The bridge structure inside porous wall is an important feature in diesel particulate filter (DPF) functionality. In this work, the formation process of bridge structure is simulated for the first time by domain decomposition-based lattice Boltzmann-cell automation probabilistic model (DDLB-CA model). The main goals of this work are modeling the formation process of the bridge structure to obtain detailed information and studying the effects of boundary conditions on the bridge structure formation process. The results show that particle clusters first appear in the narrow channels of the porous wall. The bridge structure develops on both sides of the narrow channel based on the deposited particle clusters. After the formation of the bridge structure, the number of soot particles captured by bridge structure increases significantly. These results indicated that the interception, inertia, and diffusion mechanisms play an important role in the early stage of particle filtration, but with the formation of the bridge structure, the bridge structure capture mechanism gradually dominates the capture of particles. The smaller the flow velocity, the earlier the bridge structure is formed. At the same flow velocity, for medium particles, the formation of the bridge structure is the fastest. These results all indicate the importance of the bridge structure capture mechanism in DPF filtration.

多孔壁内部的桥梁结构是柴油机微粒过滤器（DPF）功能的重要特征。在这项工作中，首次使用基于域分解的格子Boltzmann-cell自动化概率模型（DDLB-CA模型）来模拟桥梁结构的形成过程。这项工作的主要目的是为桥梁结构的形成过程建模以获得详细信息，并研究边界条件对桥梁结构形成过程的影响。结果表明，颗粒团簇首先出现在多孔壁的狭窄通道中。基于沉积的粒子簇，桥结构在狭窄通道的两侧发展。在形成桥结构之后，被桥结构捕获的烟尘颗粒的数量显着增加。这些结果表明，拦截，惯性和扩散机制在粒子过滤的早期阶段起着重要作用，但是随着桥结构的形成，桥结构捕获机制逐渐主导了粒子的捕获。流速越小，越早形成桥结构。在相同的流速下，对于中等颗粒，桥结构的形成是最快的。这些结果都表明在DPF过滤中桥结构捕获机制的重要性。桥梁结构的形成越早。在相同的流速下，对于中等颗粒，桥结构的形成是最快的。这些结果都表明在DPF过滤中桥结构捕获机制的重要性。桥梁结构的形成越早。在相同的流速下，对于中等颗粒，桥结构的形成是最快的。这些结果都表明在DPF过滤中桥结构捕获机制的重要性。