Prediction of Temperature Distribution in Orthogonal Machining Based on the Mechanics of the Cutting Process Using a Constitutive Model

Abstract

This paper presents an original method of predicting temperature distribution in orthogonal machining based on a constitutive model of various materials and the mechanics of their cutting process. Currently, temperature distribution is commonly investigated using arduous experiments, computationally inefficient numerical analyses, and complex analytical models. In the method proposed herein, the average temperatures at the primary shear zone (PSZ) and the secondary shear zone (SSZ) were determined for various materials, based on a constitutive model and a chip-formation model using measurements of cutting force and chip thickness. The temperatures were determined when differences between predicted shear stresses using the Johnson-Cook constitutive model (J-C model) and those using a chip-formation model were minimal. J-C model constants from split Hopkinson pressure bar (SHPB) tests were adopted from the literature. Cutting conditions, experimental cutting force, and chip thickness were used to predict the shear stresses. The temperature predictions were compared to documented results in the literature for AISI 1045 steel and Al 6082-T6 aluminum in multiple tests in an effort to validate this methodology. Good agreement was observed for the tests with each material. Thanks to the reliable and easily measurable cutting forces and chip thicknesses, and the simple forms of the employed models, the presented methodology has less experimental complexity, less mathematical complexity, and high computational efficiency.

Mechanism of Crack Propagation for K9 Glass

“…The marerials constants in the JC model, ZA model and JH-2model have variations because of differenet determination methodologies. The constants in JC and ZA model are considered the influence of temperature [18], but the constants in JH-2 model are defined in room temperature because the temperature have no influence on the brittle materials almostly. The variations will become a source for prediction errors in modeling work.…”

Analytical Modeling of the Temperature Using Uniform Moving Heat Source in Planar Induction Heating Process

“…However, the coil required for the planar induction heating is significantly different from the traditional spiral coils, in which the magnetic field distribution is difficult to effectively concentrated, the air impedance of the system loop is too large and the heating temperature is not uniform and difficult to control accurately [5][6][7]. The efficiency of the planar induction heating extensively depends on the effective conversion of the electromagnetic field of the coil and the reasonable matching of the In recent years, in order to apply the induction heating process more effectively, many scholars have conducted more research on induction heating [11][12][13][14][15][16][17][18][19], including numerical modeling of induction heating process and electromagnetic field conversion mechanism analysis. Numerical approaches are adopted in the power distribution and temperature prediction during induction heating process [11][12][13][14][15].…”

“…In addition, analytical approaches are also adapted in the research of various fields. The analytical approaches have less computational time than finite element simulation and thus have a relatively high efficiency [16,17]. Computational efficiency also depends on the mathematical complexity of the analytical model.…”

Evaluation of an Analytical Model in the Prediction of Machining Temperature of AISI 1045 Steel and AISI 4340 Steel

“…Ning J. et al presented an original analytical model to predict the average temperatures at PSZ and SSZ in the orthogonal cutting process. This temperature model was developed based on the Johnson-Cook constitutive model (J-C model) and mechanics of the orthogonal cutting process [24]. J-C model was employed in the temperature model because it is effective, simple and easy-to-use.…”