## 6 Conclusions  
This research work focuses on the micro-parametric calibration of mortar based on a cylindrical specimen, which is modeled using the DEM, considering the effect of particle size scale and particle size distribution on the mechanistic behavior of the specimens. The numerical solver used for conducting the simulations was ITASCA's PFC-2D, using three particle scales (1.0, 1.5, and 2.0) and from one to four particles to represent varying particle size distributions. Additionally, a parametric analysis is implemented with a variation of the micro-parameter at scale factors of 0.25, 0.50, 1.50, and 2.0. The most relevant findings of this work are:  
* The DEM's stress-strain curves are well-fitted with respect to the experimental data considering different particle size scales. Nonetheless, it is observed more localized concentrations of forces in the DEMs when the particle size scale is smaller;
* There is an increase in \(\mu\) and \(\phi\) micro-parameters when there is an increment in the particle size scale factor due to the reduction of particle contact area in the specimens;  
Figure 17: Parameter analysis results. Red arrows show the sequence direction of change as the scale factors are being increased. * The DEM's stress-strain curve shows a better agreement with the experimental data when increasing the particle size distribution resolution. It is observed more localized concentrations of forces in the DEMs when the particle size distribution resolution is higher;
* The \(\overline{\phi}\) and \(\mu\) micro-parameters increment and the \(\overline{c}\) decrement when there is a decrement in the particle size distribution resolution. This is due to the decrease in the particle interlocking caused by the reduction of the particle size distribution resolution;
* The ELC micro-parameter increments the macro-Young's modulus of the DEM. The \(\overline{c},\ \mu,\ \phi\) micro-parameters increment the peak stress. Additionally, the \(\overline{\sigma_{c}},\ \overline{\phi}\) and \(\mu\) micro-parameters increment the hardening section;
* It is recommended that the DEM contains at least two particle sizes to improve the particle interlocking and ensure that the micro-parameters values and the mechanistic behavior represent the experimental observations. Finally, from the results presented in this work, it is concluded that it is possible to produce a computationally efficient model that can later serve as a reference for future research accounting for other control variables such as particle shape, particle size distributions, the exploration of damage propagation effects, and most importantly their corresponding uncertainty quantification and propagation effects in masonry systems. Conceptualization, M.O.-C., L.F.-B. and Z.M.-C.; Methodology, Z.M.-C.; Software, M.O.-C.; Validation, M.O.-C., L.F.-B. and Z.M.-C.; Formal analysis, M.O.-C., L.F.-B. and Z.M.-C.; Investigation, M.O.-C., L.F.-B. and Z.M.-C.; Resources, Z.M.-C.; Data curation, M.O.-C.; Writing--original draft, M.O.-C.; Writing--review & editing, L.F.-B. and Z.M.-C.; Supervision, L.F.-B. and Z.M.-C.; Project administration, Z.M.-C.; Funding acquisition, Z.M.-C. All authors have read and agreed to the published version of the manuscript. Work presented in this paper was sponsored by multiple agencies throughout the course of multiple years of time and effort dedicated to populating the experimental database, including Consejo Nacional de Ciencia y Tecnologia (CONACYT) for the scholarship CONACYT-SENER and Texas A&M University (TAMU) for the Zachry Career Development II Professorship. Not applicable.