Recent advances in modelling of metal machining processes

A comparative study on Johnson–Cook, modified Johnson–Cook and Arrhenius-type constitutive models to predict the high temperature flow stress in 20CrMo alloy steel

Determination of Johnson–Cook parameters from machining simulations

Consistent and reasonable characterization of the material behavior under the coupled effects of strain, strain rate and temperature on the material flow stress is remarkably crucial in order to design as well as optimize the process parameters in the metal forming industrial practice. The objective of this work was to formulate an appropriate flow stress model to characterize the flow behavior of AISI-1045 medium carbon steel over a practical range of deformation temperatures (650⁻950 ∘ C) and strain rates (0.05⁻1.0 s - 1 ). Subsequently, the Johnson-Cook flow stress model was adopted for modeling and predicting the material flow behavior at elevated temperatures. Furthermore, surrogate models were developed based on the constitutive relations, and the model constants were estimated using the experimental results. As a result, the constitutive flow stress model was formed and the constructed model was examined systematically against experimental data by both numerical and graphical validations. In addition, to predict the material damage behavior, the failure model proposed by Johnson and Cook was used, and to determine the model parameters, seven different specimens, including flat, smooth round bars and pre-notched specimens, were tested at room temperature under quasi strain rate conditions. From the results, it can be seen that the developed model over predicts the material behavior at a low temperature for all strain rates. However, overall, the developed model can produce a fairly accurate and precise estimation of flow behavior with good correlation to the experimental data under high temperature conditions. Furthermore, the damage model parameters estimated in this research can be used to model the metal forming simulations, and valuable prediction results for the work material can be achieved.

Johnson Cook Material and Failure Model Parameters Estimation of AISI-1045 Medium Carbon Steel for Metal Forming Applications

This paper presents an original method to inversely identify the Johnson–Cook model constants (J-C constants) of ultra-fine-grained titanium (UFG Ti) based on a chip formation model and an iterative gradient search method using Kalman filter algorithm. UFG Ti is increasingly finding usefulness in lightweight engineering applications and medical implant filed because of its sufficient mechanical strength, high manufacturability, and high biocompatibility. Johnson–Cook model is one of the constitutive models widely used in analytical modeling of machining force, temperature, and residual stress because it is effective, simple, and easy to use. Currently, the J-C constants of UFG Ti are unavailable and yet an effective identification methodology based upon machining data is not readily available. In this work, multiple cutting tests were conducted under different cutting conditions, in which machining forces were experimentally measured using a piezoelectric dynamometer. The machining forces were also predicted using the chip formation model with inputs of cutting conditions, workpiece material properties, and a set of given model constants. An iterative gradient search method was enforced to find the J-C constants when the difference between predicted forces and experimental forces reached an acceptable low value. To validate the identified J-C constants, machining forces were predicted using the identified J-C constants under different cutting conditions and then compared to the corresponding experimental forces. Close agreements were observed between predicted forces and experimental forces. Considering the simple orthogonal cutting tests, reliable and easily measurable machining forces, and efficient iterative gradient search method, the proposed method has less experimental complexity and high computational efficiency.

Inverse determination of Johnson–Cook model constants of ultra-fine-grained titanium based on chip formation model and iterative gradient search

Metastable beta titanium alloys combine light weight, high strength, and excellent corrosion and fatigue resistance, and can therefore be very useful in many demanding applications. However, they are also difficult to machine and the machining costs of titanium components can be significant compared to the overall costs of the component. Finite element simulations can be used to optimize the cutting conditions and reduce the machining costs. However, any attempt to simulate the rather complex machining processes needs reliable material models that can only be generated when the mechanical behavior of the material is understood well. In this work, the mechanical properties and behavior of titanium 15-3 alloy was studied in a wide range of strain rates and temperatures, and a constitutive model was generated for simulating orthogonal cutting of the alloy. The strain-hardening rate of Ti-15-3 is a strong function of strain rate, and it decreases rapidly as the strain rate is increased. Also, the strain rate sensitivity of the material was found to depend strongly on temperature. Johnson–Cook plasticity model, based on isothermal stress–strain curves, was used to model the behavior of the material. The isothermal stress–strain response was calculated from the experimental data, and the model used in the simulations was modified to account also for the adiabatic heating and consequent thermal softening of the material. The current model is able to simulate the serrated chip formation frequently observed for titanium alloys at high cutting speeds.

Characterization and numerical modeling of high strain rate mechanical behavior of Ti-15-3 alloy for machining simulations

Titanium alloys and nickel based superalloys are used in various demanding applications because of their excellent high temperature properties, especially high strength and good corrosion and fatigue resistance. However, the high strength and hardness at high temperatures combined with strong strain hardening can lead to difficulties in machining of these alloys. Finite element simulations can be used to optimize the cutting conditions and to reduce the machining costs. However, simulations of machining operations require accurate material models that can only be built on reliable experimental data. Also, the mechanical properties of materials can only be measured in a limited range of strain and strain rate at the laboratory scale, from which the material behavior has to be extrapolated to the actual machining range. In this work, the mechanical behavior of Titanium-6246 and a nickel based superalloy, similar to Inconel 625, has been studied in details. The Johnson-Cook material model parameters were obtained from the experimental data and the model was used to describe the plastic behavior of the studied alloys in simulations of orthogonal cutting of the material. The model for the Ni- based superalloy was improved by introducing an additional strain softening term that allows decreasing of the strain hardening rate at large deformations. The preliminary simulation results have also been verified experimentally by comparing the simulation results with machining experiments, and the results of the simulations are briefly presented and discussed. The material models are able to reproduce the serrated chips with split shear bands, but the cutting stresses obtained from the simulations are somewhat higher than those obtained from the cutting experiments. Also, some differences were observed in the chip shape, and further development of the material model and simulations is needed.

Dynamic Behavior and High Speed Machining of Ti-6246 and Alloy 625 Superalloys: Experimental and Modeling Approaches

Material laws are central to any machining simulation. Johnson-Cook material law, owing to its simplicity, has often been used for machining simulations. However, at high strain rates (∼ 106 s-1) which are normally encountered during high speed machining, the same Johnson-Cook parameters are used for simulation which are usually measured at much lower strain rates. A possible solution to this problem is to conduct inverse simulation experiments to deduce the Johnson-Cook parameters. At high cutting speeds the chip formation takes place very rapidly and is essentially adiabatic. Thus through the study of the adiabatic stress-strain curves one can deduce information about the chip formation process [1]. In this numerical study, different sets of Johnson-Cook parameters that give rise to almost identical adiabatic stress-strain curves are identified by using the Levenberg-Marquardt optimization algorithm. High-speed machining simulations performed with these parameters show almost indistinguishable results, indicating that uniquely identifying material parameters from inverse analysis may be difficult.

Aviral Shrot

Papers

Determination of Johnson–Cook parameters from machining simulations

Characterization and numerical modeling of high strain rate mechanical behavior of Ti-15-3 alloy for machining simulations

Dynamic Behavior and High Speed Machining of Ti-6246 and Alloy 625 Superalloys: Experimental and Modeling Approaches

Is it possible to identify Johnson-Cook law parameters from machining simulations?

Inverse parameter identification with finite element simulations using knowledge-based descriptors