Waterproof sheets for nursing care are designed to protect bedding during urinary incontinence, and their consumption has increased in recent years. Considering data related to heat and moisture transfer properties for commercially available waterproof sheets, we proposed objective indices for evaluating moisture transfer characteristics based on humidity changes over time obtained with a simulated skin device, and their usefulness was examined. Experiments were conducted under controlled conditions at 20 degrees C and 65% RH, using 16 types of commercially available waterproof sheets and two types of cotton sheets as controls. Physical characteristics, as well as heat and moisture transfer properties of each sample-including contact cooling/warming sensation, moisture permeability, and water absorbability-were measured. In wetting simulations with a simulated skin device, water was discharged for 2 min so that the entire surface of the simulated skin became wet, and the temporal changes of temperature and humidity inside the sheets were recorded for 3 h. Heat transfer properties were evaluated using thermal resistance and evaporative heat resistance. Moisture transfer properties were assessed through three novel indices derived from temporal humidity changes within the sheet: the rate of humidity rise, the duration of high humidity, and the rate of humidity change. No inconsistencies were observed between these indices and the measured properties of the sheets. The use of these indices enables evaluations of the microclimate inside waterproof sheets, perceived wetness, and risks of pressure ulcers when sheet users experience urinary incontinence. From the perspective of improving users' quality of life, these indices are considered useful for assessing product performance. This study suggests that optimal waterproof sheets should exhibit low evaporative heat resistance, a low rate of humidity rise, a short duration of high humidity, and a low rate of humidity change, demonstrating the possibility of objective evaluations of product quality.
Visual drape simulation of fabrics enables a more intuitive demonstration of their comprehensive mechanical properties. However, the current process relies heavily on time-consuming physical prototyping and repeated experiments, resulting in poor timeliness. This paper aims to study the rapid prediction method of fabric drape visualization. This paper proposes a fast and reliable visual prediction method of fabric drape based on coil structure and physical particle simulation, using weft-plain knitted fabric as example. First, mesoscale decoupled finite element simulations were conducted based on the structural and yarn characteristics of 70 weft-plain knitted fabric. The obtained fabric morphological mechanical parameters were specifically used to match the virtual mechanical parameters of the Mass-Spring Model (MSM). Through MSM-based drape visualization simulations and experimental validation, a more reliable and comprehensive drape parameter and visual image database was established. Then, a random forest regression algorithm suitable for high-dimensional and nonlinear fitting was employed to construct a drape prediction model using coil structural parameters as independent variables. Based on the prediction results, the corresponding visual simulation effects could be rapidly matched and displayed. Finally, validation on the test set showed a high average R2 value of 0.8124, with 95% of the projected area errors confined within a small range of +/- 4.8 cm2. Moreover, compared to the time-consuming physical prototyping and experiments, the efficiency of visual prediction was significantly improved. Therefore, this method can rapidly and reliably predict drape visualization based on predefined structural parameters, contributing to the advancement of fabric digitization, intelligent garment manufacturing, and related industries.
Electrostatic-induction-assisted solution blowing spinning (ESBS) is a novel and advanced nanofiber fabrication technology. Finite element simulations were used in this study to determine the distributions of the ESBS airflow and electric fields. The airflow axial velocity and the amount of surface charge on the jet are extracted and used to investigate process parameters. Comparative experiments confirmed that the average diameter of ESBS nanofibers is positively correlated with the distance between needle and electrode (DNE), injection speed, and diameter of electrode (DE), while negatively correlated with length of electrode (LE), air pressure, and voltage. The distance between needle and receiver (DNR) has little effect on the fiber diameter. The fiber web porosity increases with increases in some process parameters (DE, DNE, and DNR), while decreasing with increases in other process parameters (air pressure, injection speed, LE, and voltage). Fiber cover rate increases with increasing injection speed or voltage. Other process parameters have little effect on fiber cover rate. Orthogonal experiments indicate that the weighted order of influence of the process parameters on the average fiber diameter is: injection speed > air pressure approximate to voltage > DNE > DE > DNR approximate to LE. The optimal fabrication scheme was determined by analyzing the results of the orthogonal experiments. The results of this study provide theoretical and experimental bases for the promotion and application of ESBS nanofibers in biology, energy, filtration and other fields.
