## 7 Conclusions  
A three-dimensional unsteady simulation was performed for a real-sized industrial-scale classifier using the TWC-CFD-DPM in ANSYS Fluent 2022 R2, with the assistance of a high-performance computing (HPC) system. The two-way gas-particle interactions in the flow field were considered in the present study. The effects of the four different guide cones on the complex two-phase flow field and the classification performance were investigated and analyzed. The following conclusions were obtained:  
1. The guide cone's structural parameters (SPs) significantly affect the flow field distribution and represent some of the key factors in improving the efficiency of classifiers. Upon changing the bottom diameter (\(d\)) of the guide cone and the material recirculation gap size, the size, shape, position, and rotational direction of the vortices formed in the secondary classification region and classification chamber were changed. These vortices directly affected the particle flow and the classification ability in the secondary and major classification regions, impacting the classification performance of the classifier (as shown in Section 4.6). 2. The highest Newton efficiency (95.5%) was achieved with CHL3 with a bottom diameter of 808 mm, while the guide cone with CHL1 had the lowest classification efficiency. In addition, the pressure drop and cut size increased gradually from CHL1 to CHL4. This meant that the energy consumption in the plant increased accordingly. In terms of KPIs, the cut size \(d_{50}\) for CHL3 was the smallest (0.26 mm), and the classification sharpness index (\(K\)) under the different guide cone structures was in the range of 1.23 to 1.38. Among these, CHL4 provided the smallest \(K\). Therefore, when evaluating the classification performance using these typical classification indices, that of the micron air classifier with a bottom diameter of 808 mm is the best. 3. The simulation results were verified by comparing them to the experimental data measured using CE-certified sensors and equipment. Regarding the KHC, both CHL3 and CHL4 provided particle size distribution curves that satisfied the requirement for the quartz material particle range of 0 to 400 \(\upmu\)m, used in the production of quartz-based artificial stone at the Vicostone Plant by the Phenikaa Group. However, CHL3 provided the highest classification efficiency in comparison with the remaining cases. Therefore, CHL3 was the best guide cone structure for the production of quartz material (0-400 \(\upmu\)m). 4. Each CHL produced its own particle size distribution curve. Producers can select a particular CHL structure to achieve the best classification efficiency and satisfy the required particle size distribution curve according to each specific product's formula in the production of quartz-based artificial stone. These results highlight some of the fundamental factors for structural improvement to achieve the best classification performance of micron air classifiers according to the production requirements, particularly in terms of production efficiency. **Author Contributions:** Conceptualization, N.X.H., H.T.D. and N.T.D. ; formal analysis, N.X.H. and H.T.D. ; investigation, N.X.H. and H.T.D. ; methodology, N.X.H. and H.T.D. ; supervision, N.X.H. and N.T.D. ; validation, N.X.H. and H.T.D. ; visualization, H.T.D. ; writing--original draft, N.X.H. and H.T.D. ; writing--review and editing, N.X.H. and H.T.D. All authors have read and agreed to the published version of the manuscript. **Funding:** This research received no external funding. **Institutional Review Board Statement:** Not applicable. **Informed Consent Statement:** Not applicable. **Data Availability Statement:** The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding authors. **Acknowledgments:** The authors are grateful to the Vicostone Plant, Phenikaa University, Advanced Technology Joint Stock Company, and Phenikaa Group for supporting this work.