Fabric Thickness Research Articles

Artificial neural network models for predicting breaking strength and abrasion resistance properties of woven fabrics with different chenille yarns

This study was carried out with aim of predicting some performance properties of fabrics with changing chenille yarn parameters. In this study, different chenille yarns were produced with parameters of pile length, yarn count and yarn type. Three different yarn types were used: polyester, acrylic and viscose. Four different yarn counts were used for each yarn type and four different pile lengths were used for each yarn count. Thus, 48 woven fabrics were obtained from 48 different yarns. The estimated properties included breaking strength in weft-warp direction and abrasion resistance, and these properties formed output data. As input data, yarn properties such as pile length, yarn count and yarn type; fabric properties such as fabric density, fabric thickness and fabric weight were used. Neural network toolbox in MATLAB was used to develop Artificial Neural Network (ANN) models. Different network structures were used to estimate three performance features, thus aiming to obtain more accurate results. Additionally, predictions were made with linear and nonlinear multiple regression models, and compared with ANN models. The R2 values ​​obtained from ANN models for breaking strength in the warp-weft direction and abrasion resistance were found to be 0.95, 0.74, 0.87, respectively, while they were found to be 0.32, 0.40, 0.41 for linear multiple regression models and 0.65, 0.27, 0.60 for nonlinear multiple regression models. The obtained ANN models were successful by a clear margin compared to statistical models.

Numerical and experimental investigation of floating wick solar still with a porous-media system

Wick-based solar desalination and solar-driven interfacial evaporation have attracted significant attention for their high efficiency in evaporation and salt removal. This study presents both experimental and numerical models for wick solar desalination. Cotton fabric, coated with black carbon for enhanced radiation absorption, was used as the evaporation medium in experiments due to its superior desalination, capillary, and salt rejection properties. Experimental results showed an evaporation rate of 1.57 kg/m2·h and efficiency of 81 % with freshwater. For saltwater (3.6 % salinity), the evaporation rate and efficiency were 1.24 kg/m2·h and 71 %, under 1000 W/m2 radiation. After validating the numerical model, the effects of porosity, capillary pressure, wick thickness, and thickness of the fabric’s upper (solar absorber) layer were examined. Results showed that reducing the solar absorber fabric thickness (from 9 mm to 0.6 mm), lowering porosity (from 0.97 to 0.3), and increasing wick thickness (from 1.5 mm to 10.5 mm) improved evaporation rates by 58.6 %, 27 %, and 28.4 %, respectively. Capillary pressure and fabric submerged length had minimal effects on evaporation. The model estimates that in real conditions at Jask coastal port (Iran), a configuration with greater wick thickness (6 mm vs. 3 mm), reduced solar absorber fabric thickness (1 mm vs. 1.5 mm), and lower porosity (0.75 vs. 0.93) could increase annual freshwater output by 26.6 % (from 796.6 to 1008.4 kg/m2). The cost per liter of produced water in the best-case scenario is estimated to be $0.0045.

Potential Penetration of Engineered Nanoparticles under Practical Use of Protective Clothing Fabrics.

The commercial application of engineered nanoparticles (ENPs) has rapidly increased as their unique properties are useful to improve many products. ENPs, however, can pose a major health risk to workers through exposure routes such as inhalation and dermal contact. Research is lacking on the protective nature of lab coats when challenged with ENPs. This study investigated multiwalled carbon nanotubes (CNTs), carbon black (CB), and nano aluminum oxide (Al2O3) penetration through four types of lab coat fabrics (cotton, polypropylene, polyester cotton, and Tyvek). Penetration efficiency was determined with direct reading instruments. The front and back of contaminated fabric swatches were further assessed with microscopy analysis to determine fabric structure with contaminated and penetrated particle morphology and level of fabric contamination. Fabric thickness, porosity, structure, surface chemistry, and ENP characteristics such as shape, morphology, and hydrophobicity were assessed to determine the mechanisms behind particle capture on the four common fabrics. CNTs penetrated all fabrics significantly less than the other ENPs. CNT average penetration across all fabrics was 1.83% compared to 15.74 and 11.65% for CB and Al2O3, respectively. This can be attributed to their fiber shape and larger agglomerates than those of other ENPs. Tyvek fabric was found to be the most protective against CB and Al2O3 penetration, with an average penetration of 0.06 and 0.11%, respectively, while polypropylene was the least protective with an average penetration of 40.36 and 15.77%, respectively. Tyvek was the most nonporous fabric with a porosity of 0.50, as well as the most hydrophobic fabric, explaining the low penetration across all three ENPs. Polypropylene is the most porous fabric with a porosity of 0.77, making it the least protective against ENPs. We conclude that porosity, fabric structure, and thickness are more important fabric characteristics to consider when discussing particle penetration through protective clothing fabrics than surface chemistry.

Viscoelastic behavior of warp-knitted spacer fabrics in iterative compression and decompression

In this study the viscoelastic behavior of warp-knitted spacer fabrics was investigated for compressional deformation. The fabric specimens were tested via loading and unloading time intervals under predetermined conditions. Following the upside tests, specimens were relaxed for 24 h to examine the recovery prior to completing the downside tests. The data obtained from the compression and decompression cycles were examined for stress relaxation and creep through stress–time plots. From the results it was observed that, despite the non-homogeneous structure of the spacer fabric, the specimens demonstrated exponentially changing behavior within the given time intervals. Since the response of fabrics to compression and decompression cycles can be expressed as a function of time, a mathematical approach was expressed in accordance with the time-dependent behavior of the fabrics regarding the monofilaments as bent beams. The responses of the fabrics to the experimental set up conditions were evaluated to determine the potential usage performances of the fabrics. Fabric thickness, number of monofilament yarns in the structure, and thickness of the monofilaments had the major effects on the performance of the fabrics. Future research could consider modeling studies to predict usage performance, and tailoring the fabrics before production.

Decorative 3D printing on textiles using elastomer TPU filament under different printing conditions

Purpose New sustainable approaches to fashion products are needed due to the demand for customization, better quality and cost reduction. Therefore, the decoration of fashion products using 3D printing technology can create a new direction for manufacturing science. Design/methodology/approach This study aims to optimize the 3D printing of soft TPU material on textiles. In the past decade, trials of using 3D printing in tailored fashion products have been done due to the 3D printing simplicity, low cost of materials and time reduction. Therefore, soft polymers can be multi-layer stepped-deposited smoothly with the fused filament fabrication process. Findings Even though there have been many attempts in the literature to 3D print multilayer polymer filaments directly onto textile fabrics by special-purpose 3D printers, only a few reports of decorative or personalized artefact 3D printing using open-platform filament material extrusion 3D printers. Printing speed, nozzle Z distance, textile fabric thickness and deposited strand height significantly affect 3D printing on textile fabric. Originality/value This study investigates the potential of 3D printing on textiles by changing the printing speed, nozzle hot end, Z distance and layer thickness. It presents two critical case studies of 3D printing soft thermoplastic polyurethane material on a cotton T-shirt and on a tulle textile to reveal the 3D printing on textile fabrics manufacturing challenges.

Experimental and numerical investigation on fluid flow and heat transfer behaviour of foam cladded pin fin heat sink

As technology advances, there is a growing demand for more efficient cooling solutions in electronics. Open-cell metal foams offer a unique solution, combining the strength of metals with the characteristics of foams, including being lightweight and having a high heat transfer area-to-volume ratio. Fully covering heatsinks with porous materials results in high pressure drop values, which is undesirable for electronics cooling. This study proposes a novel design that incorporates cladded aluminum foams on the pin fins within a heatsink. The hydrothermal performance of the proposed design is experimentally and numerically investigated. The results indicate that increasing the cladding thickness enhances heat transfer performance while increasing the pressure drop. For a heatsink with a pin fin diameter of 5 mm at the Reynolds number of 1121, the foam thickness of 5 mm depicts 46.5 % higher hydrothermal performance compared to a pin fin heatsink without porous while a fully porous covered heatsink depicts 38.9 % higher hydrothermal performance.

High-Temperature Sensing Using a Hollow-Core Fiber With Thick Cladding Tubes

High-Temperature Sensing Using a Hollow-Core Fiber With Thick Cladding Tubes

Natural Radiation Sourced Heat Stress: Thermal Comfort Depending On Color Factor In Safety Reflector Vests

Research has shown that personal protective clothing is not used by employees due to personal reasons such as lack of working comfort and heat stress. Solar (UV) radiation creates a heat effect on people working outdoors. Agricultural and construction workers are exposed to solar radiation and are known to be at high risk of heat stress, especially in arid climates. It is important for the person to individually evaluate the ambient temperature as hot or cold for the ergonomic conditions of the employee. In this study, for increasing safety and comfort expectations, heat changes in reflector vests based on colors of heating due to natural radiation were estimated with thermal camera measurements, and gained heat values ​​of vests with different fabric thicknesses were estimated using fuzzy logic modeling over time, and the effects of natural radiation on human health were examined.

Assessing compressive mechanical behavior of woven fabric green textile composite using finite element method

AbstractThe research aims to forecast the mechanical performance of a hybrid woven fabric natural composite subjected to compression, utilizing the three‐dimensional finite element method. A detailed finite element model of a plain woven fabric unit cell is created and analyzed for different materials like flax, basalt, and jute, and combinations of these materials (inter‐yarn hybrid basalt‐flax, jute‐flax and basalt‐jute fabrics). It is observed that fabric‘s response to compression is mainly influenced by the transverse longitudinal shear behaviour and the stiffness of the yarn cross‐section. Compression of single‐layer woven fabric involves yarn bending and compaction, resulting in varying fiber volume fractions in different areas due to compaction. The basalt‐jute hybrid plain woven fabric outperformed other plant‐based fiber fabrics with a polypropylene matrix in terms of mechanical performance under compression. Increase in yarn spacing and fabric thickness resulted in higher strain energy and displacement, attributed to changes in fiber volume fraction and crimp angle. Whereas, increasing yarn width led to a stiffer fabric due to increased contact area at the crossover region and higher bending rigidity, resulting in decreased strain energy and displacement. Importantly, this developed model can effectively simulate textile fabrics with diverse weaving patterns, material properties, and loading conditions.

An Investigation of Bursting Strength on Single Jersey Weft Knitted Fabrics

This paper investigates the bursting strength performance of single jersey weft knitted fabrics. The objective of the study is to find out the impact of the yarn count ,stitch length , stitch density, fabric thickness, loop shape factor, tightness factor ,GSM and porosity on the bursting strength of the single jersey weft knitted fabric. The experimental results have been statistically evaluated with Analysis ofVariance (ANOVA) test , Results show thatstitch length , stitch density, fabric thickness, loop shape factor, tightness factor ,GSM and porosity areeffective on bursting strength and individual ANOVA test results show that stitch density , fabric thickness , tightness factor , GSM and porosity are Individually effective on bursting strength .the GSM parameter of the fabric is fundamental for bursting strength , the correlation relation and R square values of GSM with bursting strength found to be in order 0.839& 0.9438

Optical fiber sensor based on magneto-optical surface plasmon resonance with ultra-high figure of merit

Compared to surface plasmon resonance (SPR), the sensors based on the magneto-optical SPR (MOSPR) technique have much higher figure-of-merit (FOM). However, there are no reports about applying MOSPR in the optical fiber structure now. In this work, a novel D-shaped optical fiber sensor based on the MOSPR technique is proposed. The D-shaped optical fiber is coated with a thin silver film and a magneto-optical (MO) material film of Cerium-doped Yttrium-Iron garnet (CeYIG). By applying a magnetic field on the sensing region, the magneto-optical Kerr effect (MOKE) of the CeYIG layer and the related MOSPR phenomenon could be excited when appropriate light is transmitted in the proposed optical fiber sensor. The influence of the structural parameters including the residual cladding thickness, silver and MO material film thicknesses are analyzed theoretically by the finite element method (FEM). With the optimal parameters, the sensor achieves the sensitivity of 5304 nm RIU−1. Since the peak width of MOSPR spectra is much narrower than that of the SPR spectra, the FOM of the sensor is largely enhanced to 3864 RIU−1 on average and 13260 RIU−1 in maximum, which surpasses the optical fiber SPR sensors vastly. The miniaturized and simple design of the D-shaped optical fiber MOSPR sensor, coupled with the ultra-high FOM, offers itself great potential in biochemical sensing applications.

Ultrawide dual contact strip fabricated quantum cascade lasers with reduced beam divergence angle

Power scaling through the broadening of the laser core in Quantum Cascade Lasers can extract greater average power from devices at the cost of mode quality. To improve transverse mode quality for ultrawide (>100 µm) devices, a dual contact strip waveguide geometry is designed and demonstrated, utilizing a reduced top cladding thickness, and modifying the gold electrical epi-side contact to affect mode competition. A 200 µm wide Dual Contact Strip laser emitting at 4.6 µm wavelength is measured with far-field full-width half-maximum of 2.5° in a central single lobe. Relative an identical waveguide without the dual contact strips, peak power was 30% higher and far field was 32% narrower. This demonstrates the ability to achieve fundamental-like far field behavior in very broad quantum cascadel asers while potentially simplifying the fabrication method.

Effects of nano‐TiO2 in configuration design and sound absorption of polyvinyl alcohol coated composite fabric structure

AbstractWith the rapid development of industrialization and population surge in modern society, noise pollution has been considered as a serious threat to human beings. In order to effectively reduce noise, the application of sound absorbing textile materials has gradually increased, also the rapid development of acoustic coating consists of conventional fiber layers and polymers. In this work, the surface morphology, micro‐structure and sound absorption properties of polyvinyl alcohol coated fabric and its composites were studied. It was found that the addition of nano‐TiO2 particles can obviously improve the sound absorption properties, and the absorption coefficient is related to fabric thickness. Furthermore, the surface of the coated fabric was compounded with melt‐blown nonwoven fabric, thus to fabricate composite sound absorber. This work indicates the good feasibility and promising application prospect of lightweight polyvinyl alcohol coated fabrics in noise reduction engineering.Highlights Combination of fiber layers and polymers for acoustic coating materials. Adding inorganic nano‐TiO2 particles with different contents. Different modification methods to improve the dispersion of coating. Composite structure with reduced thickness and increased sound absorption.

Release of microplastic fibers from synthetic textiles during household washing

Textile materials are one of the primary sources of microplastic pollution. The washing procedure is by far the most significant way that textile products release microplastic fibers (MPFs). Therefore, in this study, the effects of various textile raw materials (A acrylic, PA polyamide, PET polyester, RPET recycled polyester and PP polypropylene), fabric construction properties (woven, knitted), thickness and basis weight values on MPFs release at different washing stages (pre-washing, soaping/rinsing) were examined separately. To mimic the most popular home washing procedures, a 10-min pre-wash and a 35-min soaping/rinsing phase at 40 °C were selected for the washing procedure. Utilizing the Image J program on macroscopic images captured by a high-resolution SL. R camera, the microfibers collected by filtering the water have been visually counted. According to the results, knitted fabrics released fewer MPFs than woven fabrics, with the woven acrylic sample (A3-w) exhibiting the highest release (2405 MPFs). The number of MPFs increased along with the thickness and weight of the fabric. Recycled polyester was found to release more MPFs than virgin polyester under the same conditions (1193 MPFs vs. 908 MPFs). This study demonstrates how recycled polyester, although initially an environmentally beneficial solution, can eventually become detrimental to the environment. Furthermore, it is known that the pre-washing procedure—which is optional—releases a lot more MPFs than the soaping and rinsing procedures, and that stopping this procedure will drastically lower the amount of MPFs incorporated into the water.

Numerical simulation of aluminum-steel clad strip production using horizontal single belt casting process

A 3-D steady-state turbulent flow and solidification model was developed to simulate melt flow in a Horizontal Single Belt Caster for the production of an Al-Steel composite strip. The steel substrate is attached to the moving belt and moves at the same speed as the belt while the aluminum melt is introduced onto the substrate via an extended nozzle melt delivery system. A finite volume method was used to numerically solve the governing equations. In order to model the turbulent flow, a low Reynolds k − ε turbulent model was adopted. The developed numerical model was further employed to investigate the effect of such parameters as clad thickness, casting speed, molten aluminum superheat, and heat extraction rate from the belt surface on fluid flow and temperature fields in the system. It was found that for a certain clad thickness, casting speed and cooling rate should be adjusted properly and outlet strip temperature is independent of Inlet melt superheat.

Double-side super-hydrophilic/superspreading fabric for ultrafast asymmetric sweat transport and in-situ power generation

Asymmetric (viz. Janus or one-way transport) fabrics that can promote directional sweat transport from the next-to-the-skin surface to the outer surface by the hydrophobic-hydrophilic difference across the fabric thickness have been developed. However, the hydrophobic next-to-the-skin surface inevitably increases the inherent resistance to sweat transportation into the fabric, fundamentally hampering its moisture management property. In this work, by selectively coating a poly-pyrrole (ppy) film with Turing patterns on one side of the fabric to achieve superspreading property, we demonstrated an all-hydrophilic asymmetric fabric with outstanding one-way liquid sweat transport property. Benefiting from the low resistance of sweat absorption, the all-hydrophilic fabric exhibited a dramatically increased directional sweat transport rate of 13.6 mm/s, which is 5.9 times that of the untreated fabric, and significantly enhanced sweat evaporation rate (1.56 times of the untreated fabric) and cooling performance. Furthermore, the conductive ppy-fabric, during the process of ultra-fast sweat transport, generated a potential of 150 mV over an area of 2×2 cm2 or scalable electrical energy output of 2.5 mW/m2 under continuous sweat transportation. The finding in this work not only provided new insight into the design and development of asymmetric fabric for ultrafast sweat transport but also proposed a novel method for the in-situ energy harvesting during the sweat transportation process, which has potential applications in self-powered smart wearables and functional clothing.

Pengungkapan Kinerja Lingkungan Instansi Pemerintah Daerah Melalui Laporan Keberlanjutan Berbasis Global Reporting Initiative

Laundry washing is a crucial process in daily life. Although automatic washing machines have simplified the washing process, utilizing advanced technology like fuzzy logic control can enhance the performance of smart washing machines to achieve optimal washing results. This research aims to implement fuzzy logic control using the Mamdani method on smart washing machines to improve efficiency and washing quality. The research methodology consists of several stages. Firstly, analyzing variables that affect the washing process, such as laundry load, fabric thickness, dirt level, and water temperature. Next, designing a Mamdani fuzzy logic control system by determining membership functions for each variable and creating fuzzy rules to link input and output variables. Lastly, evaluating washing results based on predefined input variables. The research findings demonstrate that implementing Mamdani fuzzy logic control on smart washing machines can significantly enhance washing quality and adaptively determine washing parameters to achieve cleaner washing outcomes. Therefore, integrating Mamdani fuzzy logic control into smart washing machines has the potential to improve overall washing performance. In conclusion, utilizing Mamdani fuzzy logic control on smart washing machines is an effective step towards enhancing efficiency and effectiveness in laundry washing. This research contributes to the development of more adaptive and environmentally-friendly smart washing machine technology and plays a crucial role in advancing fuzzy logic control technology for other smart household applications.

Evaluating the Effects of Breaking Vacuum During the Fabrication of Amorphous Selenium Detectors.

Direct conversion X-ray detectors offer high spatial resolution and improved sensitivity over indirect conversion detectors. As interest increases in their applications, including utilization as the top layer in dual-layer detectors for polyenergetic X-ray detection, additional studies on fabrication techniques are required. Amorphous selenium is a well-studied high-Z semiconductor capable of high-resolution and high-sensitivity imaging in direct architectures. It is already commercially available for mammography, and much work has gone into developing it for higher-energy applications (>20 keV.) To fully attenuate energies required for the low energy (<35 keV) top layer in dual-layer detectors, a-Se thicknesses greater than 200 μm must be fabricated. However, evaporation crucibles have limited capacity and require reloading of crucible material to achieve higher thicknesses, which is performed by opening the chamber and breaking vacuum mid-fabrication. We investigate the effects of splitting the fabrication into two depositions - exposing the sample to air in between - on device performance. We find that there is no significant effect on the transport properties, and a small range of performance parameters can be found - suggesting small fluctuations between devices of ± 5%, independent of fabrication technique and thickness. This implies that as we increase our thicknesses to those required for the low-energy layer of the dual-layer detector, we can expect performance to be maintained.

Sound absorption and thermal insulation materials from waste palm oil for housing application: Green polyurethane/water hyacinth fiber sheet composite

This research presents an eco-friendly method for producing polyurethane foam (PUF) and water hyacinth fiber (WHF) sheets. The objectives were to engineer wall materials with sound-absorption and thermal insulation capabilities while also improving the mechanical properties of pure PUF. Waste palm oil (WPO) was successfully utilized as a polyol substrate, playing a substantially role in PUF generation, acting as a PU binder, and serving as a PU adhesive. The productions of PUF (NCO index of 100) combined with WHF sheets (WHF/PU binder ratio of 60/40) using four distinct fabrication methods (sheet-foam-sheet (SFS), foam-sheet-foam (FSF), foam-foam-foam (FFF), and sheet-sheet-sheet (SSS)) were investigated with a fabrication thickness of 150 mm. The findings indicate that the SFS configuration demonstrates remarkable sound absorption properties, with an average sound absorption (SAA) of 0.59, noise reduction coefficient (NRC) of 0.39, and the highest sound absorption coefficient (SAC) of 0.93 at 1900 Hz, alongside a thermal conductivity of 0.0301 W/mK. Importantly, all four methodologies produce SAC values greater than 0.4, outperforming commercial counterparts while demonstrating low thermal conductivity indicative of effective thermal insulation. The result noted that WHF sheet exhibited self-extinguishing properties, making them suitable for use in construction materials. As a result, SFS emerges as the best method for constructing superior sound absorption and thermal insulation materials. This study emphasizes the potential of waste derived WPO and WHF as advantageous eco-friendly substrates for industrial wall and housing materials.

Optimization of garment sewing operation standard minute value prediction using an IPSO-BP neural network

Abstract Standard minute value serves as a pivotal metric guiding the arrangement and balancing of production cycles in clothing production lines, and plays a crucial role in cost pricing and production order arrangement for clothing products. Given the complexity of the garment sewing process, ten influencing factors including fabric weight, fabric thickness, fabric density, stitching length, stitching shapes, cut pieces numbers, notch numbers, sewing technologies, sewing machine, and auxiliary accessories were identified. Upon this foundation, a standard sewing time prediction model, Improved particle swarm optimization - Back-propagation neural network (IPSO-BP), was proposed, focusing on non-quantitative factors. The IPSO-BP model was trained using actual sewing data from a women’s clothing production company. Compared to the unoptimized BP neural network, the IPSO-BP model demonstrated significant advantages in terms of convergence speed and prediction accuracy. Therefore, the IPSO-BP model proposed in this study holds promise for predicting standard sewing hours effectively.