Helical auxetic yarn is a structural material with negative Poisson's ratio which contains a soft yarn with a higher diameter as a core component and a stiff yarn with a lower diameter as wrap ...component that has been wrapped around the core component. In the present study, a semi-empirical model based on the improvement of a theoretical model and an artificial neural network model was developed for predicting the maximum negative Poisson's ratio of helical auxetic yarn. In order to verify the models, an experiment according to the initial helical angle of wrap component, the diameter ratio of components, and the modulus ratio of components has been designed. To measure the Poisson's ratio of helical auxetic yarn, an algorithm based on the image processing technique has been proposed. Unlike the results of previous studies, the experimental results showed that increasing the diameter ratio of components so much, will decrease the maximum negative Poisson's ratio of helical auxetic yarn due to higher bending stiffness of core component. The results of the comparison between the predicted and experimental values indicated that the artificial neural network model has a lower error than the semi-empirical model. It is expected that this work provides engineering tools to predict the auxetic behavior of helical auxetic yarn based on the required precision.
The present work aimed to investigate the effect of nanofiber enhancement on the sound absorption performance of fibrous materials through a brief review of the recent progress in the field and ...highlight the current challenges and issues for measuring and modeling the sound absorption coefficient (SAC) of such structures. Moreover, some composite samples consist of polyethylenterephthalat (PET) nonwoven fabric and polyacrylonitrile (PAN) nanofibers web were prepared to be studied as a case study. The nanofiber deposition amounts, nanofiber orientation, and nanofiber layering sequence were chosen as the main variables of samples. Various amounts of deposition were achieved through three different electrospinning (ES) time of 15, 60, and 180 min. The random and aligned orientation of the nanofiber web was obtained by using a rotating collector. The effect of the layering sequence of the nanofiber layer was studied in the form of quadruple-layered assemblies of samples. The results showed that the samples incorporated with the nanofiber layer with 60 min of ES and random orientation when it is used in the second position of the layering sequence have the best performance of sound absorption, mainly at lower critical frequency range. Furthermore, a discussion on some available empirical models and compare the results confirms that there is a need for developing a new approach for measuring and modeling the SAC and consequently designing such absorbers.
In this work, an experiment according to the full factorial method (FFM) to investigate the effect of initial helical angle of wrap component, diameter ratio of components and modulus ratio of ...components on Poisson's ratio of double core helical auxetic yarn (DC-HAY) is designed. Then, after statistically confirming the similarity of maximum NPR in both main directions to reduce the calculations, a regression model based on the FFM equation and an artificial neural network (ANN)-based model to predict the maximum NPR of DC-HAY are developed. The results of the analysis of variance indicated that all terms of the regression model are statistically significant. Also, the Student-Newman-Keuls showed that all of the considered levels for parameters are in separated groups. Furthermore, the optimum architecture for the ANN model is selected based on a goodness function constructed by the coefficient of determination and mean squared error. The results of comparison between the models revealed that the ANN model has better performance than the regression model. In addition, the sensitivity analysis of ANN models introduced that the modulus ratio of components is the most sensitive parameter affecting the output of the network.
In this work, a new structure for designing auxetic yarn and its geometrical analysis is presented. The proposed structure is referred to as a double-core helical auxetic yarn (DC-HAY). It consists ...of two core components of soft yarn with a larger diameter and one wrap component of stiff yarn with a smaller diameter. A primary geometrical model for predicting the Poisson's ratio of the structure was presented through the deformation analysis of the DC-HAY during the tensile loading. Also, the primary proposed model was modified by considering the non-linear behavior of Poisson's ratio of the core components. For the verification of the proposed models, some experiments were conducted based on the initial wrapping angle, as well as the diameter ratio and modulus ratio of components. The results showed that the proposed yarn structure exhibits an apparent auxetic outcome. Moreover, the modified model is capable of predicting the maximum negative Poisson's ratio of the DC-HAY with a desirable error. Furthermore, it was found that the higher modulus ratio of components, higher diameter ratio of components and the lower initial wrapping angle will result in a higher maximum NPR, which were −8.23, −8.16 through the main lateral directions of samples.
Electrospinning is an easy and efficient method for preparing nanofibers on laboratory and industrial scales. In recent years, various studies have been done with special attentions to specific ...structures, increasing the application and eliminating the shortcomings of previous methods. Janus structure is one of the new and widely used structures that due to the limitations and challenges in achieving this structure, such as nozzle design, phase separation of two polymer solutions during electrospinning, flow rate control, optimal voltage and other parameters, the published reports in this field, are limited. Side-by-side electrospinning is one of the common ways to achieve this special structure. In this method, with appropriate nozzle design, two polymer solutions can be electrospun simultaneously. In addition, the nozzle design and the related parameters such as needle diameter, angle, and distance between the nozzles are of special importance. Also, parameters related to the rheological behavior of the polymer, especially viscosity, are crucial in achieving this particular structure. In this paper, the methods of preparation of Janus nanofibers by side-by-side electrospinning method, new structures based on these nanofibers, including the study of structure and production methods through side-by-side electrospinning, are briefly reviewed.
The mechanical behavior of fabrics with different configurations has been investigated in many works by various approaches including the force equilibrium or energy methods. However, representing a ...suitable geometrical model for fabric structure is prerequisite to apply these approaches.
This paper introduces an analytic 3D meso-scale geometrical modelling of regular twill weaves, in terms of a few structural parameters in 2D biaxial orthogonal woven fabrics. The model is proposed for the fabrics in their fully relaxed state considering their inherent skewness. For this purpose, a three dimensional structure is used to show this phenomenon. In this model, the yarns cross-section is assumed to be circular and the yarns path is assumed to be straight line (saw-tooth) in the unit cell which leads to the results that are in reasonable agreement with experimental data. These assumptions will be helpful in finding a close form solution for the mechanical behavior of woven structures.
The proposed model has been verified by comparing its output with some experimental data for its areal mass and thickness in 2/2 twill fabric as a case study. By applying this model, the geometrical structural parameters such as skewness and weave angles as well as their total consumed yarns can be predicted theoretically. This model is a framework which will be used for estimating the initial deformation behavior of regular twill woven structures under uniaxial tensile loads in our forthcoming works.
