Characterization on vermicular graphite rate and tensile strength in vermicular graphite cast iron based on nonlinear ultrasonic technique.

Ultrasonic techniques have been widely used to detect the percentage of vermicular graphite, defects, etc. in vermicular graphite cast iron. The linear ultrasonic velocity method is the main ultrasonic method for characterizing vermicular graphite rate and tensile strength in the current study, however, it is often easy to misjudge the vermicular graphite rate due to its insignificant variation. This study explores the feasibility of using the nonlinear ultrasonic technique (NUT) to characterize the vermicular graphite rate and tensile strength. Based on the longitudinal critically refracted (LCR) wave detection model, an experimental study to detect the vermicular graphite rate and tensile strength of vermicular graphite cast iron is carried out using the nonlinear ultrasonic harmonic method, and compared with the ultrasonic velocity method. The experiment results show that the relative nonlinear parameter of the LCR wave decreases along with the increase of vermicular graphite rate and increases along with the increase of tensile strength, and it has higher detection sensitivity and resolution than ultrasonic velocity by analyzing the obtained data. The increase in the acoustic nonlinearity parameter (ANP) is related to the increase in the number of grain boundaries in the microstructure. Therefore, the relationship among microstructure, ANP, and mechanical properties of vermicular graphite cast iron can be established, and it's promising that a new approach might be developed for quickly detecting the vermicular graphite rate and corresponding tensile strength with the NUT.

Multi-response optimization of process parameters in nitrogen-containing gray cast iron milling process based on application of non-dominated ranking genetic algorithm.

As a new, high-strength and clean cast iron material, nitrogen-containing gray cast iron has excellent properties and a wide range of application prospects. However, the excellent material properties of the material not only make the machinability challenging, but also the high efficiency and quality of the machining process is a pressing issue. Therefore, it is necessary to study the machining characteristics of nitrogen-containing gray cast iron to obtain the optimal machining parameters to enrich the research work on nitrogen-containing gray cast iron. In this paper, the machining characteristics of nitrogen-containing gray cast iron are systematically studied, and the effects of cutting parameters on milling force, milling temperature, and surface roughness are analyzed. And, based on the machinability assessment, the objective function weights under different production requirements are determined by using hierarchical analysis trade-offs, and an integrated optimization model based on non-dominated ranking genetic algorithm and hierarchical analysis (AHP) is proposed. The model outputs the optimal combination of milling parameters by inputting the cutting speed (vc), feed rate per tooth (fz) and cutting depth (ap), surface roughness and cutting efficiency as the objective functions. The experimental results show that cutting depth has the greatest effect on the cutting force and cutting speed has the greatest effect on the cutting temperature and the surface roughness. The passivation effect of nitrogen on the graphite tip resulted in an increase in both cutting force and cutting temperature. The parameter optimization results indicated that the optimized roughing parameters significantly improve the surface quality while machining efficiently; the optimized finishing parameters improve Ra by 23.53% while ensuring higher MRR, which can achieve efficient and high-quality machining under different production requirements and provide an experimental basis for practical engineering applications of nitrogen-containing gray cast iron.