Considering multiple process observables to determine material model parameters for FE-cutting simulations

Hardt, M.; Bergs, Thomas

doi:10.1007/s00170-021-06845-6

Cited by 8 publications

(5 citation statements)

References 38 publications

(56 reference statements)

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“…For modeling the plasticity of the workpiece, the Johnson-Cook constitutive model was utilized. The Johnson-Cook model is one of the most commonly used material model for cutting simulations [14]. Its mathematical expression is shown in Eq.…”

Section: Simulation Of Specific Cutting Forcesmentioning

confidence: 99%

Investigation of the Cutting Uid'S Ow and its Thermomechanical Effect on the Cutting Zone Based on Uid-Structure Interaction (FSI) Simulation

Liu

Meurer

Schraknepper

et al. 2021

Preprint

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Cutting fluids are an important part of today's metal cutting processes, especially when machining aerospace alloys. They offer the possibility to extend tool life and improve cutting performance. However, the equipment and handling of cutting fluids also raises manufacturing costs. To reduce the negative impact of the high cost of cutting fluids, cooling systems and strategies are constantly being optimized. In most existing works, the influences of different cooling strategies on the relevant process parameters, such as tool wear, cutting forces, chip breakage, etc., are empirically investigated. Due to the limitations of experimental methods, analysis and modeling of the working mechanism has so far only been carried out at a relatively abstract level. For a better understanding of the mechanism of cutting fluids, a thermal coupled two-dimensional simulation approach for the orthogonal cutting process was developed in this work. This approach is based on the Coupled Eulerian Lagrangian (CEL) method and provides a detailed investigation of the cutting fluid’s impact on chip formation and tool temperature. For model validation, cutting tests were conducted on a broaching machine. The simulation resolved the fluid behavior in the cutting area and showed the distribution of convective cooling on the tool surface. This work demonstrates the potential of CEL based cutting fluid simulation, but also pointed out the shortcomings of this method.

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Section: Simulation Of Specific Cutting Forcesmentioning

confidence: 99%

Investigation of the Cutting Uid'S Ow and its Thermomechanical Effect on the Cutting Zone Based on Uid-Structure Interaction (FSI) Simulation

Liu

Meurer

Schraknepper

et al. 2021

Preprint

Self Cite

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“…The authors claim the approach can inversely re-identify the parameters of the constitutive model in a few iterations when compared with his earlier work [23]. In [25], Hardt et al extended his work to include the automation of the post-processing of the results and increased the number of observables in the objective function. The authors concluded that different parameter sets identified by the algorithm result in the prediction of identical temperature, stress, and strain profiles, highlighting the non-uniqueness.…”

Section: Introductionmentioning

confidence: 99%

Identification of the Parameter Values of the Constitutive and Friction Models in Machining Using EGO Algorithm: Application to Ti6Al4V

Palanisamy

Rivière-Lorphèvre

Gobert

et al. 2022

Metals

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The application of artificial intelligence and increasing high-speed computational performance is still not fully explored in the field of numerical modeling and simulation of machining processes. The efficiency of the numerical model to predict the observables depends on various inputs. The most important and challenging inputs are the material behavior of the work material and the friction conditions during the cutting operation. The parameters of the material model and the friction model have a decisive impact on the simulated results. To reduce the expensive experimentation cost that gives limited data for the parameters, an inverse methodology to identify the parameter values of those inputs is suggested to potentially have data of better quality. This paper introduces a novel approach for the inverse identification of model parameters by implementing the Efficient Global Optimization algorithm. In this work, a method relying on a complete automated Finite Element simulation-based optimization algorithm is implemented to inversely identify the value of the Johnson–Cook (JC) parameters and Coulomb’s friction coefficient correlatively, where the objective function is defined as minimizing the error difference between experimental and numerical results. The Ti6Al4V Grade 5 alloy material is considered as a work material, and the identified parameters sets are validated by comparing the simulated results with experimental results. The developed automation process reduces the computation time and eliminating human errors. The identified model parameters value predicts the cutting force as 169 N/mm (2% deviation from experiments), feed force as 55 N/mm (7% deviation from experiments), and chip thickness as 0.150 mm (11% deviation from experiments). Overall, the identified model parameters set improves the prediction accuracy of the finite element model by 32% compared with the best-identified parameters set in the literature.

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“…With the recent progress of computer and software science, finite element technology has been extensively adopted in the cutting field, providing support for the study of chip formation, cutting temperature prediction, microstructure evolution, cutting force and residual stress. 23–33 At present, finite element technology is generally regarded as an indispensable method for investigating the cutting mechanisms of titanium alloys. 34–42 Hu et al 34 established a 2D finite element model to explore the effect of the ultrasonic method on the ultra-precision cutting of Ti6Al4V alloy under different cutting conditions.…”

Section: Introductionmentioning

confidence: 99%

Influence of different cutting edges caused by tool wear on cutting process of titanium alloy TC21 based on finite element model

Zhu

Qian

2022

Proceedings of the Institution of Mechanical Engineers, Part B:

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Titanium alloys have emerged as a significant aerospace material due to the high strength, good corrosion resistance and high temperature resistance thereof, but such alloys also have poor machinability because of the unique properties. Rapid tool wear is a serious problem for titanium alloy machining, with tool wear resulting in different tool edges. In the present study, finite element technology was used to establish a 2D cutting numerical model, so as to investigate the influence of the different cutting edges caused by tool wear during the machining process of titanium alloy TC21. In the cutting model, four different types of tool edges, including sharp edge, round edge, chamfer edge and crater edge, were established to analyze the influence of different tool edges on the cutting process of TC21 alloy. Additionally, the material model, chip separation model, friction model and heat transfer model have been included in the established model. A series of cutting simulations based on the model were conducted, through which the chip morphology, cutting temperature, cutting force, surface morphology and residual stress under the different tool edges were analyzed. The simulation results were compared with the experimental results, and indicated that the tool edge is a significant factor in the machining process of TC21 alloy. A proper cutting edge can improve the cutting quality.

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Considering multiple process observables to determine material model parameters for FE-cutting simulations

Cited by 8 publications

References 38 publications

Investigation of the Cutting Uid'S Ow and its Thermomechanical Effect on the Cutting Zone Based on Uid-Structure Interaction (FSI) Simulation

Investigation of the Cutting Uid'S Ow and its Thermomechanical Effect on the Cutting Zone Based on Uid-Structure Interaction (FSI) Simulation

Identification of the Parameter Values of the Constitutive and Friction Models in Machining Using EGO Algorithm: Application to Ti6Al4V

Influence of different cutting edges caused by tool wear on cutting process of titanium alloy TC21 based on finite element model

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