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There are situations where geotextiles are subjected to uniaxial tensile strain, which may result in noticeable variations in their filtration performance. This study accordingly investigated the behaviors of needle-punched nonwoven geotextiles during tensile testing using in-situ X-ray computed tomography. Furthermore, a numerical analysis of the variation in pore size characteristics was performed by establishing a geotextile model based on the web formation and bonding manufacturing process. The pore size and fiber orientation distributions were subsequently investigated and a model for the changes in the pore characteristics was established and validated. With increasing tension strain in the machine direction, the pore throat size distribution curve exhibited an overall shift towards larger sizes, and the characteristic pore sizes ranging from 10% to 98% either initially decreased, then increased or consistently increased. Furthermore, the fiber distribution was predominantly within the geotextile plane along the machine direction, and as the strain increased, the fibers stretched and aligned along the direction of the tensile load along the machine direction. Finally, the experimental findings of this study and relevant test results from the literature were thoroughly interpreted. The numerical model align well with the actual changes in pore size characteristics observed under tensile strain. • The tensile behaviors of nonwoven geotextiles during testing were revealed in situ with X-ray computed tomography. • The numerical simulation analysis of the pore size characteristics variation was realized by establishing a geotextile mode. • A model for the changes in pore characteristics of the geotextile under tensile strain was established. • The simulation method can well predict the variation in pore size characteristics under uniaxial tensile strain. [ABSTRACT FROM AUTHOR]

Two digital image methods based on scanning electron microscope (SEM) and computed tomography (CT) were proposed to study the microstructural characteristics of staple fibers and continuous filament geotextiles. Two-dimensional (2D) image analysis was developed for SEM images using a machine-learning-based segmentation algorithm. Three-dimensional (3D) image analysis of the CT images was based on 3D reconstruction and a pore network model. The fiber orientation distribution, porosity, pore size distribution (PSD), and characteristic pore size O 95 determined from image analysis were compared with the theoretical equation and bubble point test (BBP) results. It is shown that 2D and 3D image analyses can accurately measure the fiber orientation distribution of the geotextiles. The porosity values obtained using 3D imaging were comparable to theoretical values. The PSD curves obtained in the BBP tests were in good agreement with those obtained using the 3D image method. O 95 sizes of continuous filament geotextiles estimated by 2D image analysis compared well with O 95 sizes obtained by BBP tests, whereas this was not the case for staple fiber geotextiles. The O 95 pore throat sizes of the two nonwoven geotextiles determined by 3D image analysis were comparable to the BBP test-based values and 2D image analysis-based values. • The applicability and results of 2D and 3D image methods for measuring the microstructure characteristics of nonwoven geotextiles were discussed. • A machine learning-based 2D image method without complex sample preparation and parameter tuning was proposed. • 2D image analysis have accurate results of O 95 sizes for continuous filament nonwoven geotextiles. • 3D image analysis is a good approach for determining the pore characteristic of nonwoven geotextiles. [ABSTRACT FROM AUTHOR]