LEE- Yenilikçi Teknik Tekstiller Lisansüstü Programı

Bu topluluk için Kalıcı Uri

http://hdl.handle.net/11527/19497

Gözat

Yazar "Mula, Murat" ile LEE- Yenilikçi Teknik Tekstiller Lisansüstü Programı'a göz atma
  • Öge
    Simulation-based analysis of porosity in needle punched nonwoven structures
    (ITU Graduate School, 2025) Mula, Murat ; Gürarslan, Alper ; 503231857 ; Innovative Technical Textiles
    Nonwoven fabrics, produced without traditional weaving or knitting, offer advantages such as low production cost, fast processing, and high design flexibility. Among them, needle-punched nonwovens are notable for their mechanical bonding achieved without chemical binders, making them suitable for a wide range of technical applications. This thesis focuses on developing a simulation-based model to analyze the porosity of needle-punched nonwoven structures at the microstructural level. A Python-based algorithm was integrated with the TexGen software to simulate random fiber orientations, segmentations, and distributions, enabling virtual reconstruction of the nonwoven fabric. The literature review covers the evolution of nonwovens, web formation techniques bonding methods. It also discusses modeling strategies including statistical regression, artificial neural networks (ANN), and image-based simulations. These approaches are compared in terms of their ability to predict structural and performance parameters. Experimentally, needle-punched polyester nonwoven samples were prepared and tested for thickness, tensile strength, bursting strength, abrasion resistance, water contact angle, air permeability, and porosity. SEM imaging combined with ImageJ analysis was used to quantify fiber fraction and pore structures. Results showed high mechanical strength, strong hydrophobicity, and good air permeability. The modeled porosity (38%) closely matched experimental values (36%), with only a 2.3% deviation. In conclusion, the developed model effectively predicts porosity by incorporating parameters like fiber diameter, thickness, and alignment. The findings validate the model's accuracy and highlight its potential for use in designing high-performance nonwoven materials in various technical sectors. This work offers a digital tool that can reduce physical trial-and-error processes and accelerate product development in the nonwovens industry.