石墨烯改性含能材料的制备方法及性能研究进展

含能材料是武器装备的核心材料之一,在国防工业中发挥着重要作用.开发高能量密度、高释能效率、高安全性特征的新型含能材料是现代武器装备发展和新军事变革的迫切需求.石墨烯具有较大的比表面积、良好的导热导电性以及适中的化学活性,作为功能添加剂负载纳米颗粒,能够显著改善含能材料的感度、力学性能和安全性.从石墨烯的制备及功能化改性...     

航空材料数据的管理与应用

飞机及发动机对航空材料提出挑战性的要求,设计师要在避免风险的同时充分利用合金、复合材料以及陶瓷等具有的特性.在这当中,对材料性能数据的采集、管理以及应用至为关键.     

材料特性对热障涂层合理压入深度的影响

基于有限元计算方法和量纲分析原理提出了热障涂层合理压入深度的确定方法,并研究了涂层及基体材料特性对合理压入深度的影响.首先,根据量纲分析原理提出了合理压入深度的无量纲表达式;其次基于锥形压头识别理想弹塑性材料的材料特性的方法,提出合理压入深度的确定方法;最后研究了各无量纲因素对合理压入深度的影响.研究发现基体的弹性模量对合理压入深度的影响最大,粘结层材料特性的影响较大,热氧化生成层的材料特性及基体的屈服极限对合理压入深度的影响不大.     

飞机日历寿命试验的介质成分确定和加速方法

 针对飞机使用环境,研究了飞机日历寿命试验中的腐蚀介质成分确定方法和加速方法。进行了5 ℃,25 ℃,50 ℃这3种温度和4种介质浓度下的30CrMnSiA结构钢和LY12CZ铝合金两种金属的纯腐蚀和腐蚀疲劳试验研究。得到的试验曲线表明,它们的腐蚀动力学规律都近似遵循线性关系,每条曲线的腐蚀速度也基本保持不变。从而认为,飞机日历寿命试验介质成分最好选用飞机所在机场使用环境的各腐蚀介质成分,加速腐蚀试验的最好方法,就是在此机场的各介质成分上加权,加权越高,加速越快。这个结论得到了试验验证。     

基于静强度分布的复合材料疲劳寿命分布的预测模型(英文)

The reasons of the static strength dispersion and the fatigue life dispersion of composite laminates are analyzed in this article. It is concluded that the inner original defects, which derived from the manufacturing process of composite laminates, are the common and major reason of causing the random distributions of the static strength and the fatigue life. And there is a correlative relation between the two distributions. With the study of statistical relationship between the fatigue loading and the fatigue life in the uniform confidence level and the same survival rate S-N curves of material, the relationship between the static strength distribution and the fatigue life distribution through a material S-N curve model has been obtained. And then the model which is used to describe the distributions of fatigue life of composites, based on their distributions of static strength, is set up. This model reasonably reflects the effects of the inner original defects on the static strength dispersion and on the fatigue life dispersion of composite laminates. The experimental data of three kinds of composite laminates are employed to verify this model, and the results show that this model can predict the random distributions of fatigue life for composites under any fatigue loads fairly well.