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基于耦合欧拉-拉格朗日法计算的随机多颗粒冷喷涂Al涂层沉积特性

Deposition characteristics of random multi-particle cold spray Al coatings based on CEL

  • 摘要: 针对U型薄壁铝管基体,开展了冷喷涂Al涂层沉积特性的仿真与实验研究.利用ABAQUS软件建立了基于耦合欧拉-拉格朗日法(CEL)的随机多颗粒撞击模型,并对不同载气压力与温度下Al涂层的微观形貌和孔隙率进行预测;通过实验制备了相应涂层,同时对其微观结构进行观测,以验证仿真结果.结果表明:在载气压力5.1 MPa、载气温度500 K的工艺条件下,Al涂层的性能最优,孔隙率最低(1.78%),抗拉强度最高(47.55 MPa).对比4组工艺参数下的仿真与实验孔隙率结果,发现误差范围为0.64%~0.86%,吻合良好,这表明所建立的随机多颗粒沉积模型具有较高的可靠性,可为管型构件表面冷喷涂工艺的优化提供参考.

     

    Abstract: This thesis presents a simulation and experimental study on the deposition characteristics of cold-sprayed Al coatings on U-shaped thin-walled aluminum tube substrates. A stochastic multi-particle impact model based on the Coupled Eulerian-Lagrangian(CEL) method has been established using ABAQUS software to predict the microstructure and porosity of coatings under different carrier gas pressures and temperatures. Meanwhile, corresponding coatings have been prepared experimentally, and their microstructures were observed to validate the simulation results. The results show that under the process conditions of a carrier gas pressure of 5.1 MPa and a temperature of 500 K, the coating exhibits the optimal performance with the lowest porosity(1.78%) and the highest tensile strength(47.55 MPa). The comparison of porosity between simulation and experiment under four different parameter sets shows that the error ranges from 0.64% to 0.86%, demonstrating good agreement. This indicates that the established stochastic multi-particle deposition model has high reliability and can provide a reference for the optimization of cold spray processes on tubular component surfaces.

     

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