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基于耦合损伤的镍基单晶高温合金DD6同相热机械疲劳寿命预测 被引量:4

Coupling Damage Based Lifetime Prediction of In-Phase Thermomechanical Fatigue in Nickel-Based Single Crystal Superalloy DD6
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摘要 在应力控制的同相热机械疲劳试验基础上,研究了DD6高温合金同相热机械疲劳损伤机理。基于连续介质损伤力学,建立了反映蠕变损伤和疲劳损伤耦合作用的寿命预测模型,并利用纯蠕变、疲劳的试验数据获取了模型中的损伤参数。开展了带保载时间的DD6高温合金同相热机械疲劳试验,试验寿命在基于耦合损伤的预测寿命的2.3倍分散带内,这表明本研究建立的基于耦合损伤的寿命预测模型能够较为准确地预测DD6高温合金同相热机械疲劳寿命,可以为工程应用中DD6高温合金结构的寿命预测提供基础。 Based on the in-phase thermomechanical fatigue experiments under stress control, the damage mechanism of in-phase thermomechanical fatigue of DD6 superalloy was investigated. Based on the continuous damage mechanics, a lifetime prediction model reflecting the coupling of creep damage and fatigue damage was established, and the damage parameters in the model were obtained through using the experiment data of creep and fatigue. Furthermore, the experiments of in-phase thermomechanical fatigue with dwells of DD6 superalloy were conducted in the present paper, and the experiment lifetimes are within a factor of 2.3 of the prediction lifetimes based on the coupling damage. Results indicate that the coupling damage based lifetime prediction model developed in the present paper could accurately predict the in-phase thermomechanical fatigue lifetimes of DD6 superalloy and provides a basis for the lifetime prediction of DD6 superalloy structure in engineering applications.
作者 张斌 王荣桥 胡殿印 蒋康河 毛建兴 荆甫雷 Zhang Bin;Wang Rongqiao;Hu Dianyin;Jiang Kanghe;Mao Jianxing;Jing Fulei(Beihang University,Beijing 100191,China;Collaborative Innovation Center of Advanced Aero-Engine,Beijing 100191,China;Beijing Key Laboratory of Aero-Engine Structure and Strength,Beijing 100191,China;AECC Hunan Aviation Powerplant Research Institute,Zhuzhou 412000,China;Aero Engine Corporation of China,Beijing 101304,China)
出处 《稀有金属材料与工程》 SCIE EI CAS CSCD 北大核心 2019年第12期3889-3894,共6页 Rare Metal Materials and Engineering
基金 国家自然科学基金(51675024,51305012,51375031)
关键词 耦合损伤 镍基单晶高温合金 同相热机械疲劳 寿命预测 coupling damage nickel-based single crystal superalloy in-phase thermomechanical fatigue lifetime prediction
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