz crystals using an abrasive airjet. The effect of the various process parameters on the major machining performance measures are analysed to provide a deep understanding of this micro-machining process. Predictive models are then developed for quantitatively estimating the machining performance. The models are finally verified by an experiment. It shows that the model predictions are in good agreement with the experimental results under the corresponding conditions.