The efficacy of an elasto-viscoplastic fast Fourier transform (EVPFFT) code was assessed based on blind predictions of micromechanical fields in a sample of Inconel 625 produced with additive manufacturing (AM) and experimentally characterized with high-energy X-ray diffraction microscopy during an in situ tensile test. The blind predictions were made in the context of Challenge 4 in the AFRL AM Modeling Challenge Series, which required predictions of grain-averaged elastic strain tensors for 28 unique target (Challenge) grains at six target stress states given a 3D microstructural image, initial elastic strains of Challenge grains, and macroscopic stress–strain response. Among all submissions, the EVPFFT-based submission presented in this work achieved the lowest total error in comparison with experimental results and received the award for Top Performer. A post-Challenge investigation by the authors revealed that predictions could be further improved, by over 25% compared to the Challenge-submission model, through several model modifications that required no additional information beyond what was initially provided for the Challenge. These modifications included a material parameter optimization scheme to improve model bias and the incorporation of the initial strain field through both superposition and eigenstrain methods. For the first time with respect to EVPFFT modeling, an ellipsoidal-grain-shape Eshelby approximation was tested and shown to improve predictive capability compared to previously used spherical-grain-shape assumptions. Lessons learned for predicting full-field micromechanical response using the EVPFFT modeling method are discussed.

基于对增材制造（AM）生产的Inconel 625样品中微机械场的盲目预测，评估了弹粘塑性快速傅里叶变换（EVPFFT）代码的功效，并在实验过程中通过高能X射线衍射显微镜对其进行了实验表征原位拉伸试验。盲预测是在AFRL AM建模挑战赛系列中的挑战4的背景下做出的，该要求要求在给定3D微观结构图像（初始弹性）的情况下，在六个目标应力状态下对28个唯一目标（挑战）晶粒的晶粒平均弹性应变张量进行预测挑战晶粒的应变和宏观应力应变响应。在所有提交的文件中，与实验结果相比，本文中基于EVPFFT的提交所实现的总错误率最低，并获得了“最佳执行者”奖。作者在质询后进行的一项调查显示，通过进行多次模型修改，除最初为质询提供的信息外，不需要其他任何信息，与质询提交模型相比，预测可以进一步提高25％以上。这些修改包括材料参数优化方案，以改善模型偏差，并通过叠加和特征应变方法合并初始应变场。对于EVPFFT建模，这是第一次，测试了椭圆粒形状的Eshelby近似值，并证明与以前使用的球形粒状假设相比，该方法可以提高预测能力。讨论了使用EVPFFT建模方法预测全场微机械响应的经验教训。