Prediction of Microstructural Changes and Residual Stresses in Hard Machining
硬加工中微观结构变化和残余应力的预测
基本信息
- 批准号:0100176
- 负责人:
- 金额:$ 16.17万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2001
- 资助国家:美国
- 起止时间:2001-04-01 至 2004-03-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
This grant provides funding for the development of a computational tool for analysis and prediction of microstructure changes and residual stresses generated in cutting of hardened steels using single-point tools. The computational tool will be used to establish the optimal parameter values for cutting speed, feed, depth of cut and tool geometry that yield favorable residual stresses and a workpiece surface free of undesirable microstructure changes (e.g., white layer formation) in two-dimensional cutting of a hardened steel material. To achieve this goal, analytical models of the metallurgical phase transformation occurring in quenching of steels will be developed and combined with a coupled thermo-mechanical updated Lagrangian finite element model of the two-dimensional cutting process developed using the ABAQUS Standard finite element code. In order to validate the complete model, orthogonal cutting experiments will be performed with bearing steel (e.g., AISI 52100) as the workpiece material and PCBN tool material using cutting parameters determined from the model. Existing material property data and/or elevated temperature high strain-rate tests will be used to establish the material flow-stress models to be used in the simulations. The microstructure of the machined workpiece samples will be characterized using optical and scanning electron microscopy while residual stresses will be measured using X-ray diffraction. If successful, the results of this research will provide the capability of accurately simulating surface generation in machining of hardened steels and determining an optimal window of cutting conditions to produce surface characteristics that enhance the service-life of hardened steel components. This will in turn help to reduce cost, improve part quality, and promote the industrial use of hard machining technology. On a fundamental level, the proposed research will advance current physical understanding of material and cutting process interactions in hard machining, particularly from a standpoint of workpiece microstructure changes (e.g., white layer formation) and residual stresses. The proposed research will also provide a solid framework for future development of a three-dimensional model for simulating hard machining processes such as turning and milling.
这笔赠款提供资金用于开发一种计算工具,用于分析和预测使用单点工具切割硬化钢时产生的微观结构变化和残余应力。 计算工具将用于建立切削速度、进给、切削深度和工具几何形状的最佳参数值,这些参数值产生有利的残余应力和没有不期望的微观结构变化(例如,白色层形成)。 为了实现这一目标,冶金相变发生在淬火钢的分析模型将开发和结合使用ABAQUS标准有限元代码开发的二维切削过程的耦合热机械更新拉格朗日有限元模型。 为了验证完整的模型,将对轴承钢进行正交切削实验(例如,AISI 52100)作为工件材料和PCBN刀具材料,使用由模型确定的切削参数。 现有的材料性能数据和/或高温高应变率试验将用于建立模拟中使用的材料流动应力模型。 将使用光学和扫描电子显微镜表征加工工件样品的微观结构,同时使用X射线衍射测量残余应力。如果成功的话,这项研究的结果将提供准确模拟加工硬化钢表面生成的能力,并确定切削条件的最佳窗口,以产生提高硬化钢部件使用寿命的表面特性。 这将有助于降低成本,提高零件质量,并促进硬加工技术的工业应用。 在基础层面上,拟议的研究将推进当前对硬加工中材料和切削过程相互作用的物理理解,特别是从工件微观结构变化的角度来看(例如,白色层形成)和残余应力。 拟议的研究也将提供一个坚实的框架,为未来开发的三维模型模拟硬加工过程,如车削和铣削。
项目成果
期刊论文数量(0)
专著数量(0)
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Shreyes Melkote其他文献
Prediction of part orientation error tolerance of a robotic gripper
- DOI:
10.1016/j.rcim.2008.02.006 - 发表时间:
2009-04-01 - 期刊:
- 影响因子:
- 作者:
Matthew Wagner;John Morehouse;Shreyes Melkote - 通讯作者:
Shreyes Melkote
Co-training of multiple neural networks for simultaneous optimization and training of physics-informed neural networks for composite curing
多个神经网络的协同训练,用于同时优化和训练用于复合材料固化的物理信息神经网络
- DOI:
10.1016/j.compositesa.2025.108820 - 发表时间:
2025-06-01 - 期刊:
- 影响因子:8.900
- 作者:
Keith D. Humfeld;Geun Young Kim;Ji Ho Jeon;John Hoffman;Allison Brown;Jonathan Colton;Shreyes Melkote;Vinh Nguyen - 通讯作者:
Vinh Nguyen
McGAN: Generating manufacturable designs by embedding manufacturing rules into conditional generative adversarial network
McGAN:通过将制造规则嵌入条件生成对抗网络来生成可制造的设计
- DOI:
10.1016/j.aei.2024.103074 - 发表时间:
2025-03-01 - 期刊:
- 影响因子:9.900
- 作者:
Zhichao Wang;Xiaoliang Yan;Shreyes Melkote;David Rosen - 通讯作者:
David Rosen
Laser tempering based turning process for efficient machining of hardened AISI 52100 steel
- DOI:
10.1016/j.jmapro.2013.03.002 - 发表时间:
2013-08-01 - 期刊:
- 影响因子:
- 作者:
Satyanarayanan Raghavan;Shreyes Melkote;Fukuo Hashimoto - 通讯作者:
Fukuo Hashimoto
Shreyes Melkote的其他文献
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{{ truncateString('Shreyes Melkote', 18)}}的其他基金
FMRG: Manufacturing USA: Cyber: Data-Driven Methods for Future Cyber Manufacturing as a Service
FMRG:美国制造:网络:未来网络制造即服务的数据驱动方法
- 批准号:
2229260 - 财政年份:2022
- 资助金额:
$ 16.17万 - 项目类别:
Continuing Grant
EAGER: Exploration of Data-Driven Methods for Cyber Manufacturing
EAGER:探索数据驱动的网络制造方法
- 批准号:
2113672 - 财政年份:2021
- 资助金额:
$ 16.17万 - 项目类别:
Standard Grant
GOALI: Diamond Wire Slicing of Crystalline Silicon Materials with Application to Manufacturing of High Quality Solar Cell Substrates
目标:晶体硅材料的金刚石线切割及其在高质量太阳能电池基板制造中的应用
- 批准号:
1538293 - 财政年份:2015
- 资助金额:
$ 16.17万 - 项目类别:
Standard Grant
2011 NSF CMMI Engineering Research and Innovation Conference: Engineering Challenges to Energy Management and Sustainability; Atlanta, Georgia; January 4-7, 2011
2011 NSF CMMI 工程研究与创新会议:能源管理和可持续性的工程挑战;
- 批准号:
0933388 - 财政年份:2009
- 资助金额:
$ 16.17万 - 项目类别:
Standard Grant
Travel Support for U.S. Researchers to Attend The 2006 International Symposium on Flexible Automation; held in Osaka, Japan; July 10-12, 2006
为美国研究人员参加 2006 年灵活自动化国际研讨会提供差旅支持;
- 批准号:
0539178 - 财政年份:2005
- 资助金额:
$ 16.17万 - 项目类别:
Standard Grant
Modeling of Size-Effect in Micro-Cutting Process Using Strain Gradient Plasticity
使用应变梯度塑性对微切削过程中的尺寸效应进行建模
- 批准号:
0300457 - 财政年份:2003
- 资助金额:
$ 16.17万 - 项目类别:
Standard Grant
Modeling of Part-Fixture Dynamics With Application to Synthesis of Dedicated and Flexible Fixturing Systems
零件夹具动力学建模及其在专用和柔性夹具系统综合中的应用
- 批准号:
0218113 - 财政年份:2002
- 资助金额:
$ 16.17万 - 项目类别:
Standard Grant
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