Savvas Vassiliadis

Prediction of the air permeability of woven fabrics using neural networks

Purpose – The target of the current work is the creation of a model for the prediction of the air permeability of the woven fabrics and the water content of the fabrics after the vacuum drying.Design/methodology/approach – There have been produced 30 different woven fabrics under certain weft and warp densities. The values of the air permeability and water content after the vacuum drying have been measured using standard laboratory techniques. The structural parameters of the fabrics and the measured values have been correlated using techniques like multiple linear regression and Artificial Neural Networks (ANN). The ANN and especially the generalized regression ANN permit the prediction of the air permeability of the fabrics and consequently of the water content after vacuum drying. The performance of the related models has been evaluated by comparing the predicted values with the respective experimental ones.Findings – The predicted values from the nonlinear models approach satisfactorily the experiment...

Structural characterization of textile fabrics using surface roughness data

The surface of the textile fabrics is not absolutely flat and smooth. Its geometrical roughness within certain extents is considerable. The surface roughness influences the fabric hand and it plays a significant role in the end use of the fabric. In parallel, the periodic variations of the fabric surface level due to the regular interlaced patterns of the yarns cause a respective variation of the geometrical roughness measurement. Thus, the fabric roughness data measured using the Kawabata Evaluation System for Fabrics and imposed to a certain process of numerical calculations result into the retrieval of the structural parameters of the fabric. The principle of the method has a non‐destructive character and can be applied to woven or knitted fabrics.

Sedimentation behaviour in electrorheological fluids based on suspensions of zeolite particles in silicone oil.

Sedimentation is a known and expected shortcoming of electrorheological fluids (ERFs) due to the inherent difference in the constituent densities. The long-term sedimentation causes loss of the electrorheological phenomenon and the exploitable electromechanical and viscoelastic properties despite the presence of the stimulating electric field. In this work, we report the effect of temperature and surfactant concentration on the stability of ERFs prepared from zeolite particles and silicone oil with primary focus on the sedimentation of the particles in the ERF. As the temperature stability of the ERFs is fundamentally important, we have studied three different ERF suspensions composed of different zeolite particles, in silicone oil. These ERFs have been comparatively evaluated for their sedimentation over time, across a wide range of temperatures (-40°C to +60°C). The influence of surfactant concentration on the colloidal stability of the ERFs has also been investigated. A novel method of acoustic stirring (kHz range) on the homogenisation of the ERFs has been proposed and its effect on the sedimentation process evaluated. These results are useful for assessment of alternative suspension methods for specific applications.

Artificial Neural Networks and Their Applications in the Engineering of Fabrics

Historically the main use of the textile fabrics has been limited mainly to clothing and domestic applications. The technical uses were of minor importance. However in the last decades the use of the textile structures has started to spread over other sectors like construction, medicine, vehicles, aeronautics, etc. The increased interest in technical applications have improved the fabric design and engineeringprocedures, given that the final products must be characterized by certain mechanical, electrical etc. properties. The performance of the fabrics should be predictable right from the design phase. The design of a fabric is focusing on the materials selection as well as on the definition of its structural parameters, so that the requirements of the end use be fulfilled. These changes in the application field of the textile structures caused a move from the esthetic design to the total technical design, where the fabric appearance and the particular properties affecting its final performance are taken in account. However, the textile structures are highly complex. A textile fabric consists of yarns; yarns in turn consist of fibres. Thus the mechanical performance of the fabrics is characterized by the structural geometrical complexity and non-linearity, as well as from the non-linearities of the materials themselves. This double non-linear bahaviour of the textile fabrics increases the difficulty in the fabric design and engineering processes. The complex structure and the difficulties introduced by the raw materials do not allow the use of precise analytical models for the technical design of the fabrics. Fabric engineering activities are increasingly based on computational models that aim at the prediction of the properties and the performance of the fabrics under consideration. Various computational tools have been used in order to represent the fabrics in a computational environment and to predict their final properties. Among others, Finite Element Method (FEM) analysis has supported mainly the prediction of the behaviour of the complex textile structures under mechanical loads. In the case of classification problems Artificial Neural Networks (ANNs) have proved a very efficient tool for the fast and precise solution. ANNs have found an increasing application in the textile field in the classification as well as in the

Finite Element Modelling of the Warp Knitted Structure

The finite element modelling of the Charmeuse warp knitted fabrics is the main subject of this paper. The proposed model consists of a three-dimensional representation of the warp knitted fabric microstructure and a mechanical analysis of the defined unit cell. An iterative calculation procedure was used for the definition of the geometrical representation of the structure. The parametric modelling is based on the main structural parameters: yarn crosssection, warp density, course density, and yarn consumption of the front and the back bar. The flattening of the yarn cross-section has been introduced in the undeformed state of the model for the realistic approach of the authentic situation. The Finite Element Method (FEM) with contact analysis was implemented for a mechanical analysis of the multi-body structural unit. The appropriate contact algorithm was defined for fast convergence during the solution. Although the complexity of the unit cell was high, the modelling was possible and it can become a tool for the mechanical analysis of warp knitted fabrics.

Mechanical simulation of the plain weft knitted fabrics

Purpose – The present work aims to focus on the simulation of tensile, shear and bending deformation of the plain‐weft knitted fabrics in an analogous manner to the tests performed on the Kawabata Evaluation System for Fabrics.Design/methodology/approach – The simulation of the tests is based on the modelling of the fabric microstructure and the application of the boundary conditions and the equivalent loading that correspond to each mechanical test, with a respect to the contact phenomena. A three‐dimensional model consisting of three bodies in contact represents the unit cell of the fabric microstructure. Finite element analysis is used for the prediction of fabric performance since the complexity of the structure, the anisotropic properties of the yarns and the interaction phenomena between the yarns at the contact areas preclude the use of analytical methods.Findings – The proper definition of the boundary conditions and the appropriate load is of great significance for the realistic simulation of the...

On the performance of the geometrical models of fabrics for use in computational mechanical analysis

The computer aided engineering and the respective computer aided design tools compose a modern mechanical modelling environment for the textile materials. The numerical mechanical models of the textile structures are a strong tool for the in‐depth study of the mechanical properties and the behaviour of the textiles. The precision of these models in terms of their accuracy in representing the exact geometry of the real textile structures is the fundamental factor affecting the overall success of the idealisation. This paper discusses older traditional analytical models (Peirce, Saw‐tooth, Kemp) as well as some variations of these fundamental models. Their numerical solutions are successfully compared to the experimental measurements of the yarn longitudinal deformation parameters using microscopic and digital image processing techniques. The results of the analytical models are compared with the actual measurements and the more precise models are indicated.

Contact mechanics in two‐dimensional finite element modelling of fabrics

Purpose – This paper proposes a simplified two‐dimensional representation of the unit cell of the fabric that involves three bodies in contact.Design/methodology/approach – The fabrics are not simple homogenous structures. They have a discrete structural character and this is essential for their complex mechanical behaviour. Low stress micro‐mechanics is mainly used for the prediction of the fabric hand. Modelling of the fabric microstructure is a powerful tool for the in‐depth study of their performance. Based on the geometrical models of the fabrics, finite element analysis (FEA) is a very useful method for the mechanical analysis of their complex shape structures. Especially FEA can be applied on a system of bodies in contact by taking into account the interactions between the individual bodies. The parametric FEA analysis of the unit cell of the fabric provides interesting results about its mechanical behaviour.Findings – The present work states that the use of the finite element method is a friendly ...

On the Measurement of the Electrical Power Produced by Melt Spun Piezoelectric Textile Fibres

Piezoelectric, melt spun, textile fibres as multifunctional materials appeared recently, and they are under thorough investigation and testing in order to define their performance and behaviour. Although piezoelectricity was first reported in 1880 and the piezoelectric behaviour of organic polymers materials has been known since 1969, the fibrous form of the piezoelectric materials under consideration opens new technological horizons; however, it introduces novel restrictions and further complex parameters are involved in their study. The major issue of the current research work is the study of the actual capacity of the piezoelectric fibres, i.e. the electric power produced following mechanical stimulation of the individual fibre. The measurements were made possible after the development of the necessary specific equipment. The test results enabled the ranking of the various types of the piezoelectric fibres according to the respective power generation. The main difference in this research approach is the measurement of the power generated by the fibres. Measurement of the power generated by an electrical power source (in the case of energy harvesting applications which is the prime interest of this research project) is an important characteristic as the requirements of various applications are expressed in units of power. Stating the voltage produced during mechanical deformation of the fibres is not enough (cf. voltage produced due to electrostatic phenomena on textiles where the voltage is in the range is the several kV, but the power is not enough to power a light-emitting diode).

Optimization Aspects on the Hand of the Fabrics

Fabric hand is an essential property of textile fabrics. It affects the sensorial perception of humans when they touch a fabric. The feeling of hand depends on many factors; mainly on the low stress mechanical behavior of the fabric as well as on the subjective aspects of the person assessing the fabric such as sensitivity, culture, etc. The hand of the fabrics can be approached either by subjective estimations or by objective measurements. Both evaluation methods provide the necessary information for the calculation of the total hand value (THV) of the fabric. The THV is a function of multiple variables: the primary hand values. The complex expression of the THV introduces difficulties in predicting the conditions for the maximization of its final value. The present work provides a mathematical tool for a parametric study and definition of the quantities, which have to change, in order to maximize the THV of the fabric.