The transverse motion of fabrics in domestic tumble dryers plays an important role in fabric heat and mass transfer using hot air. However, owing to a lack of effective and accurate experimental methods, little attention has been paid to this dynamic behavior. This paper describes how a high-speed detection system was utilized to track a tracer fabric dyed yellow as it was tumbled amongst other fabrics under different drying conditions, with the aim of identifying transverse fabric motion in a domestic tumble dryer. The experimental results demonstrate that fabric motion is complicated and can be affected by the size of fabrics as well as by drying load mass. Most fabrics inhabited two main regions, the bulk region and the disperse region. Increasing the size of the disperse region, where fabrics are projected into the air by the motion of the rotary drum, also expands the contact area between the fabric and the surrounding air, and augments the mixing motions of textiles. This contributes positively to the mass and heat transfer, and to the prevention of wrinkling. A higher drying efficiency together with a better smoothness appearance was observed with a fabric size of 80 cm $\times$ 80 cm and a mass of 3 kg. The high-speed detection system identified that specific ranges of fabric size and load mass led to increased fabric mixing and air-fabric contact.

In order to understand the impact of fabric properties on textile motion and drying performance in a domestic tumble dryer, mechanical properties of 10 different fabrics were measured and compared. A video capturing and processing system was utilized to track and record the centroid of the tracer fabric for characterizing fabric dynamics during the drying process. Based on the observation of motion trajectory, velocity profile and residence time distribution of the tracer fabric for each fabric, 10 motion indexes were established, and the correlation between fabric motion and drying performance was investigated. The results showed that fabric motions in a whole drying process were complicated and could be divided into four categories. The major property which influenced textile motion was weight of the fabric determined by ANOVA and the post hoc test using the LSD method. Various fabric motions during the drying process due to fabric mechanical properties had a direct impact on drying performance. Motion indexes were examined with their relation to the drying performance based on the regression analysis. The regression models to predict the two drying indexes by the motion indexes were developed with an explanatory power of around 90%.

Cotton wrinkling after home laundry has become an unfavorable phenomenon for consumers for a long time. Research has indicated that the wrinkles during tumble drying result from complicated changes of fabric physical properties as well as drying parameters such as temperature of drying air and drying duration. However, most of the research that has been done in this field has showed certain limitations, such as not simulating the real drying process or not understanding the cotton wrinkling mechanism accurately. This research, through an experimental design of 21 cotton fabrics in tumble drying, has explained the wrinkling behavior of woven cotton fabric in different drying stages and has investigated the wrinkling forming stage during tumble drying. Results showed that fabric characterization (such as thickness, density, and weight) does not significantly influence the smoothness appearance of the cotton fabrics in the tumble dryer. Moreover, heater power in the falling-rate period (heater power 2) and relative humidity dividing point between falling-rate period and unheated air blowing stage (air RH dividing point 2) were the most important factors that influenced the smoothness appearance of cotton fabrics. Therefore, it is indicated that wrinkles are formed in the latter part of the drying cycle. The results can provide a reference for dryer design and drying performance optimization.

A high-speed video camera was used to track a tracer textile as it is tumbled among other textiles in a domestic tumble dryer under different operating conditions, with the aim of investigating the mechanisms by which the mechanical action is imposed on textiles and affects drying performance during drying. These mechanisms were first recognized by comparing the clothes drying process to other well-researched chemical engineering processes. From the observation of the recorded motion processes, cotton textile transverse motion can be divided into three categories and a motion index system was derived to characterize the type of motion undergone. The impact of textile transverse motion on drying performance was numerically discussed based on the results of an analysis of variance and regression analysis. Results indicated that textile dynamics with more complexity and flexibility tended to have more mixing, shortened distance of moisture migration inside the fabric layer and fewer wrinkles formed, resulting in higher potential to have a better drying performance.

The purpose of this study is to investigate the effect of drying parameters on drying performance in an air-vented tumble dryer, and to optimize its drying performance by adjusting parameters. The critical drying parameters that influenced specific moisture extraction rate (SMER), final moisture content, evenness of drying, and smoothness appearance were determined by the analysis of variance in JMP software, which were rotational speed of the motor and load size, with clearly significant individual effects and binary interactions. In order to improve the applicability of the outcomes obtained in this study and to take into account the interactions between drying parameters and drum structure parameters on drying efficiency, non-dimensional analysis was used and the correlation between drying efficiency and dimensionless variables was studied. The Buckingham Pi theorem was applied to the problem to derive dimensionless Pi terms upon which the drying efficiency depends. A step regression analysis was then conducted to test the assumption that SMER was influenced by the dimensionless parameters based on the standard least squares fitting. Results indicated that the regression model showed an explanatory power of 73.8%. By adjusting the dimensionless parameters in the model, an optimized energy-saving drying program was obtained with the desirability goal of reducing the value of SMER. Compared with the original program, energy efficiency was improved by 32.4%.

To investigate the influence of fabric motion pattern on damage behaviors of cotton fabric during repeated tumble-drying in clothes dryer, smoothness appearance (SA), dimensional change, softness and microstructure were examined. Results indicated that repeated tumble-drying process led to several degrees of damages on cotton fabric owing to the continuous mechanical motion and the heat-humidity drying air environment. The morphological changes were primarily cracks, peeling-off, distortion, embrittlement and fracture, which depended on drying cycles and the distribution of force on fabric. These findings not only contribute to a better understanding of the mechanism of damage behaviors of cotton fabric in the tumble dryer, but also guide dryer manufactures to optimize drying programs for specific types of fabric.