Intelligent machining simulation: Process Modelling and Functional Performance Prediction of Superalloys

智能加工仿真：高温合金的工艺建模和功能性能预测

• 批准号: 2604446
• 金额: --
• 依托单位: University of Sheffield
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2604446
• 关键词: Intelligent; machining; simulation; Process; Modelling

Machining is one of the fundamental manufacturing operations wherein the material experiences a very complex deformation condition during the interaction with a cutting tool, Figure 1. To meet quality standards and achieve efficient productivity, a number of time-consuming and costly experimental trials are typically used to optimise cutting parameters and show partconformity, particularly for safety critical aerospace components. Although there already exists some knowledge about the effect of cutting operation on the produced surface qualities and subsurface deformation, there is not a reliable non-destructive technique available to detect their presence nor the extent of which these features affect the parts performance is known. Additionally, many modelling strategies have already been developed to reduce the need for experimental observations, however these are either very time consuming or not comprehensive enough to link the process parameters and simulations to the parts quality with respect to their service life.The project aims to develop a digital platform for simulation of machining process, produced surface integrity and functional performance of the superalloys in order to create an intelligent framework for process control and optimisation with respect to the applied cutting parameters and cutting tool conditions. A multi-scale physics based Finite Element model of the cutting process will be realised to simulate the chip formation and predict the machining induced deformation and stress state on the workpiece materials. The results are used to model microstructural morphology and surface integrity at the machined surface that will be fed into a functional performance analysis under various service loads.

机械加工是基本的制造操作之一，其中材料在与切削刀具相互作用的过程中会经历非常复杂的变形条件，如图 1 所示。为了满足质量标准并实现高效的生产率，通常使用大量耗时且昂贵的实验试验来优化切削参数并显示零件的一致性，特别是对于安全关键的航空航天部件。尽管已经存在一些关于切削操作对所产生的表面质量和表面下变形的影响的知识，但没有可靠的非破坏性技术可用于检测它们的存在，也不知道这些特征对零件性能的影响程度。此外，已经开发了许多建模策略来减少实验观察的需要，但是这些策略要么非常耗时，要么不够全面，无法将工艺参数和模拟与零件质量及其使用寿命联系起来。该项目旨在开发一个用于模拟加工过程、高温合金的表面完整性和功能性能的数字平台，以便创建一个智能框架，用于针对所应用的切削参数和切削刀具进行过程控制和优化 状况。将实现基于多尺度物理的切削过程有限元模型，以模拟切屑形成并预测加工引起的工件材料变形和应力状态。结果用于对加工表面的微观结构形态和表面完整性进行建模，并将其输入到各种服务负载下的功能性能分析中。