Results 41 to 50 of about 5,651,169 (235)
Prediction of Cotton Yarn’s Characteristics by Image Processing and ANN
Alexandria Engineering Journal, 2022 Machine learning and computer vision were employed in quality assessment in the textile field for more objectivity and less expense. The estimation of yarn various parameters is of great importance for the producers and customers in order to achieve ...
Manal R. Abd-Elhamied +4 more
doaj +1 more source
Advanced Engineering Materials, EarlyView.A numerical–experimental framework is developed for characterizing multi‐matrix fiber‐reinforced polymers (MM‐FRPs) combining epoxy and polyurethane matrices. Harmonic bending tests are integrated with finite element model updating (FEMU) to simultaneously identify elastic and viscoelastic material parameters.
Rodrigo M. Dartora +4 more
wiley +1 more source
Advanced Engineering Materials, EarlyView.A simplified thermoplastic pultrusion model is developed to predict thermal fields in glass fiber/polyethylene terephthalate (GF/PET) composites with reduced computational cost. By combining effective material homogenization, validation against literature data, and Gaussian‐process‐based optimization, the study reveals how heating limits, pulling speed,
Elder Soares +3 more
wiley +1 more source
Thermo-physiological Clothing Comfort of Wool-Cotton Khadi Union Fabrics
Journal of Natural Fibers, 2022 Khadi is a handspun and handloom woven textile fabric made up of natural textile fibers, predominantly cotton and wool. Khadi mainly intended for apparel purposes. Hence, the thermo-physiological properties of wool-cotton blended khadi fabric are crucial
H C Meena +3 more
doaj +1 more source
Advanced Engineering Materials, EarlyView.Building machine‐readable vocabularies for materials science is slow, expert‐driven work. This study benchmarks 13 large language models on two of its first steps: finding candidate terms in engineering articles and deciding where they belong in a class hierarchy.
Thomas Bjarsch +3 more
wiley +1 more source
Mechanical Properties Of Traditional And Nanofibre Textiles
AUTEX Research Journal, 2015 This study deals with a comparison of mechanical properties of a conventional yarn and a textile from nanofibres. The conventional yarn represents the textile objects with high degree of orientation of fibres and the textile from nanofibres represents ...
Ursíny Petr +5 more
doaj +1 more source
TRAVELLER CLEARER GAUGE CONSEQUENCE ON YARN QUALITY [PDF]
, 2022 Traveller clearer is an important part of the ring frame machine because, without it, fiber flying in the traveller cannot be cleaned. As a result, fiber congests travellers which may lead to a rise in end breakage rate as well as declination of quality ...
CHOWDHURY, MAHMUD FARHAD +3 more
core +1 more source
A Lightweight Procedural Layer for Hybrid Experimental–Computational Workflows in Materials Science
Advanced Engineering Materials, EarlyView.We unveil a prototype hybrid‐workflow framework that fuses automatedcomputation with hands‐on experiments. Built atop pyiron, a lightweight, parameterized layer translates procedure descriptions into executable manual steps, syncing instrument settings, human interventions, and data capture in real‐time today.
Steffen Brinckmann +8 more
wiley +1 more source
Effect of Filament Fineness on Composite Yarn Residual Torque
AUTEX Research Journal, 2018 Yarn residual torque or twist liveliness occurs when the twist is imparted to spin the fibers during yarn formation. It causes yarn snarling, which is an undesirable property and can lead the problems for further processes such as weaving and knitting ...
Sarıoğlu Esin +2 more
doaj +1 more source
Journal of Natural Fibers, 2021 This study discussed the influence of fiber length distribution on yarn qualities (yarn irregularity and strength) based on simulation on fiber random arrangement.
Zhan Jiang +4 more
doaj +1 more source