An assessment of statistical models of competitive growth during transient Ostwald ripening in turbine disc nickel-based superalloys
An assessment of statistical models of competitive growth during transient Ostwald ripening in turbine disc nickel-based superalloys
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DOI：
10.1088/1361-651x/ac8c5d
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发表时间：
2022-08
影响因子：
1.8
通讯作者：
M. Anderson;L. Liao;H. Basoalto
中科院分区：
文献类型：
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作者：
M. Anderson;L. Liao;H. Basoalto
准确预测析出物尺寸分布随时间变化的能力对于优化工程合金的热处理和机械性能至关重要。平均场模型的粒子增长率假设相邻粒子之间的扩散场是弱耦合的，减少了一个嵌入在有效介质中的单个粒子的问题。低体积分数合金预期满足这种性能。然而，这些假设在许多感兴趣的应用中并不满足，其中沉淀物之间存在强相互作用。通常引入校正因子来解释相邻沉淀物之间扩散场的重叠所引起的加速扩散速率。本文应用Wang-Glicksman-Rajan-Voorhees（WGRV）离散点源/汇模型对竞争性增长的描述进行了比较。这包括评估校正因子的平均场粒子的增长率由Ardell，Marqusee和Ross，Svoboda和Fischer除了Di Nunzio的成对相互作用模型。WGRV模型被用作比较采用类似假设的竞争性增长的不同近似值的基准。随后应用该模型模拟镍基高温合金IN 738 LC和RR 1000长期时效动力学过程中的析出动力学。结果表明，竞争性生长校正因子是准确的体积分数为20%，并预测在40%的沉淀动力学预测的加速。WGRV模型能够以合理的精度捕获在IN 738 LC和RR 1000中观察到的粗化动力学。WGRV模型确定粒子的生长速率作为一个函数的直接邻居，并提供了一个改进的预测的粗化行为的第三粒子在RR 1000相比，平均场近似，但是高估的第三粒子的生长速率相比，实验数据。
The ability to accurately predict the time evolution of precipitate size distributions is fundamental to optimising heat treatments and mechanical properties of engineering alloys. Mean-field models of the particle growth rates assume that diffusion fields between neighbouring particles are weakly coupled reducing the problem to a single particle embedded in an effective medium. This regime of behaviour is expected to be satisfied for low volume fraction alloys. However, these assumptions are not fulfilled in many applications of interest where strong interactions between precipitates holds. Correction factors are often introduced to account for the accelerated rate of diffusion caused by the overlapping of diffusion fields between neighbouring precipitates. This paper applies the Wang–Glicksman–Rajan–Voorhees (WGRV) discrete point-source/sink model to compare descriptions of competitive growth. This includes assessing correction factors to the mean-field particle growth rate derived by Ardell, Marqusee and Ross, and Svoboda and Fischer in addition to Di Nunzio’s pairwise interaction model. The WGRV model is used as a benchmark to compare different approximations of competitive growth that apply similar assumptions. This is followed by the application of the models to simulate precipitation kinetics during long term aging kinetics observed in the nickel-based superalloys IN738LC and RR1000. It is shown that the competitive growth correction factors are accurate for volume fractions of 20% and under-predict the acceleration of precipitate kinetics predicted at 40%. The WGRV model is able to capture the coarsening kinetics observed in both IN738LC and RR1000 with reasonable accuracy. The WGRV model determines particle growth rates as a function of the immediate neighbourhood and provides an improved prediction of the coarsening behaviour of tertiary particles in RR1000 in comparison to the mean-field approximation, however over-estimates the growth rate of the tertiary particles compared to experimental data.