## 4 Conclusions  
The present work introduced a computational framework that aims to make use of data regarding the microstructural characteristics of composite materials and the mechanical properties of each phase, in order to predict the composite's macroscopic mechanical behavior. Overall, the framework is able to:  
* Extract statistical data describing the microstructure of AA7075 alloy and match the extracted surface fraction with the volume fraction of each phase;
* Build 3D SSRVEs by employing the DREAM.3D package, representing the two precipitate phases present in the alloy;
* Insert carbon fibers with the desired volume fraction and shape morphology, to mimic the microstructure of a randomly oriented MMC with discontinuous fibers;
* Perform tensile testing simulations with Abaqus FEA to these SSRVEs having appropriately adjusted the mechanical properties of each phase;
* Assess the macroscopic mechanical behavior of MMCs with respect to the volume fraction and the aspect ratio of CF by comparing this performance with that theoretically expected from fiber composite mechanics.  
Starting from the statistics retrieval stage, it becomes apparent that more than one microscopy image is required to precisely represent the statistics of the material. The  
Figure 12: (a) Stress–strain curves for 8% AA7075/CF MMCs with different aspect ratios and (b) a close-up around yield points.  
Figure 13: Yield stress of 8% AA7075/CF MMCs with different aspect ratios compared with shear-lag model.  
procedure outlined for obtaining the statistics, namely the SEM image segmentation, the color-based thresholding of each phase, the particle discretization, and, finally, the particle size measurement, is suggestive of yielding satisfactory results, close to the expected ones, even assuming that the surface coverage fractions of the image correspond to the volume fractions of each phase. Certainly, by employing a larger number of images, more reliable data will be obtained for both the volumes and the statistics of each phase.  
The process of building 3D digital data with DREAM.3D by utilizing the statistical parameters for the microstructure is highly efficient, as it was possible to convert 2D data into 3D data in a relatively fast and automated way. It was shown that inclusions of various shapes and sizes can be included within the ensemble and, thus, represent various types of particles, whether they are precipitates of alloys, which are the result of heat treatment, or whether they are reinforcing phases. Different types of reinforcing phases, either fibrous or shaped otherwise, such as particles or platelets, can also be introduced. In addition, it is also possible to simulate other types of composites, such as polymer or ceramic matrix composites or even structural materials (concrete).  
Finally, it was shown that the mechanical properties of MMCs as a function of the volume fraction and aspect ratio of CFs seem to confirm, up to a certain extent, the expected mechanical behavior of real fibrous composites. In particular, the validity of the rule of mixtures for the elastic modulus was shown, as well as an indication of the validity of the shear-lag model. As the micromechanical phenomena governing fibrous composites are quite complex, no further study of them was attempted in this work but, with appropriate use of the tools described, a more thorough investigation could be attempted.  
Conceptualization, A.K.; methodology, A.K.; software, I.M. and L.-A.K.; validation, I.M. and L.-A.K.; writing--original draft preparation, I.M.; writing--review and editing, A.K. and L.-A.K.; visualization, I.M. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Not applicable.  
The authors declare no conflict of interest.