The research aims the development of knitted reinforcement structures for inducing self-diagnostic properties into knitted reinforced composites for structural health monitoring. Conductive carbon fiber was used in knitted inlaid structures as inlay yarns, and l × 1 Rib knitted base fabric of polyester filament yarn was used for knitting. The reinforcement’s conductive nature induced self-diagnostic properties into composites using correlation of mechanical damages and changes in electrical resistance values. Single and double stimuli layers and inlay patterns of 3 × 1, 6 × 1 and 9 × 1 was used to check their impact on self-diagnostic properties. Mechanical testing and real-time electrical resistance monitoring proved knitted structures as a solution to induce self-diagnostic properties into composite materials. Composites having double stimuli (conductive) layers exhibited better self-diagnostic properties than single stimuli layer composites, and the self-diagnostic properties also improved as the inlay pattern of reinforcement moved from 9 × 1 to 6 × 1 and 3 × 1 inlay. Such knitted reinforced self-diagnostic composites could be practically used in structural health monitoring applications, e.g., complicated structures of large buildings infrastructures and machinery which require record of each minor happening with structures to keep smooth and successful running of the system.

Knitted fleece fabrics with superior comfort characteristics are chiefly focused in winter wear. Thermal characteristics are an area of interest in selecting fleece clothing. However, environmental hazards also need to be focused. Fleece clothing is worn in cold areas having higher ultraviolet rays exposures. Hence the clothing should have the capability of combating environmental challenges. The study focuses on engineering variable fleece structures with different materials. Cotton, nylon, and polypropylene fleece patterns have been knitted using fleece 1:1, 3:1, and 2:2 patterns. The designs vary by tuck and miss stitch configurations in the fleece course. Comfort characteristics were determined through air permeability, moisture management, and thermal resistance tests. Performance criteria were evaluated in terms of pilling resistance and ultraviolet protection factor (UPF) investigation. Structures and materials owing better comfort characteristics with satisfactory UPF have been predicted as safe clothing in UV affected zones, that is, fleece 3:1 possessed the optimum comfort characteristics and UPF simultaneously; however, the mechanical performance was better for 2:1 and 1:1 fleece fabric due to less amount of miss stitch floating yarns.

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Compared to other textiles, socks are made at the lowest cost and have the highest consumption rate, making them one of the least-lasting fabric goods in the clothing industry. Socks are available in a wide range of fibers blends, that is, cotton, wool, nylon, acrylic, polyester, olefin, spandex, etc. As an element of footwear, socks act in tandem with the foot and shoe, influencing the temperature and moisture levels of the feet. The comfort of clothing next to the skin in terms of temperature and moisture is gaining more and more attention. Pilling is a serious issue with wool items, and less pilling is required since it negatively impacts the esthetic, comfort, and longevity of the fabric. This research has investigated socks pilling tendency and thermo-physiological comfort properties, that is, air permeability and thermal resistance made by wool/polypropylene blend yarn. Three different combinations of wool/polypropylene yarns on the main and platting side of the socks were used at two different tightness levels. Polyurethane finish has been applied to check the socks’ behavior after the finish application. Statistical analysis showed that finished samples knitted with wool/polypropylene as a main yarn offer the best results against the pilling test while sample code ANL, an unfinished sample, offers the best results regarding air permeability, thermal resistance, and overall moisture management capacity.