A thermo-mechanical fully coupled model for high-speed machining of Ti6Al4V

IF 1.5 4区 工程技术 Q3 ENGINEERING, MECHANICAL Industrial Lubrication and Tribology Pub Date : 2024-07-26 DOI:10.1108/ilt-05-2024-0168
Zeyuan Zhou, Ying Wang, Zhijie Xia
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Abstract

Purpose

This study aims to further refine the model, explore the influence of cutting parameters on the machining process, and apply it to practical engineering to improve the efficiency and quality of titanium alloy machining.

Design/methodology/approach

This paper establishes a comprehensive thermo-mechanical fully coupled orthogonal cutting model. This paper aims to couple the modified Johnson–Cook constitutive model, damage model and contact model to construct a two-dimensional orthogonal cutting thermo-mechanical coupling model for high-speed cutting of Ti6Al4V. The model considers the evolution of microstructures such as plastic deformation, grain dislocation rearrangement, dynamic recrystallization, as well as stress softening and hardening occurring continuously in Ti6Al4V metal during high-speed cutting. Additionally, the model incorporates friction and contact between the tool and the workpiece. It can be used to predict parameters such as cutting process, cutting force, temperature distribution, stress and strain in titanium alloy machining. The study establishes the model and implements corresponding functions by writing Abaqus VUMAT and VFRICTION subroutines.

Findings

The use of different material constitutive models can significantly impact the prediction of the cutting process. Some models may more accurately describe the mechanical behavior of the material, thus providing more reliable prediction results, while other models may exhibit larger deviations. Compared to the Tanh model, the proposed model achieves a maximum improvement of 8.9% in the prediction of cutting force and a maximum improvement of 20.9% in the prediction of chip morphology parameters. Compared to experiments, the proposed model achieves a minimum prediction error of 2.8% for average cutting force and a minimum error of 0.57% for sawtooth parameters. This study provides a comprehensive theoretical foundation and practical guidance for orthogonal cutting of titanium alloys. The model not only helps engineers and researchers better understand various phenomena in the cutting process but also serves as an important reference for optimizing cutting processes.

Originality/value

The originality of this research is guaranteed, as it has not been previously published in any journal or publication.

Peer review

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2024-0168/

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用于 Ti6Al4V 高速加工的热机械全耦合模型
目的 本研究旨在进一步完善模型,探索切削参数对加工过程的影响,并将其应用于实际工程中,以提高钛合金加工的效率和质量。本文旨在将改进的约翰逊-库克(Johnson-Cook)构成模型、损伤模型和接触模型耦合起来,构建一个二维正交切削热机械耦合模型,用于 Ti6Al4V 的高速切削。该模型考虑了 Ti6Al4V 金属在高速切削过程中连续发生的塑性变形、晶粒位错重排、动态再结晶以及应力软化和硬化等微观结构的演变。此外,该模型还包含了刀具与工件之间的摩擦和接触。该模型可用于预测钛合金加工中的切削过程、切削力、温度分布、应力和应变等参数。研究通过编写 Abaqus VUMAT 和 VFRICTION 子程序建立模型并实现相应功能。一些模型可以更准确地描述材料的力学行为,从而提供更可靠的预测结果,而另一些模型则可能表现出更大的偏差。与 Tanh 模型相比,所提出的模型在切削力预测方面最大提高了 8.9%,在切屑形态参数预测方面最大提高了 20.9%。与实验相比,所提出的模型在平均切削力方面的预测误差最小为 2.8%,在锯齿参数方面的预测误差最小为 0.57%。这项研究为钛合金的正交切削提供了全面的理论基础和实践指导。该模型不仅能帮助工程师和研究人员更好地理解切削过程中的各种现象,还可作为优化切削过程的重要参考。原创性/价值由于该研究之前未在任何期刊或出版物上发表过,因此其原创性得到了保证。同行评审本文的同行评审历史可在以下网址查阅:https://publons.com/publon/10.1108/ILT-05-2024-0168/。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Industrial Lubrication and Tribology
Industrial Lubrication and Tribology 工程技术-工程:机械
CiteScore
3.00
自引率
18.80%
发文量
129
审稿时长
1.9 months
期刊介绍: Industrial Lubrication and Tribology provides a broad coverage of the materials and techniques employed in tribology. It contains a firm technical news element which brings together and promotes best practice in the three disciplines of tribology, which comprise lubrication, wear and friction. ILT also follows the progress of research into advanced lubricants, bearings, seals, gears and related machinery parts, as well as materials selection. A double-blind peer review process involving the editor and other subject experts ensures the content''s validity and relevance.
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