Multi-Scales Behaviour of Materials

236 Pages·2012·31.581 MB·English

by  Edited by Moussa Karama

Multi-Scales Behaviour
of Materials
Edited by
Moussa Karama
Multi-Scales Behaviour
of Materials
Special topic volume with invited peer reviewed papers only.
Edited by
Moussa Karama
Copyright  2012 Trans Tech Publications Ltd, Switzerland

All rights reserved. No part of the contents of this publication may be reproduced or
transmitted in any form or by any means without the written permission of the
publisher.

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Volume 146 of
Applied Mechanics and Materials
ISSN 1662-7490
Full text available online at http://www.scientific.net

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PREFACE

ICSAAM 2011 focuses on the development of methods to predict the behaviour of materials, in order to
design materials with specific properties. This requires a multiscales materials modeling framework that
is based on the fundamental laws of nature and links the electronic modeling hierarchy through the
atomistic and mesoscale modeling regimes to macroscopic material behaviour. It is evident that such a
framework may not be based on rigid, formal parameterizations alone but must emerge from a detailed
understanding of the mechanistic behaviour of materials, a robust knowledge of materials properties
and metallurgical trends, and must take into account the processing of materials as the basis of
dynamical structure property relations. Through bundling expertise on modeling and simulation of
materials across all length and time scales at “ICSAAM 2011” and the advanced study researchers with
is a position that will allow it to fast-track the development of advanced multi-scale modeling methods.

ICSAAM 2011 focused on three areas to achieve its objectives:

─ Research: Modeling of materials across the length scales is an interdisciplinary task as different
disciplines tend to focus on certain aspects and length scales of materials. The expertise and
experience available at ICSAAM and in the advanced study researchers will help us to tackle
complex materials modeling problems and to establish ICSAAM as a meeting for multi-scale
materials modeling.
─ Application: Input and feedback from industry and experiment is vital for the development of
successful multi-scale materials modeling frameworks. Only a problem-driven approach will be
able to contribute to technological development and deliver a multi-scale modeling frame-work
that will help guide the design of new materials.
─ Education: A long-term impact of materials modeling can be sustained only by educating
students that will then apply their knowledge and skills in industry and academia. ICSAAM will
setup a course with focus on multi-scale modeling and also contributes special lectures to the
curricula of mechanical engineering and physics.

Prof. Moussa KARAMA
Guest editor
Table of Contents
Preface
Micro-Scale Modeling of Carbon-Fiber Reinforced Thermoplastic Materials
F. Abbassi, A. Gherissi, A. Zghal, S. Mistou and J. Alexis 1
Cellulose Whiskers Micro-Fibers Effect in the Mechanical Proprieties of PP and PLA
Composites Fibers Obtained by Spinning Process
A. Gherissi, R.B. Cheikh, E. Dévaux and F. Abbassi 12
Behavior of Reinforced Concrete Beams by Confined Oblique Rods
F. Taouche, K. Ait Tahar and N. Hannachi 27
Behavior of the Composite Lightweight Concrete
S. Bouaziz and K. Ait Tahar 39
Effects of Ageing in Marine Environment on Glass Fibre/Unsaturated Polyester Composite
K. Laoubi, N. Belloul, A.A. Benyahia, A. Sérier and N. Ouali 51
Study of Mechanical Behavior of Concrete in Direct Tensile Fiber Chips
Y. Bouafia, M.S. Kachi, D. Atlaoui and S. Djebali 64
Effect of Artificial Defect and Mean Shear Stress on Torsional Fatigue Behaviour
A. Nasr, Y. Nadot, C. Bouraoui and R. Fathallah 74
Optimizing Residual Stress Profile Induced by Laser Shock Peening Using DOE Technique
M. Frija, R.B. Sghaier, C. Bouraoui and R. Fathallah 83
Toward Optimal Updating Time Inspection Based on Reliability Approach of Fatigue
Crack Propagation
M. Eltaief, T. Hassine, C. Bouraoui, H. Riahi, A. Chateauneuf and P. Bressolette 96
Impact and Sliding Wear Resistance of Hadfield and Rail Steel
R. Harzallah, A. Mouftiez, S. Hariri, E. Felder and J.P. Maujean 112
Predicting the Reliability of Aligned Carbon Nanotube Bundles in Mechanical Structures
K. El-Hami and A. El-Hami 124
Safety and Reliability of Carbon Nanotubes in Nanoactuator Application
K. El-Hami and A. El-Hami 130
Correlating Piezoelectric Polymer/Carbon Nanotubes Nanocomposite Strain Sensor with
Reliability and Optimization Tools
K. El-Hami and A. El-Hami 137
Performance and Analysis of Concrete in Sewer Environment: Anisotropy of Damage
M. Oualit, R. Jauberthie, Y. Melinge and T. Abadlia 147
Epoxy-Layered Silicate and Epoxy MWCNTs Nanocomposites
A. Stan, I. Dinca, C. Ban, S. Ilina, D. Donescu, H. Paven, L. Dumitrache, L. Gavrila and I. Voicu 160
Design and Finite Element Modal Analysis of 48m Composite Wind Turbine Blade
M. Tarfaoui, H. Khadimallah, A. Imad and J.Y. Pradillon 170
Residual Stresses in a Ceramic-Metal Composite
V. Cazajus, S. Seguy, H. Welemane and M. Karama 185
Impact Depth on Glass Surface Caused by Sand Particles
S. Bouzid and Z. Azari 197
Effect of Hydrogen on Mechanical Properties of Pipeline API 5L X70 Steel
T. Bellahcene, J. Capelle, M. Aberkane and Z. Azari 213
© (2012) Trans Tech Publications, Switzerland
doi:10.4028/www.scientific.net/AMM.146.1
Micro-scale modeling of carbon-fiber reinforced thermoplastic materials
F. ABBASSI1,a, A. GHERISSI1,b, A. ZGHAL1,c S. MISTOU2,d
and J. ALEXIS2,e
1 URMSSDT- ESST Tunis, 5 Avenue Taha Hussein, BP, 56, Bâb Manara, 1008 Tunisia
2Université de Toulouse ; INP/ENIT ; M2SP-LGP, 47 Avenue d’Azereix; 65016 Tarbes, France
a [email protected], b [email protected] ,[email protected],
[email protected] , [email protected]

Keywords: Composite carbon fiber, Micro-scale modeling, Homogenization and Mechanical
property
Abstract Thin-walled textile-reinforced composite parts possess excellent properties, including
lightweight, high specific strength, internal torque and moment resistance which offer opportunities
for applications in mass transit and ground transportation. In particular, the composite material is
widely used in aerospace and aircraft structure. In order to estimate accurately the parameters of the
constitutive law of woven fabric composite, it is recommended to canvass multi-scale modeling
approaches: meso, micro and macro. In the present investigation, based on the experimental results
established by carrying out observations by Scanning electron microscope (SEM), we developed a
micro-scale FEM model of carbon-fiber reinforced thermoplastic using a commercial software
ABAQUS. From the SEM cartography, one identified two types of representative volume
elementary (RVE): periodic and random distribution of micro-fibers in the yarn. Referring to
homogenization method and by applying the limits conditions to the RVE, we have extracted the
coefficients of the rigidity matrix of the studied composites. In the last part of this work, we
compare the results obtained by random and periodic RVE model of carbon/PPS and we compute
the relative error assuming that random model gives the right value.

Introduction
The determination of the mechanical performance of woven fabric composites materials is based on
the study of the behavior of the texture and the composite under different solicitations. Currently,
the multi scale modeling of composites (figure 1) is one of the most used methods and it was
adapted by several researchers. In fact, using this approach, F. Costanzo and L. Gray [1] haves
implanted a survey on periodicity and boundary conditions; P.Boisse [2] has raised the constructive
equations of the mechanical behavior of the composites woven during the forming; Gilles Hivet [3]
has elaborated a mathematical approach to identify the trajectory and the different sections of the
yarn in texture, the profiles of the contacts’ curves and the contact’s sections according to the conic
equations; L. Orgéas [4] has studied in meso-scale, the permeability of the reinforcements woven of
stratified composites by surveying the velocity in such composites; J. Wang [5] has studied the
predictive mechanical behavior modeling in woven composite structure, by analyzing 3D finites
elements ; P. Badel and P. Boisse [6,7] have determined fibers orientations, in reinforcements
woven during and after composites’ formation.
2 Multi-Scales Behaviour of Materials

Fig. 1: Multi-scale modeling techniques in woven fabric composites

In order to identify the behavior of the studied composite using multi-scale approach, we have
developed in this paper a simulation of the reinforcement’s woven fabric composite (figure 1).
We have started by using an experimental characterization of the texture to prepare a geometrical
description of fibers’ diameters and distributions in the Polyphenylene sulfide (PPS) matrix. Then,
we identified two types of RVE (periodic and random one) in order to estimate the errors’ values in
the results. Then, basing on the homogenization method and after applying the boundary conditions
to the RVE, one has extracted the coefficients of the rigidity matrix and the parameters of the yarn
composites. Finely, we have identified the able RVE to characterize accurately the yarn of our
woven fabric composite.

I. Carbon-fiber reinforced thermoplastic materials
The composite texture consists of a carbon fibers and a PPS matrix and the volumetric fraction of
the fibers in the composites is .The characteristics of the materials forming the composite
(cid:1) = 0.5
(cid:2)
are summarized in the following table:
Table 1: The characteristic of the materials forming the composite

Material Filament Volumetric YOUNG Shear Poisson’s Constrained Maximum Thermal
diameter Mass ρ module Module ratio of rupture Elongation dilation
(µm) (kg.m-3) E(Mpa) G (Mpa) υ (traction) (%) ratio °C-1
MPa
Carbon 6.24 1800 390 000 20 000 0.35 2500 0.6 0.08 10-5
Fiber
PPS 1300 4000 _____ 65 100 5 10-5
Moussa Karama 3
The characterization of the texture of the composite has been carried out throw two main steps. In
the first one, we determine the texture’s character, the trajectory, and the sections of the yarns
(Texture of the composite: satin 5x1 in three layers). Then, in a second step, we find out the
micrographic arrangement of the fibers in a yarn (figure 3).

(a) (b)
Fig. 2: (a) micrographic of three ply fabric specimens (meso-scale), (b) size and
arrangement of the micro fibers in the yarn

The yarn is composed by thousands of small fibers whose diameter in the order of 6.24 µms (figure
2). This value is established by calculating the average of 150 fibers’ diameter. The disorganized
arrangement of the fibers in the yarn presented in figure3 will produce a variation in the local
properties influenced by the distance between these fibers. Then it is necessary to start by
characterizing the fibers’ arrangement in order to determine the minimal size of the representative
volume elementary (RVE) of the yarn. To do so, we can characterize the distribution of the fibers
by analyzing the yarn’s picture and using the covariance concept adapted already by [8]:
(2)
(cid:7)(cid:8)(cid:9),(cid:9)+ℎ(cid:13) = (cid:14)(cid:15)(cid:9) ∈ (cid:17),(cid:9)+ℎ ∈ (cid:17)(cid:18)
The covariance is defined as the probability of adherence of two points” x “and “x+h” in the same
phase d, and it can be valued by carrying out the Fourier’s transformation of the figure 2.
According to the works of P.Badel and al [7] the periodicity of the microstructure is presented by
the periodicity of the covariance.
II. The micro scale modeling
1. The geometric model of RVE
The choice of the RVE, which is a cubic shape, was based on several researches works [10, 11, 12
and 13]. This RVE should have the smallest size which makes it representative of the yarn material.
We opted for this step of the simulation for two cubic cells shapes and we considered the fiber has a
cylindrical form. The first cell (figure 5-a) is periodic and the second is random (figure 5-b). The
volumetric fraction of the reinforcement is calculated by the report between the volume of the fibers
and the total volume of the basic cell:
(cid:19)(cid:20)(cid:21)(cid:22)(cid:23)(cid:24)(cid:25) !" (3)
(cid:1) = = (cid:31)
(cid:2) (cid:19)(cid:26)(cid:27)(cid:28)(cid:29)(cid:30) #$"
Where: d is the diameter of the fiber, a is the side of the basis cell, and n: is the number of fibers by
cell
4 Multi-Scales Behaviour of Materials
Choosing the size of representative volume elementary must satisfy the following criteria:
1) It must be small enough to take into account the microscopic structure of material, and
sufficiently large to describe the overall behavior of material.
2) The properties must be independent of the location of the material where it was taken.
We have chosen to make statistical case to identify the yarn random representative volume
elementary. One varies the window size. We identify in each window, the minimum and maximum
fibers volume fraction by scanning the window in the photograph of the structure see Figure 3 and
4.

Fig. 3: Evolution of bounds for local volume fraction with window size

Fig. 4: Variations in local volume fraction of fibres
Two types of representative volume elementary (RVE): periodic and random distribution of micro-
fibers in the yarn has identifying (figure 5):