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Öğe Acoustical absorptive properties of spunbonded nonwovens made from islands-in-the-sea bicomponent filaments(Taylor and Francis Ltd., 2013) Suvari, Fatih; Ulcay, Yusuf; Maze, Benoit; Pourdeyhimi, BehnamIn this paper, we report on the acoustical absorptive behavior of spunbonded nonwovens that contain bicomponent islands-in-the-sea filaments. Nylon 6 (PA6) and polyethylene were used as the islands and the sea polymers, respectively. Spunbonded webs made with islands-in-the-sea bicomponent filaments with island counts of 1, 7, 19, 37, and 108 were produced at the Nonwovens Institute's pilot facilities at NC State University. The filaments were fibrillated by hydroentangling, where high-speed water jets were used to fibrillate the fiber and free' the islands. The influence of the number of islands on acoustical absorptive behavior of the spunbonded nonwovens was investigated. A comparison of acoustical absorptive properties of multi-layer islands-in-the-sea nonwoven and high loft nonwoven was also performed to evaluate the potential use of spunbonded nonwovens made from islands-in-the-sea bicomponent filaments in place of bulky fibrous sound absorbers. Results have shown that multi-layer 108 nonwoven islands were better acoustic absorbers at nearly half of the frequency range. Spunbonded nonwovens made from islands-in-the-sea bicomponent filaments can be a good alternative in applications where there is desire to replace bulky fibrous sound absorbers.Öğe Comparing the Prediction Capabilities of Artificial Neural Network (ANN) and Nonlinear Regression Models in Pet-Poy Yarn Characteristics and Optimization of Yarn Production Conditions(Inda, 2017) Yıldırım, Kenan; Öğüt, Hamdi; Ulcay, YusufIn the manufacture of yarn, predicting the effect of changing production conditions is vital to reducing defects in the end product. This study compares, for the first time, non-linear regression and artificial neural network (ANN) models in predicting 10 yarn properties shaped by the influence of winding speed, quenching air temperature and/or quenching air speed during production. A multilayer perceptron ANN model was created by training 81 patterns using the Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm. The hyperbolic tangent, or TanH, activation function and logistic activation functions were used for the hidden and output layers respectively. Results showed that the ANN approach exhibited a greater prediction capability over the non-linear regression method. ANN simultaneously predicted all of the 10 final properties of a yarn; tensile strength, tensile strain, draw force, crystallinity ratio, dye uptake based on the colour strengths (K/S), brightness, boiling shrinkage and yarn evenness, more accurately than the non-linear regression model (R-2 = 0.97 vs. R-2 = 0.92). These results lend support to the idea that the ANN analysis combined with optimization can be used successfully to prevent production defects by fine tuning the production environment.Öğe An experimental study and model development of poly(ethylene terephthalate) yarn morphology(Walter De Gruyter Gmbh, 2014) Yıldırım, Kenan; Ulcay, YusufIn this study, macromolecular arrangements in fibers were investigated and a novel approach based on model development for partially oriented (POY) polyethylene terephthalate (PET) yarn morphology was proposed. Differential scanning calorimeter (DSC) analysis, Fourier transform infrared (FT-IR) analysis, boiling water shrinkage and tensile tests were performed through the study. DSC thermogram, FT-IR spectra, stress-strain curve, the change in the boiling water shrinkage properties and data from the literature were used to develop the model for POY PET fiber morphology. In order to make a comparison, textured PET yarn morphology was also investigated. The neck formations during tensile tests, cold crystallization on the DSC thermogram, peak formation on the FT-IR spectrum of the POY PET yarn after texturizing and shrinkage test at 971 and 845 cm(-1) and shrinkage phenomenon have been explained by this model.Öğe On the design method of lightweight construction materials: Structural characteristics-tearing strength relationship(Fiber Society, 2012) Suvari, Fatih; Ulcay, YusufOn the design method of lightweight construction materials: Structural characteristics-tearing strength relationshipÖğe Preparation and properties of poly(ethylene terephthalate)/nanoclay nanocomposites fibers(Fiber Society, 2012) Hojiyev, Rustam; Altun, Şule; Ulcay, YusufPreparation and properties of poly(ethylene terephthalate)/nanoclay nanocomposites fibersÖğe Reducing noise level in vehicles by spunbonded nonwovens made from bicomponent filaments(Fiber Society, 2013) Suvari, Fatih; Ulcay, Yusuf; Maze, Benoit; Pourdeyhimi, BehnamReducing noise level in vehicles by spunbonded nonwovens made from bicomponent filamentsÖğe Sound absorptive nonwovens for indoor structures(Fiber Society, 2012) Suvari, Fatih; Ulcay, Yusuf; Pourdeyhimi, BehnamSound absorptive nonwovens for indoor structures
