材料科学
气动冷喷涂
沉积(地质)
临界电离速度
纳米技术
复合材料
化学工程
机械
涂层
沉积物
生物
物理
工程类
古生物学
作者
Che Zhang,Tesfaye Tadesse Molla,Christian Brandl,Jarrod Watts,Rick McCully,Caixian Tang,G. B. Schaffer
标识
DOI:10.1016/j.jmapro.2024.12.077
摘要
Deposition efficiency (DE) in cold spray additive manufacturing (CSAM) is a key indicator for evaluating process efficiency. Here we develop a reduced-order model to predict DE of metals during CSAM by simultaneously calculating the critical velocity and impact velocity using the gas temperature, gas pressure, and particle size as inputs. The impact velocity must exceed the critical velocity to achieve particle adhesion. Since both the critical and impact velocities vary with particle size, DE can be derived from the intersection of these curves. An equation for calculating critical velocity is proposed based on the hydrodynamic spall mechanism with the support of experimental data. The impact velocity is determined using a parametric expression that accounts for the bow shock effect. The model is first calibrated for aluminum to create process design maps. Ten validation experiments are then conducted using two different cold spray systems. The experimental DE values show close agreement with the predicted results. The model can be used to rapidly identify optimal process parameters for achieving high DE of metals, contributing to improved process efficiency and product quality during CSAM. • A reduced-order model is developed to predict deposition efficiency in cold spray additive manufacturing. • Deposition efficiency is evaluated by calculating both the impact velocity and critical velocity of particles across the particle size distribution. • An equation for the critical velocity of particles is proposed, considering particle diameter, temperature, and material properties. • The model is validated using two cold spray systems with excellent agreement.
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