菱形颗粒冲击材料表面冲蚀磨损特性分析
收藏中国科学院兰州化学物理研究所科学数据中心2023-09-27 更新2024-03-05 收录
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基于弹射试验装置,借助高速摄像机捕捉不同入射条件下单个菱形颗粒冲击金属表面的动态过程,同时结合试验过程建立菱形颗粒冲击金属表面的FEM-SPH耦合数值模型,通过对比试验现象与仿真结果优化数值模型参数,最后借助数值模型进一步分析菱形颗粒在临界冲击、自身初始旋转以及重复冲击等工况下的运动行为及预测的凹坑轮廓形态. 结果表明:优化后的模型能够很好地捕捉颗粒冲击过程中金属表面凹坑的产生及演化规律,并能详细记录颗粒的入射行为及反弹规律,测得颗粒反弹速度和反弹角度误差均在14%以内. 临界冲击工况下颗粒动能损失最大,且冲击角越高,残余动能越少;颗粒初始旋转能够改变其反弹后的运动行为及金属表面材料的失效方式;颗粒重复冲蚀对材料表面的作用机制与后续颗粒的入射条件有密切关系,模型成功捕捉到重复冲蚀导致的材料破坏加深和破坏减缓两种特殊现象.
Based on an ejection test setup, high-speed cameras were utilized to capture the dynamic process of a single rhombic particle impacting a metal surface under various incident conditions. Meanwhile, a coupled FEM-SPH numerical model for rhombic particle impact on metal surfaces was established based on the experimental procedures. The parameters of the numerical model were optimized by comparing experimental phenomena with simulation results. Finally, the numerical model was employed to further analyze the motion behavior and predicted crater profile morphology of rhombic particles under working conditions including critical impact, initial self-rotation, and repeated impact. The results demonstrate that the optimized model can effectively capture the generation and evolution laws of craters on the metal surface during the particle impact process, and comprehensively record the incident and rebound behaviors of the particles. The errors of the measured particle rebound velocity and rebound angle are both within 14%. Under critical impact conditions, the particle undergoes the maximum kinetic energy loss, and the higher the impact angle, the smaller the residual kinetic energy. Initial self-rotation of the particle can change its post-impact motion behavior and the failure mode of the metal surface material. The action mechanism of repeated particle erosion on the material surface is closely correlated with the incident conditions of subsequent particles, and the model successfully captures two special phenomena induced by repeated erosion: deepened material damage and slowed damage progression.
提供机构:
中国科学院兰州化学物理研究所科学数据中心
创建时间:
2023-09-27



