Abstract: Amidst the rapid advancement of digital fashion and artificial intelligence technologies, the contemporary apparel and textile industry is accelerating its digital transformation. The aesthetic appeal and authenticity of virtual clothing hinge on the simulation effects of virtual fabrics, which necessitates fabric simulation in digital apparel design to be grounded in a more realistic physical world. Once fabrics are transformed into garments, they are subjected to a variety of dynamic environments during actual wear rather than constant speed conditions. Therefore, this paper conducts an in-depth study of the dynamic drape performance and its characteristics by analyzing changes in fabric drape behavior under different dynamic conditions. It explores the influencing factors of fabric dynamic drape performance and the variation patterns of fabric drape coefficients at different rotational speeds, providing useful reference for research and applications in fabric dynamic simulation.
This paper selected 32 fabrics with different static drape performances and weights, and measured their dynamic drape coefficients at a total of 15 different rotational speeds ranging from 10 to 150 r/min (with increments of 10 r/min). These data revealed how the dynamic drape shape of the fabrics changed as the rotational speed increased. The mechanical properties of the fabric samples under low stress environment were measured using the KESFB-AUTO-A. The correlation between fabric mechanical properties and dynamic drape coefficients was analyzed for different dynamic environments. Building on this foundation, to further analyze the dynamic drape behavior of fabrics, the K-means clustering algorithm was applied to classify the collected data. Meanwhile, to more intuitively observe and analyze the trend of fabric dynamic drape coefficients as the rotational speed changed, the sample data closest to the cluster center in each cluster was selected as a representative. The least squares method was then applied to perform curve fitting on the original scatter plot data. To capture the nonlinear relationships within the data, a polynomial function was used as the fitting model, and the order of the polynomial was adjusted to achieve the best fitting effect. The order of the polynomial was determined based on the criterion of a goodness of fit (R²) greater than 0.9, ensuring that the fitted curve accurately reflected the data trend.
The study found that the bending, tensile, and shear properties of fabrics affect the dynamic drape performance to varying degrees. Among these, the influence of bending properties is the most significant, followed by tensile properties, and shear properties having a relatively weak influence. During the experiments, fabrics were ultimately classified into four categories based on their basic parameters and hand feel using a clustering algorithm: heavy and soft ones (Cluster 1), light and soft ones (Cluster 2), light and tight ones (Cluster 3), and heavy and tight ones (Cluster 4). According to the measurement data, the static drape coefficient of the fabrics, as well as the increment and increase amplitude of the dynamic drape coefficient after changes in speed, were identified as important indicators for classification. Meanwhile, based on the fitted curves and drape diagrams, it was observed that the wave numbers formed by the fabric due to gravity and bending characteristics would increase the dynamic drape coefficient. Furthermore, there exists a speed threshold for the dynamic drape performance of fabrics relative to their rotational speed. For light and soft fabrics, this threshold is 90 r/min, and for light and tight fabrics, it is 120 r/min. When the rotational speed is below this threshold, the fabric retained its shape more effectively; above this threshold, the shape is more prone to change.

Key words: dynamic drape coefficient, rotational speed, cluster analysis, drape behavior

摘要： 为探索不同转动速度下织物悬垂系数的变化规律和动态悬垂行为，测量了32种常见织物在不同转动速度下的动态悬垂系数，分析了织物力学性能与动态悬垂系数的相关性，运用K-means聚类算法，获取了4类织物动态悬垂行为，得到了不同转动速度下动态悬垂行为的变化趋势。结果表明：织物弯曲性能对动态悬垂性能的影响最为显著；织物因重力和弯曲特性所形成的波数会增加动态悬垂系数；织物的动态悬垂性能与其转动速度存在一个速度阈值，轻薄柔软型织物的速度阈值为90 r/min，轻薄紧密型织物的速度阈值为120 r/min。当转动速度低于阈值时，织物形态保持能力较强；高于阈值时，形态更容易变化。研究结果不仅深化了对织物悬垂行为的理解，还为织物动态仿真提供了有益参考。

关键词: 动态悬垂系数, 转速, 聚类分析, 悬垂行为