The macroscopic mechanical behaviors of granular construction materials are fundamentally linked to the morphology of the particles. Characterization of real particles is important for exploring the linkage through physical investigation, while regeneration of virtual particles is a key step for reliable numerical investigation. This paper proposes a Fourier series-based approach to represent and characterize two-dimensional (2D) general-shape particles, which is more versatile than the traditional complex Fourier analysis for characterizing 2D nonstar-like particles. Additionally, a numerical algorithm that combines the concepts of principal component analysis and empirical cumulative distribution functions is proposed to generate 2D general-shape particles that bears the morphological features of real particles. The approach can consider both the intrinsic relationships among the Fourier coefficients for the x and y coordinates at the first degree of harmonics. The empirical correlation among the Fourier coefficients at different degrees of harmonics can also be taken into account. Precise controlling the elongation property of virtual particles is also readily achievable in this approach. A comprehensive study with two types of construction material particles reveals that the proposed approach is promising.

颗粒状建筑材料的宏观力学行为从根本上与颗粒的形态有关。真实粒子的表征对于通过物理研究探索链接至关重要，而虚拟粒子的再生是可靠数值研究的关键步骤。本文提出了一种基于傅立叶级数的方法来表示和表征二维（2D）一般形状的粒子，它比用于表征2D非星形粒子的传统复杂傅立叶分析具有更多的用途。此外，提出了一种将主成分分析和经验累积分布函数相结合的数值算法，以生成具有真实粒子形态特征的二维普通形状粒子。 x 和y处于第一谐波程度。还可以考虑不同谐波度下傅立叶系数之间的经验相关性。在这种方法中，也容易达到精确控制虚拟颗粒的伸长性能的目的。对两种类型的建筑材料颗粒进行的全面研究表明，该方法很有希望。