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Prediction of Tool Wear Rate and Pattern during Metal Cutting

Prediction of Tool Wear Rate and Pattern during Metal Cutting
金属切削过程中刀具磨损率和模式的预测
批准号:
RGPIN-2014-06223
负责人:
Ng, EuGene
金额:
$1.75万
依托单位:
依托单位国家:
加拿大
项目类别:
Discovery Grants Program - Individual
财政年份:
2018
资助国家:
加拿大
项目状态:
已结题
起止时间:
2018-01-01 至 2019-12-31

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中文摘要
翻译
刀具磨损率高度依赖于接触压力、界面接触速度、温度、材料性能和表面粗糙度等因素。在过去的半个世纪里,有限刀具磨损模型被发展用来预测刀具寿命、刀具磨损率和金属切削过程中的模式。在金属切削过程中,准确预测刀具微观结构对刀具磨损率和刀具磨损模式的影响,将使研究人员和工程师能够优化高价值部件的加工参数,从而提高零件质量,减少零件变形,最大限度地减少加工后工序。遗憾的是,研究刀具材料微观结构对刀具磨损率和磨损模式模型影响的研究文献很少。*本研究的长期目标是开发数值模型来预测金属切削过程中刀具的磨损率和模式。本研究将发展一种半数值和经验的方法来确定摩擦系数,并实验研究表面粗糙度对摩擦系数的影响。将设计一个独特的摩擦学测试配置,以确定在高接触应力和高温下的摩擦系数。为了创造这种与金属切削相似的接触条件,将修改正交切削构型。采用有限元模型预测法向接触压力和界面温度。接下来,将开发一种独特的方法,以有限或很少的实验参数校准工具磨损模型常数。校准常数将是刀具碳化物粒度的函数,这是本研究的一个独特方面。将建立一个正交切削有限元模型,以模拟刀具微观结构和切削刃的磨损几何形状对法向接触应力、界面滑动速度和界面接触温度的影响。正交切削模型将首先采用任意拉格朗日和欧拉(ALE)公式技术来模拟瞬态切削过程。当模型达到稳态时,通过控制重网格边界条件,将模型由ALE公式转换为欧拉公式。这种方法将显著减少计算时间。这将减少校准时间,提高刀具磨损率预测。最后,本研究将开发一种基于物理的方法,仅使用有限元方法模拟正交切削过程中刀具的磨损模式和磨损率。为了模拟磨损速率和模式,必须在刀具磨损模型中加入一个侵蚀子程序。侵蚀子程序将包括侵蚀准则和元素删除方案。侵蚀准则将是静水压力、冯米塞斯应力和温度的函数。当侵蚀标准达到时,元素删除方案将被激活。该方案将从刀具本体中移除元件,生成新的刀具表面几何形状,并将载荷和边界条件转移到这个新表面。将进行大量的实验来验证这些模型。*这项研究将有助于提高加拿大在基于物理的工具磨损模式建模方面的努力的可见度。预期的研究成果将使加拿大成为使用有限元方法模拟刀具微观结构对刀具磨损模式和刀具磨损率影响的研究前沿国家之一
英文摘要
Tool wear rate is highly dependent on factors like contact pressure, interface contact velocity, temperature, material properties and surface roughness. Over the last half century, limited tool wear models were developed to predict tool life, tool wear rate and pattern during metal cutting. Accurate and important knowledge on predicting the effect of tool microstructure on tool wear rate and tool wear pattern during metal cutting will enable researchers and engineers to optimize machining parameters for high value components, leading to enhanced part quality as well as reducing part distortion and minimizing post machining processes. Unfortunately very few research publications to investigate the effect of tool material microstructure on tool wear rate and wear pattern models are found. *The long term objective of this research is to develop numerical models to predict tool wear rate and pattern during metal cutting. This research will develop a semi numerical and empirical approach to determine the coefficient of friction and experimentally investigate the effect of surface roughness on the coefficient of friction. A unique tribological test configuration will be designed to determine the coefficient of friction under high contact stress and at elevated temperature. To create such contact conditions that are similar in metal cutting, the orthogonal cutting configuration will be modified. A finite element (FE) model will be used to predict the normal contact pressure and interface temperature. Following on from here, an unique methodology will be developed to calibrate tool wear model constants with limited or few experimental parameters. The calibration constants will be a function of tool carbide particle size, which is a unique aspect of this research. An orthogonal cutting FE model will be developed to model the effects of tool microstructure and the worn geometry and shape of the cutting edge on normal contacting stress, interface sliding velocity, and along the interface contacting temperature. The orthogonal cutting model will initially employ the Arbitrary Lagrangian and Eulerian (ALE) formulation technique to simulate the transient cutting process. Once the model reaches steady state, the model will then switch from ALE to Eulerian formulation by controlling the remeshing boundary conditions. This approach will significantly reducing computational time. This will reduce calibration time and improve tool wear rate prediction. Lastly, this research will develop a physics-based approach to simulate tool wear pattern and rate of wear during orthogonal cutting using the FE method only. In order to simulate wear rate and pattern, an erosion subroutine must be incorporated into the tool wear model. The erosion subroutine will comprise an erosion criterion and an element deletion scheme. The erosion criterion will be a function of hydrostatic pressure, Von Mises stress and temperature. The element deletion scheme will be activated when the erosion criterion has been met. This scheme will remove the element from the tool's body, generate a new tool surface geometry, and transfer the loading and boundary conditions to this new surface. Extensive experiments will be performed to validate the models.*This research will contribute to raise the visibility of Canadian effort in physics based tool wear pattern modelling. The expected research outcomes will establish Canada as one of the top research countries on using FE method to model the effect of tool microstructure on tool wear pattern and tool wear rate
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Additive Manufacturing of Selected Automotive Components
  • 批准号:
    513513-2017
  • 项目类别:
    Engage Grants Program
  • 资助金额:
    $1.82万
  • 财政年份:
    2017
  • 负责人:
    Ng, EuGene
  • 依托单位:
Prediction of Tool Wear Rate and Pattern during Metal Cutting
  • 批准号:
    RGPIN-2014-06223
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.75万
  • 财政年份:
    2017
  • 负责人:
    Ng, EuGene
  • 依托单位:
Prediction of Tool Wear Rate and Pattern during Metal Cutting
  • 批准号:
    RGPIN-2014-06223
  • 项目类别:
    Discovery Grants Program - Individual
  • 资助金额:
    $1.75万
  • 财政年份:
    2016
  • 负责人:
    Ng, EuGene
  • 依托单位:
Optimization of real-diamond coated tooling for high-value CFRP composites machining
  • 批准号:
    490428-2015
  • 项目类别:
    Engage Grants Program
  • 资助金额:
    $1.82万
  • 财政年份:
    2015
  • 负责人:
    Ng, EuGene
  • 依托单位:
海外基金