A5101748315- Fatigue and fracture mechanics
- High Temperature Alloys and Creep
- Structural Health Monitoring Techniques
- Non-Destructive Testing Techniques
- Mechanical Failure Analysis and Simulation
- Mechanical stress and fatigue analysis
- Structural Load-Bearing Analysis
- Probabilistic and Robust Engineering Design
- Fire effects on concrete materials
- Numerical methods in engineering
- Material Properties and Failure Mechanisms
- Hydrogen embrittlement and corrosion behaviors in metals
- Rock Mechanics and Modeling
- Metal Forming Simulation Techniques
- Engineering Structural Analysis Methods
- Engineering Diagnostics and Reliability
- Engineering Applied Research
- Machine Learning and ELM
- Energy, Environment, Economic Growth
- Turbomachinery Performance and Optimization
- Educational Reforms and Innovations
- Advanced Optical Sensing Technologies
- Mechanical Engineering and Vibrations Research
- Additive Manufacturing Materials and Processes
- Machine Fault Diagnosis Techniques
Tongji University
2015-2024
Shandong University of Science and Technology
2021
Hohai University
2015
Shanghai Institute of Quality Inspection and Technical Research
2014
Shandong Special Equipment Inspection Institute
2014
Abstract From the literature concerning traditional nonproportional (NP) multiaxial cyclic fatigue prediction, special attentions are usually paid to constitutive relations quantify damage accumulation. As a result, estimation of NP hardening effect decided by entire history path is always proposed, which challenging and complex task. To simplify procedure life prediction engineering components, in this paper, novel effective energy parameter based on simple material properties proposed. The...
Abstract For engineering components subjected to multiaxial loading, fatigue life prediction is crucial for guaranteeing their structural security and economic feasibility. In this respect, energy‐based models, integrating the stress strain components, are widely used because of availability in prediction. Through employing plastic energy concept critical plane approach, a new model proposed paper evaluate low‐cycle life, which defined as maximum damage plane. model, newly NP factor κ *...
Abstract An accurate and stable data‐driven model is proposed in this work for fatigue life prediction presence of mean stresses. Multiple independent extreme learning machines are integrated into the with distinct neural network configurations to simulate complex correlations among stress levels, material properties, lives. Meanwhile, theoretical prediction, as a representation domain knowledge, used optimize processes training prediction. Extensive experimental data 13 metallic materials...
Accurate estimation of remaining fatigue life is crucial to assess the structural durability and reliability engineering components. For this purpose, an energy-based model proposed in paper for modeling process damage accumulation under multistep loading. To account effects loading sequence load interaction, two parameters, a concept normalized driving energy (NFDE) interaction factor, are introduced model. The former based on variable energy-life curves latter formulized as exponential...
The behaviors of short fatigue crack remain to be one the most challenging topics in fracture mechanics. It is widely accepted that process can divided as microstructure-sensitive stage and microstructure-independent stage. inherent multiscaling characteristics necessitates formulation multiscale growth model. One crucial way address concern explore physically reasonable expression crack-tip driving force. This paper briefly reviews models through two approaches. further modification...
Abstract Multiaxial variable amplitude histories usually require a rainflow algorithm to identify individual cycles. A computationally- efficient 5D multiaxial that can deal with any 1D 6D history has been proposed by the authors, based on representation of stresses and strains in deviatoric sub-spaces use von Mises metric. These spaces provide simple geometric interpretations for identified load cycles while highly reducing computational cost. In this work, most algorithms are presented...
摘要: 金属构件的主要失效方式是在循环载荷作用下的疲劳破坏,因此金属构件的疲劳寿命预测对于保证结构安全性和可靠性十分必要。能量法是一种既能用于低周疲劳寿命预测,也能用于高周疲劳寿命预测的方法,其以寻找有效的显式能量损伤参量为手段,结合适当的损伤积累方式进行寿命评估。针对材料疲劳寿命预测问题,提出一个基于能量法和人工神经网络算法的疲劳寿命预测方法。为了达到反映不同加载路径影响的目的,从转动惯量的角度引入两个路径相关参量。使用基于应变控制的九种材料的疲劳试验数据对提出的神经网络模型进行训练、测试。结果显示模型对训练数据和测试数据均有良好的预测精度,并可对单轴加载、多轴加载、高周疲劳和低周疲劳寿命进行有效预测,表明本模型在多轴疲劳寿命预测方面具有较广泛的适用性。