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Well-designed compression sportswear can be used for the enhancement of athletic performance and reduction of injury. The material and geometric properties of fabric for compression sportswear are vital in achieving compression effects. This study evaluated and optimized the performance of fabric using the design of experiment (DOE) methods, the response surface method (RSM) and the finite element (FE) model. The evaluation and optimization procedure consisted of three phases. The first phase involved developing the FE model of a fabric tube and cylinder, and validated it by compression experiments involving different fabrics. The second phase evaluated the FE prediction using a five-factor experimental design, namely, hyperelastic properties, thickness, density, friction, and tensile strain. The third and final phase was an optimization process using RSM based on the evaluation results. Findings show that the FE predictions approach closely the results of validation experiments. The nonlinear elastic material properties (hyperelastic properties) and shape dimensions (thickness and tensile strain) of fabric tube were found to be important design factors in influencing contact pressure, while the density of fabric and interface friction coefficient played less important roles. The optimal FE model was determined using RSM analysis. The statistically based FE model was found to be an effective approach for evaluating and optimizing the design parameters of fabric for compression sportswear. The results can be applied to make sportswear that has different compression effects at selected anatomical locations to enhance performance and reduce injuries.

In clinical practice, fast assessment of contact pressure is usually calculated by Laplace’s Law, which neither provides detailed surface geometry for soft materials of the leg, nor offers sufficient predictive power for designing high-performance sportswear. To bridge this gap, this paper describes a finite element (FE) model of sports tights that was developed with a detailed anatomic male leg model to predict the compression effects of high-performance sportswear. Non-linear elastic material was applied on the sportswear material to model the large deformation behavior. Experimental validation on athletes was performed. A reasonable agreement was found in the experimental validation. Suitable profiles were achieved along the height of the leg, in terms of both contact pressure and clothing deformation (true strain or logarithmic strain). The maximum contact pressure (2222 Pa) occurred on the posterior of the ankle, while the maximum principal true strain of the sports tights occurred on the edge of the upper thigh. This study indicates that the proposed FE model is useful for the assessment of contact pressure distribution in sportswear.

Fabric drape is one of the most important factors which affect the graceful appearance of the garment. The drape coefficient is the widely used parameter to describe fabric drape but it needs other parameters to explain the fabric behavior. In this study, we have investigated the relationship between the fabric drape parameters such as drape coefficient, drape distance ratio, fold depth index, amplitude and number of nodes and low stress mechanical properties. Drape parameters were tested on a specially developed instrument based on a digital image processing technique and the low stress mechanical properties were tested by the Kawabata evaluation system. Then the drape parameters were predicted by constructing models using multiple regressions method and feed-forward back-propagation neural network technique. Simple equations are derived using regressions method to predict the five shape parameters of drape profile from the low stress mechanical properties. It is observed that bending, shear and aerial density affect the drape parameters most whereas the tensile and compression have little effect on the drape parameters.