GOALI/Collaborative Research: Reliable Prediction of Endurance Life of Ultra-High-Strength Aerospace Rolling-Element Bearings

GOALI/合作研究：超高强度航空航天滚动轴承耐久性寿命的可靠预测

• 批准号: 1434834
• 负责人: Qian Wang
• 金额: $ 20万
• 依托单位: Northwestern University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-08-01 至 2019-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1434834&HistoricalAwards=false
• 关键词: GOALI; Collaborative; Research; Reliable; Prediction

Rolling-element bearings are key precision components used for rotor support in nearly all machinery. The annual revenue associated with bearings is a substantial $50.5 billion worldwide. Future demands on high performance rotor support for advanced aircraft engines, wind turbines and high-speed rail require bearings to survive thousands of hours and consequently billions of Rolling Contact Fatigue (RCF) cycles under severe operating conditions. A new generation of high strength bearing steels with graded material properties has been designed to meet these challenges. Existing life prediction methodologies rely on empirical models dating back to the 1940s, resulting in a large discrepancy between observed and predicted life, for the new generation of materials. This Grant Opportunity for Academic Liaison with Industry (GOALI) collaborative researh project aims to predict reliable service life and structural integrity of new generation bearing materials based on novel experimental and computational procedures for understanding material degradation due to RCF at the micro and nanometer scale. The results will translate to the design of other components with large economic impact such as transmission gears, cams, railway wheels and tracks, and manufacturing tooling. This research is an effort to bring back an academic focus to manufacturing-related research to campuses and to better assist US industries. The project will contribute to the education and training of future manufacturing research workforce and leaders.This collaborative GOALI project involves developing a novel physics-based material-specific life prediction model rooted in fundamental understanding of local material properties of as-manufactured and RCF-affected materials from sub-micrometer/nanometer to macroscopic length scales. The project will develop: 1) quantifiable measures for subsurface graded material response as a function of load, temperature and RCF cycles; 2) computational approaches for understanding the influence of microstructural features on the material cyclic response, resultant stress and strain fields, and fatigue damage; and 3) a material-specific RCF life prediction methodology based on enhancements to the existing Lundberg-Palmgren empirical approach by the evolving elastic-plastic subsurface stress and strain fields. Methodologies for tracking RCF material damage in the giga-cycle regime will become available for reliable life prediction, which are of considerable importance with applications to broader areas of tribology and heterogeneous materials for future component design. Intellectual significance of the project comprises of two novel contributions: 1) it will aid development of a new material-specific RCF life prediction model, particularly beneficial to accelerated design of new bearing materials, and 2) it will result in a methodology to model cycle-specific material property evolution in rolling contacts, with direct relevance to design of gears, cams, railway wheels and tooling.

滚动轴承是几乎所有机械中用于支撑转子的关键精密部件。全球与轴承相关的年收入高达 505 亿美元。未来对先进飞机发动机、风力涡轮机和高速铁路的高性能转子支撑的需求要求轴承能够在恶劣的工作条件下承受数千小时，从而承受数十亿次滚动接触疲劳（RCF）循环。具有分级材料性能的新一代高强度轴承钢旨在应对这些挑战。现有的寿命预测方法依赖于 20 世纪 40 年代的经验模型，导致新一代材料的观测寿命与预测寿命之间存在巨大差异。这一学术与工业联络资助机会 (GOALI) 合作研究项目旨在基于新颖的实验和计算程序来预测新一代轴承材料的可靠使用寿命和结构完整性，以了解微米和纳米尺度上 RCF 引起的材料退化。研究结果将转化为具有重大经济影响的其他部件的设计，例如传动齿轮、凸轮、铁路车轮和轨道以及制造工具。这项研究旨在将制造业相关研究的学术重点带回校园，并更好地帮助美国工业。该项目将为未来制造研究人员和领导者的教育和培训做出贡献。该合作 GOALI 项目涉及开发一种新颖的基于物理的特定材料寿命预测模型，该模型植根于对从亚微米/纳米到宏观长度尺度的制造和受 RCF 影响的材料的局部材料特性的基本了解。该项目将开发：1）作为负载、温度和 RCF 循环函数的地下分级材料响应的可量化测量； 2）用于理解微观结构特征对材料循环响应、合成应力和应变场以及疲劳损伤影响的计算方法； 3）特定材料的 RCF 寿命预测方法，该方法基于通过不断演变的弹塑性次表面应力和应变场对现有 Lundberg-Palmgren 经验方法的增强。在千兆循环范围内跟踪 RCF 材料损伤的方法将可用于可靠的寿命预测，这对于未来组件设计中更广泛的摩擦学和异质材料领域的应用具有相当重要的意义。该项目的智力意义包括两个新颖的贡献：1）它将有助于开发新的特定材料 RCF 寿命预测模型，特别有利于加速新轴承材料的设计，2）它将产生一种对滚动接触中特定周期材料性能演变进行建模的方法，与齿轮、凸轮、铁路车轮和工具的设计直接相关。