A Monte-Carlo approach for crack initiation modeling of cast superalloys informed by crystal plasticity

IF 5.7 2区材料科学 Q1 ENGINEERING, MECHANICAL

International Journal of Fatigue Pub Date : 2024-09-26 DOI:10.1016/j.ijfatigue.2024.108616

Niklas Sayer , Markus Fried , Sebastian Münstermann

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Abstract

Crystal plasticity simulations of materials to assess the fatigue response on the microscale are becoming increasingly popular in industrial application. However, in the case of parts made from cast Ni-base superalloys, the amount of pores in a part combined with the fine spatial discretization around the pores needed due to strong mechanical gradients quickly leads to a computationally impractical number of mesh elements. In this paper we show an alternative to explicit crystal plasticity modeling of part-scale porosity by introducing a Monte-Carlo submodel that recombines the fatigue response of single pores predicted by crystal plasticity into the fatigue response of the pore agglomerate. The model can be applied in realtime due to the use of precomputed crystal plasticity results. We demonstrate that fatigue indicator parameters predicted by the Monte-Carlo submodel agree well with those predicted by explicit crystal plasticity simulations. Lastly, we apply the proposed model to study the influence of different porosity volume percentages, pore sizes and pore morphologies on the fatigue indicator parameters of a cast MAR-M247 superalloy.

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根据晶体塑性建立铸造超合金裂纹起始模型的蒙特卡洛方法

对材料进行晶体塑性模拟，以评估微观尺度上的疲劳响应，在工业应用中越来越受欢迎。然而，对于由镍基超级合金铸造而成的零件，由于机械梯度较大，零件中的孔隙数量与孔隙周围所需的精细空间离散化相结合，很快就会导致网格元素数量在计算上不切实际。本文通过引入蒙特卡洛子模型，将晶体塑性预测的单个孔隙的疲劳响应重新组合为孔隙团聚的疲劳响应，展示了零件尺度孔隙率显式晶体塑性建模的替代方法。由于使用了预先计算的晶体塑性结果，该模型可以实时应用。我们证明，蒙特卡洛子模型预测的疲劳指标参数与显式晶体塑性模拟预测的参数非常吻合。最后，我们应用所提出的模型研究了不同孔隙度体积百分比、孔隙大小和孔隙形态对铸造 MAR-M247 超级合金疲劳指标参数的影响。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of Fatigue 工程技术-材料科学：综合

CiteScore

10.70

自引率

21.70%

发文量

619

审稿时长

58 days

期刊介绍： Typical subjects discussed in International Journal of Fatigue address: Novel fatigue testing and characterization methods (new kinds of fatigue tests, critical evaluation of existing methods, in situ measurement of fatigue degradation, non-contact field measurements) Multiaxial fatigue and complex loading effects of materials and structures, exploring state-of-the-art concepts in degradation under cyclic loading Fatigue in the very high cycle regime, including failure mode transitions from surface to subsurface, effects of surface treatment, processing, and loading conditions Modeling (including degradation processes and related driving forces, multiscale/multi-resolution methods, computational hierarchical and concurrent methods for coupled component and material responses, novel methods for notch root analysis, fracture mechanics, damage mechanics, crack growth kinetics, life prediction and durability, and prediction of stochastic fatigue behavior reflecting microstructure and service conditions) Models for early stages of fatigue crack formation and growth that explicitly consider microstructure and relevant materials science aspects Understanding the influence or manufacturing and processing route on fatigue degradation, and embedding this understanding in more predictive schemes for mitigation and design against fatigue Prognosis and damage state awareness (including sensors, monitoring, methodology, interactive control, accelerated methods, data interpretation) Applications of technologies associated with fatigue and their implications for structural integrity and reliability. This includes issues related to design, operation and maintenance, i.e., life cycle engineering Smart materials and structures that can sense and mitigate fatigue degradation Fatigue of devices and structures at small scales, including effects of process route and surfaces/interfaces.