## 4 Conclusions  
This study utilized CFD methods to simulate and analyze the airflow distribution within the multi-chamber bag filter in a practical engineering project. An optimization strategy involving the addition of three descending deflectors was proposed, with five different schemes designed. Scaled-down flow field distribution experiments were also conducted to validate feasibility and accuracy. Multi-dimensional indices were developed to evaluate the optimization effects of each scheme. Based on the research findings, the following conclusions can be drawn:  
1. Although there are numerical differences in airflow velocity and pressure across the chambers of the bag filter, they all share similar distribution characteristics. Uneven airflow distribution, primarily caused by high-velocity inlet airflow colliding with the hopper walls, leads to higher velocities near the bag bottom and sidewalls. This results in inconsistent airflow handling by the filter bags, varying levels of dust scouring due to vortex formation, and significant differences in wear and filter bag lifespan.
2. The addition of deflectors enhances airflow organization by guiding dust-laden air to collide with the deflectors, causing coarse particles to settle more efficiently and reducing excessive velocity, ensuring a more uniform flow into the filtration area. However, potential negative effects, such as increased abrasion and particle adhesion, should be addressed. Future research should focus on deeper investigation into the interactions between particles and deflectors to better understand their impact on filter performance.
3. Three Deflectors Scheme 4 demonstrates relatively superior optimization, achieving improvements of 40.3% in \(\Delta K_{qi}\), 47.4% in \(\Delta\overline{K}_{\xi}\), 51.8% in RMS \(\sigma\), and 51.6% in \(\mathbb{C}_{\textsc{p}}\) compared to the original model. It also reduced pressure drops by 11.2%, leading to lower energy consumption. This design minimizes channeling, resulting in more uniform airflow and significantly enhanced filtration efficiency. Furthermore, it effectively guides particle movement within the filter chamber, ensuring overall improved system performance.
4. The optimization measures have currently only been applied to the single-chamber model, and the results are valid for relatively low levels of fine particulate air pollution. Future research will focus on applying these measures to multi-chamber models and generalizing the results for industrial applications. Additionally, this study derives an optimal condition within a limited range of design structures. More deflector sizes and combinations will be explored, and more accurate experimental validation based on full-scale models will be considered.  
**Funding:** This research was funded by the National Key Research and Development Program of China, grant number 2022 YFC3902300. The APC was funded by Hongting Ma.  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** The raw data supporting the conclusions of this article will be made available by the authors on request.  
**Conflicts of Interest:** The authors declare no conflicts of interest.