**5. Conclusions**

The angle of repose, coordination number (CN) and bottom porosity distribution (BPD) of pellet piles were studied by DEM simulation and experimental methods. A charging system mimicking that of a blast furnace, but in 1:10 scale was designed to simulate the pile formation of iron oxide pellets. The effects of DEM parameters and packing method on the angle of repose were also studied, including the drop height in the Discharging Method and properties (lifting velocity, barrel size) of the Lifting Method. Some of the results are highlighted in the following.

The angle of repose shows a positive correlation with static and rolling friction coefficients. The angle of repose formed by the Lifting Method is bigger than that obtained by the Discharging Method. When the drop height increases, the angle of repose decreases, but this trend will weaken when the static friction coefficient becomes large. In the Lifting Method, the angle of repose tends to decrease with an increase in the lifting velocity or in the barrel size, but the trend is less clear for pellets with large friction coefficients. The size of the bottom circle of the heap is significantly reduced with an increase in the friction coefficient. Appropriate values of the rolling and static friction coefficients for the pellets were found to be 0.12 and 0.15, respectively.

The porosity distribution in the bottom of the heap (BDP) along the heap diagonal shows a V-type behavior, where the value in the center is smaller than those at the edges. The BPD shows an increasing trend with the increase of the friction coefficient. CN is an important parameter reflecting the internal structure of the pile, and expectedly, it shows a negative correlation with porosity. The maximum of the frequency distribution of CN, which occurs at CN ≈ 4, exhibits a negative correlation with the static friction coefficient and eventually remains unchanged when the coefficient grows larger than 0.6. CN is not significantly affected by the rolling friction coefficient.

**Author Contributions:** Conceptualization, H.W. and Y.Y.; methodology, H.W. and M.L.; Software, H.W. and M.L.; validation, H.W. and Y.L.; formal analysis, Y.G.; investigation, H.W. and Y.Y.; resources, H.W. and M.L.; data curation, H.W. and Y.G.; writing, H.W; supervision, Y.Y. and H.S.; funding acquisition, Y.Y.; Writing-Review and Editing, H.S. and H.W.

**Funding:** This research was funded by The Program for Professor of Special Appointment (Eastern Scholar) at Shanghai Institutions of Higher Learning grant number TP2015039.

**Acknowledgments:** The authors are grateful for the financial support from The Program for Professor of Special Appointment (Eastern Scholar) at Shanghai Institutions of Higher Learning (No. TP2015039). The Discrete Element Method was conducted using LIGGGHTS 3.5.0 open source.

**Conflicts of Interest:** The authors declare no conflict of interest.
