The adhesion forces of particles on rough walls are important for particle–wall interactions in particle deposition, rebound, and resuspension. For the micron-scale graphite particles and sub-micron-scale rough walls in high-temperature gas-cooled reactors, a mathematical adhesion model is proposed based on the Johnson–Kendall–Roberts theoretical model and the assumption of asperity heights with Gaussian distribution. A statistical roughness parameter, the root-mean-square wall roughness height, is used to reflect the influence of roughness on adhesion. Meanwhile, an atomic force microscope (AFM) is used to measure the adhesion forces between different particles and rough walls, then the proposed model is verified based on related AFM measurements and compared with previous adhesion models. Although the AFM results exhibit considerable scatter, the statistical adhesion falls into the prediction range of the proposed model. The results show that the present model can explain the effects of material properties on adhesion and be extended to other AFM measurements. The present study provides a convenient and practical mathematical model for adhesion between particles and rough walls for engineering applications.

颗粒在粗糙壁上的附着力对于颗粒在沉积，回弹和再悬浮中的相互作用至关重要。对于高温气冷反应堆中的微米级石墨颗粒和亚微米级粗糙壁，根据约翰逊·肯德尔·罗伯茨理论模型和具有高斯分布的粗糙高度的假设，提出了一种数学粘附模型。统计粗糙度参数，即均方根壁粗糙度高度，用于反映粗糙度对附着力的影响。同时，使用原子力显微镜（AFM）测量不同颗粒与粗糙壁之间的粘附力，然后基于相关的AFM测量结果对所提出的模型进行验证，并将其与以前的粘附模型进行比较。尽管原子力显微镜的结果显示出很大的分散性，统计粘附力落在所提出模型的预测范围内。结果表明，该模型可以解释材料性能对附着力的影响，并可以扩展到其他原子力显微镜测量。本研究为工程应用中的颗粒与粗糙壁之间的粘附提供了一种方便实用的数学模型。