Air permeability is one of the fundamental textile properties influencing the design of comfortable clothes. In particular, it is very important in the field of technical textiles. Air permeability depends mainly on the fabric structure, which can be described by yarn linear density, type of yarn, warp/weft density and weave. The purpose of our study was to identify a small number of parameters that have the strongest influence on air permeability of cotton fabrics and enable its good prediction. Rather than focusing on the constructional parameters, we decided to include a composite parameter known from the theory of fluids, hydraulic diameter of pores, which treats rectangular-shaped pores as circular ones. In addition to the hydraulic diameter of pores, two other parameters were used for the prediction of air permeability: the number of macro pores and the total porosity of woven fabrics. 36 woven fabric samples were produced using nine frequently implemented weave types together with two warp densities (29.3 and 22 ends/cm) and two weft densities (15 and 20 picks/cm), resulting in four different densities of woven fabrics. The yarns had the same linear density and material in warp and weft directions. Air permeability measurements were performed with the Air Permeability tester FX 3300 Labotester III (Textest Instruments) according to the ISO 9237:1995 (E) standard. Principal components analysis revealed that the four investigated plain weave specimens behave differently than the other samples, which might be explained by weave structure. This multivariate statistical method also confirmed the appropriateness of the three selected parameters for air permeability prediction which was done using multiple linear regression. The high adjusted coefficient of determination (R²) value of 0.94 indicates that the model explains variability in the air permeability to a large extent.

This paper deals with the possibility of a fast and accurate assessment of the number, size, and distribution of pores in transparent woven fabrics based on light penetration. The procedure of analyzing the pore structure in the fabrics based on a digital image is presented in detail. Fabric pores are treated as image particles and analyzed with the Java-based image processing software ImageJ. The obtained data relate to the constructional parameters of the fabric that allow for further analysis, provide the possibility to compare structurally similar or different samples as well as double check the results generated by optical or other means. This paper describes work on plain and similar to plain weaves. The conducted analysis revealed several expected and some unexpected results. Among the former, we can list the range of pore sizes in the examined woven fabrics, the distribution of pores in regard to their similarity, and the effect of dents. Examples of the latter are the magnitude of the cumulative percentage of pores in regard to the weave and the degree to which they participate in the inter-yarn and inter-fiber pores.

Porosity, the measure of the open spaces within a fabric structure, is a decisive factor in the performance of textiles. It influences breathability, permeability to liquids or gases, and suitability for various industries such as apparel, medical, and technical textiles. This study compares classical porosity calculation methods with non-destructive image analysis for 24 woven fabric samples that differ in density and weave pattern. Factors such as fabric density, weave pattern, illumination conditions, magnification, and the influence of the Otsu and Yen threshold algorithms were considered. The multifactor ANOVA statistical analysis shows that fabric density and weave pattern significantly influence porosity, with illumination playing an important role, while the threshold algorithm has a minor influence. A strong correlation is found between the actual fabric porosity and the results of the image analysis, except for double-sided illumination (reflective and transmissive), where the correlation is weakest. This comprehensive investigation provides valuable insights into the reliability of different porosity assessment approaches, which is essential for applications in various textile industries.

In this article, the breaking elongation properties of woven fabrics with incorporated PBT yarns are presented. Different polybutylene terephthalate (PBT) yarns (multifilament PBT yarn, cotton core yarn and twisted viscose yarn, both with PBT in the core) were used. Textured PBT yarns have latent elastic properties, which become visible after the thermal treatment by the finishing process. The aim was to determine which of the constructional parameters is most important in analysing the shrinkage of fabrics after treatment, breaking elongation properties of all tested fabrics, and breaking elongation properties of woven fabrics before and after treatment. A multivariate statistical method ANOVA was used for the analysis. The results show that treatment was by far the most influential factor in the study of breaking elongation of all tested fabrics. When analysing the fabrics separately before and after treatment, the construction of the PBT yarn and the weave were found to be statistically significant parameters.

The aim of the research was to investigate the usability and legibility of 3D printed typeface characters in smaller sizes. In the experimental investigation two software programs for letter modelling, three typefaces, three type sizes, two weight options, and two printing materials were tested. The samples were analysed visually and with image analysis. The legibility tests were conducted in laboratory conditions and testing chamber. The participants were asked to read pangrams and answer close-ended questions. The reading speed and understanding of the text were measured and analysed. It was found that the success of printing parts of letters, as well as their recognition and visual evaluation, is most often influenced by two analysed factors, i.e. weight option and type size, in all three typefaces. We established that the type size is statistically significant, and that the typographic tonal density is influenced by the typeface and the material used. Practitioner summary: The research presents the investigation of usability and legibility of 3D printed typefaces at smaller sizes. Five variables were analysed visually and with image analysis. Typographic tonal density, reading speed, and text comprehension were evaluated. The findings demonstrated that weight option, type size, and material influence the reading speed and text comprehension.

The comfort properties of fabrics are closely related to their structural parameters. Various material and construction changes affect thermal insulation, permeability properties, wetting and water vapour permeability, which are the most important properties related to the comfort of textiles. Thermal comfort evaluation plays a crucial role in the development of textiles and is mainly carried out in the three aspects of breathability, heat transfer and moisture transfer. The aim of the research is to investigate the comfort and flame retardant properties of knitted fabrics made of four different materials: three conventional (cotton, Tencel and Micromodal) and one flame retardant material (blend of Tencel, polyacrylate, Modacryl-Tayrilan) that can be used for firefighter underwear. All materials were knitted in three different constructions of double jersey. It was found that the blend of Tencel, polyacrylate and Modacryl-Tayrilan is a truly flame retardant material suitable for firefighter underwear and has good comfort properties.