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Perspiration and heat are produced by the body and must be eliminated to maintain a stable body temperature. Sweat, heat and air must pass through the fabric to be comfortable. The cloth absorbs sweat and then releases it, allowing the body to chill down. By capillary action, moisture is driven away from fabric pores or sucked out of yarns. Convectional air movement improves sweat drainage, which may aid in body temperature reduction. Clothing reduces the skin's ability to transport heat and moisture to the outside. Excessive moisture makes clothing stick to the skin, whereas excessive heat induces heat stress, making the user uncomfortable. Wet heat loss is significantly more difficult to understand than dry heat loss. The purpose of this study is to provided a good compilation of complete information on wet thermal comfort of textile and technological elements to be consider while constructing protective apparel.

This paper aims to critically review studies on the thermal comfort of textiles in wet conditions and assess the results to guide future research.

Several recent studies focused on wet textiles' impact on comfort. Moisture reduces the fabric's thermal insulation value while also altering its moisture characteristics. Moisture and heat conductivity were linked. Sweat and other factors impact fabric comfort. So, while evaluating a fabric's comfort, consider both external and inside moisture.

The systematic literature review in this research focuses on wet thermal comfort and technological elements to consider while constructing protective apparel.

Nearly 75% of EU buildings are not energy-efficient enough to meet the international climate goals, which triggers the need to develop sustainable construction techniques with high degree of resilience against climate change. In this context, a promising construction technique is represented by ventilated façades (VFs). This paper aims to propose three different VFs and the authors define a novel machine learning-based approach to evaluate and predict their energy performance under different boundary conditions, without the need for expensive on-site experimentations

The approach is based on the use of machine learning algorithms for the evaluation of different VF configurations and allows for the prediction of the temperatures in the cavities and of the heat fluxes. The authors trained different regression algorithms and obtained low prediction errors, in particular for temperatures. The authors used such models to simulate the thermo-physical behavior of the VFs and determined the most energy-efficient design variant.

The authors found that regression trees allow for an accurate simulation of the thermal behavior of VFs. The authors also studied feature weights to determine the most relevant thermo-physical parameters. Finally, the authors determined the best design variant and the optimal air velocity in the cavity.

This study is unique in four main aspects: the thermo-dynamic analysis is performed under different thermal masses, positions of the cavity and geometries; the VFs are mated with a controlled ventilation system, used to parameterize the thermodynamic behavior under stepwise variations of the air inflow; temperatures and heat fluxes are predicted through machine learning models; the best configuration is determined through simulations, with no onerous in situ experimentations needed.

The aim of the work is to investigate structural behaviour of reinforced concrete (RF) beam retrofitted with basalt fibre (BF) fabric. The incorporation of BF showed enhancement in bending strength, to increase confinement and to repair damages caused by cracking. In the early decades, using BF for composite materials shaped BF as an excellent physical substance with necessary mechanical properties, highlighting the significant procedures ability.

Specimens were casted with U-wrapped BF and then evaluated based on flexural tests. In the test carried over for flexural fortifying assessment, BF reinforcements demonstrated a definitive quality improvement in the case of the subjected control sample; ultimately, the end impacts depend upon the applied test parameters. From the outcomes introduced in this comparison, for the double-wrapped sample, the modifications improved by 12% than that of the single-wrapped beam, which is identified to subsist for a better strengthening of new-age retrofitting designs.

The current research deals with the retrofitting of RC beam by conducting a comparative experiment on wrapping of BF (single or double BF wrapping) in improving the mechanical behavior of concrete.

It can be shown from the experimental results that increasing the number of layers has significant effect on basalt strengthened beams.

The aim of this study is to determine the fracture behavior of wool felt and fabric based epoxy composites and their responses to electromagnetic waves.

Notched and unnotched tensile tests of composites made of wool only and hybridized with a glass fiber layer were carried out, and fracture behavior and toughness at macro scale were determined. They were exposed to electromagnetic waves between 8 and 18 GHz frequencies using two horn antennas.

The keratin and lignin layer on the surface of the wool felt caused lower values to be obtained compared to the mechanical values given by pure epoxy. However, the use of wool felt in the symmetry layer of the laminated composite material provided higher mechanical values than the composite with glass fiber in the symmetry layer due to the mechanical interlocking it created. The use of wool in fabric form resulted in an increase in the modulus of elasticity, but no change in fracture toughness was observed. As a result of the electromagnetic analysis, it was also seen in the electromagnetic analysis that the transmittance of the materials was high, and the reflectance was low throughout the applied frequency range. Hence, it was concluded that all of the manufactured materials could be used as radome material over a wide band.

Sheep wool is an easy-to-supply and low-cost material. In this paper, it is presented that sheep wool can be evaluated as a biocomposite material and used for radome applications.

The combined evaluation of felt and fabric forms of a natural and inexpensive reinforcing element such as sheep wool and the combined evaluation of fracture mechanics and electromagnetic absorption properties will contribute to the evaluation of biocomposites in aviation.

The purpose of this study is to develop a magnetic resonance imaging (MRI)-safe iron-free electrical actuator for MR-guided surgical interventions.

The paper deals with the design of an MRI compatible electrical actuator. Three-dimensional electromagnetic and thermal analytical models have been developed to design the actuator. These models have been validated through 3D finite element (FE) computations. The analytical models have been inserted in an optimization procedure that uses genetic algorithms to find the optimal parameters of the actuator.

The analytical models are very fast and precise compared to the FE models. The computation time is 0.1 s for the electromagnetic analytical model and 3 min for the FE one. The optimized actuator does not perturb imaging sequence even if supplied with a current 10 times higher than its rated one. Indeed, the actuator’s magnetic field generated in the imaging area does not exceed 1 ppm of the B₀ field generated by the MRI scanner. The actuator can perform up to 25 biopsy cycles without any risk to the actuator or the patient since he maximum temperature rise of the actuator is about 20°C. The actuator is compact and lightweight compared to its pneumatic counterpart.

The MRI compatible actuator uses the B₀ field generated by scanner as inductor. The design procedure uses magneto-thermal coupled models that can be adapted to the design of a variety actuation systems working in MRI environment.

The purpose of this paper is to develop a concept and design to cast Al alloys/metal matrix composites (MMCs) by continuous casting process. The various steps involved in the evolution of the design have been reported and discussed in this study.

On the basis of developed design concept, initial prototype design has been prepared in this study. The casting process's melt flow pattern was studied via computer simulation, and the resulting changes were implemented in the original design. The single-phase fluid flow pattern through bottom feeding technique is studied. The equipment was fabricated based on computer simulation and water modelling studies. Finally, validation was performed for the preparation of Al alloys/ MMCs after parameter optimisation. The results were observed in the optical metallography to confirm the alloying and Al MMC preparation.

The developed continuous casting process with bottom feeding technique for the addition of constituent particles shows more efficiency in comparison to the existing batch processes. The final manufactured setup demonstrates effective Al alloy/MMC production as the basis for final fabrication has been accomplished by both computer simulation and water model test. In addition, the microstructure exhibits homogeneous distribution, validating the reliability of the setup.

Integrating continuous casting with continuous reinforcement or master alloy addition is novel in this area. The constraints that batch production had that have been rectified will also lower the contemporary cost of production.

Composite materials have revolutionized the aerospace industry by offering superior structural qualities over traditional elements. This study aims to focus on the development and testing of bamboo natural fiber-based composites enhanced with SiO₂ nanoparticles.

The investigation involved fabricating specimens with varying nanoparticle compositions (0, 10 and 20%) and conducting tensile, flexural, impact and fracture toughness tests. Results indicated significant improvements in mechanical properties with the addition of nanoparticles, particularly at a 10% composition level.

This study underscores the potential of natural fiber composites, highlighting their environmental friendliness, cost-effectiveness and improved structural properties when reinforced with nanoparticles. The findings suggest an optimal ratio for nanoparticle integration, emphasizing the critical role of precise mixing proportions in achieving superior composite performance.

The tensile strength, flexural strength, impact resistance and fracture toughness exhibited notable enhancements compared with the 0 and 20% nanoparticle compositions. The 10% composition showed the most promising outcomes, showcasing increased strength across all parameters.

This paper aims to identify the different system approach using Building Information Modelling (BIM) technology that is equipped with decision making processes. Maintenance planning and management are integral components of the construction sector, serving the broader purpose of post-construction activities and processes. However, as Precast Concrete (PC) construction projects increase in scale and complexity, the interconnections among these activities and processes become apparent, leading to planning and performance management challenges. These challenges specifically affect the monitoring of façade components for corrective and preventive maintenance actions.

The concept of maintenance planning for façades, along with the main features of information and communication technology tools and techniques using building information modeling technology, is grounded in the analysis of numerous literature reviews in PC building scenarios.

This research focuses on an integrated system designed to analyze information and support decision-making in maintenance planning for PC buildings. It is based on robust data collection regarding concrete façades' failures and causes. The system aims to provide appropriate planning decisions and minimize the risk of façade failures throughout the building's lifetime.

The study concludes that implementing a research framework to develop such a system can significantly enhance the effectiveness of maintenance planning for façade design, construction and maintenance operations.

This study aims to investigate the effects of nano or inorganic fillers on unsaturated polyester’s (UPE) thermal, mechanical, and physical properties. UPE reinforced with nanoparticles shows better properties than the pure polymer itself. Nano or inorganic fillers are used in the polymeric matrix to improve thermal, mechanical and physical properties.

To improve thermal, mechanical and physical properties, UPE resin was modified with silica (S), boron nitride (BN) and S/BN hybrid nanoparticles at different ratios. Viscosity and solids content measurement, Fourier transform infrared spectroscopy, contact angle measurement, scanning electron microscopy (SEM), thermogravimetric analysis (TGA) and thermal conductivity coefficient tests were performed on the samples.

In the SEM analysis, the UPE sample showed a smooth appearance, while all samples containing additives showed phase separation and overall heterogeneous distribution. TGA results demonstrated that the thermal stability of the resin increased in the presence of S and BN additives. According to the results, it was observed that the presence of S and BN additives in the UPE resin and the use of certain ratios improved the resin properties.

As a result of the literature search, to the best of the authors’ knowledge, no study was found in which BN nanoparticles were included in the UPE resin together with S.

At the moment, in terms of both research and commercial products, smart shoe technology and applications seem not to attract the same magnitude of attention compared to smart garments and other smart wearables such as wrist watches and wrist bands. The purpose of this study is to fill this knowledge gap by discussing issues regarding smart shoe sensing technologies, smart shoe sensor placements, factors that affect sensor placements and finally the areas of smart shoe applications.

Through a review of relevant literature, this study first and foremost attempts to explain what constitutes a smart shoe and subsequently discusses the current trends in smart shoe applications. Discussed in this study are relevant sensing technologies, sensor placement and areas of smart shoe applications.

This study outlined 13 important areas of smart shoe applications. It also uncovered that majority of smart shoe functionality are physical activity tracking, health rehabilitation and ambulation assistance for the blind. Also highlighted in this review are some of the bottlenecks of smart shoe development.

To the best of the authors’ knowledge, this is the first comprehensive review paper focused on smart shoe applications, and therefore serves as an apt reference for researchers within the field of smart footwear.