On the basis of the wave energy balance equation, the response model of mean directions of locally wind-generated waves in slowly turning wind fields has been derived. The results show that in a homogeneous field, the...On the basis of the wave energy balance equation, the response model of mean directions of locally wind-generated waves in slowly turning wind fields has been derived. The results show that in a homogeneous field, the time scale of the response is not only related to the rate of wave growth, but also to the directional energy distribution and the angle between the wind direction and the mean wave direction. Furthermore, the law of change in the mean wave direction has been derived. The numerical computations show that the response of wave directions to slowly turning wind directions can be treated as the superposition of the responses of wave directions to a series of sudden small-angle changes of wind directions and the turning rate of the mean wave direction depends on the turning rate and the total turning angles of the wind direction. The response of wave directions is in agreement with the response for a sudden change of wind directions if the change in wind directions is very fast. Based on the normalized rates of wave growth under local winds presented by Wen et al. (1989), a quantitative estimate of the time scale of the response shows that the relationships between the dimensionless time scale and both the dimensionless total wave energy and the dimensionless peak frequency agree fairly well with the observations in comparison with other models.展开更多
There are many advanced tooling approaches in metal cutting to enhance the cutting tool performance for machining hard-to-cut materials. The self propelled rotary tool （SPRT） is one of the novel approaches to improv...There are many advanced tooling approaches in metal cutting to enhance the cutting tool performance for machining hard-to-cut materials. The self propelled rotary tool （SPRT） is one of the novel approaches to improve the cutting tool performance by providing cutting edge in the form of a disk, which rotates about its principal axis and provides a rest period for the cutting edge to cool and allow engaging a fresh cutting edge with the work piece. This paper aimed to present the cutting performance of SPRT while turning hardened EN24 steel and optimize the machining conditions. Surface roughness （Ra） and metal removal rate （rMMR） are considered as machining perfor- mance parameters to evaluate, while the horizontal incli- nation angle of the SPRT, depth of cut, feed rate and spindle speed are considered as process variables. Initially, design of experiments （DOEs） is employed to minimize the number of experiments. For each set of chosen process variables, the machining experiments are conducted on computer numerical control （CNC） lathe to measure the machining responses. Then, the response surface method- ology （RSM） is used to establish quantitative relationships for the output responses in terms of the input variables. Analysis of variance （ANOVA） is used to check the adequacy of the model. The influence of input variables on the output responses is also determined. Consequently, these models are formulated as a multi-response optimi- zation problem to minimize the Ra and maximize the rMMR simultaneously. Non-dominated sorting genetic algorithm-II （NSGA-II） is used to derive the set of Pareto-optimal solutions. The optimal results obtained through the pro- posed methodology are also compared with the results of validation experimental runs and good correlation is found between them.展开更多
文摘On the basis of the wave energy balance equation, the response model of mean directions of locally wind-generated waves in slowly turning wind fields has been derived. The results show that in a homogeneous field, the time scale of the response is not only related to the rate of wave growth, but also to the directional energy distribution and the angle between the wind direction and the mean wave direction. Furthermore, the law of change in the mean wave direction has been derived. The numerical computations show that the response of wave directions to slowly turning wind directions can be treated as the superposition of the responses of wave directions to a series of sudden small-angle changes of wind directions and the turning rate of the mean wave direction depends on the turning rate and the total turning angles of the wind direction. The response of wave directions is in agreement with the response for a sudden change of wind directions if the change in wind directions is very fast. Based on the normalized rates of wave growth under local winds presented by Wen et al. (1989), a quantitative estimate of the time scale of the response shows that the relationships between the dimensionless time scale and both the dimensionless total wave energy and the dimensionless peak frequency agree fairly well with the observations in comparison with other models.
文摘There are many advanced tooling approaches in metal cutting to enhance the cutting tool performance for machining hard-to-cut materials. The self propelled rotary tool （SPRT） is one of the novel approaches to improve the cutting tool performance by providing cutting edge in the form of a disk, which rotates about its principal axis and provides a rest period for the cutting edge to cool and allow engaging a fresh cutting edge with the work piece. This paper aimed to present the cutting performance of SPRT while turning hardened EN24 steel and optimize the machining conditions. Surface roughness （Ra） and metal removal rate （rMMR） are considered as machining perfor- mance parameters to evaluate, while the horizontal incli- nation angle of the SPRT, depth of cut, feed rate and spindle speed are considered as process variables. Initially, design of experiments （DOEs） is employed to minimize the number of experiments. For each set of chosen process variables, the machining experiments are conducted on computer numerical control （CNC） lathe to measure the machining responses. Then, the response surface method- ology （RSM） is used to establish quantitative relationships for the output responses in terms of the input variables. Analysis of variance （ANOVA） is used to check the adequacy of the model. The influence of input variables on the output responses is also determined. Consequently, these models are formulated as a multi-response optimi- zation problem to minimize the Ra and maximize the rMMR simultaneously. Non-dominated sorting genetic algorithm-II （NSGA-II） is used to derive the set of Pareto-optimal solutions. The optimal results obtained through the pro- posed methodology are also compared with the results of validation experimental runs and good correlation is found between them.
