Jayantha Ananda Epaarachchi

A Simplified Empirical Model for Prediction of Mechanical Properties of Random Short Fiber/Vinylester Composites

This article discusses a simplified approach to analyze mechanical properties of randomly distributed short fiber composites. Mechanical properties of three different randomly oriented short fiber composites, cotton, nylon, and aluminium with vinylester resins, were experimentally investigated. The analytical results were compared with experimental results and a very good correlation was found. Further, the experimental results and the predictions showed that the strength of the composites is less than the strength of the matrix material, for all three composites tested.

The Response of Embedded NIR (830 nm) Fiber Bragg Grating Sensors in Glass Fiber Composites under Fatigue Loading

The fabrication and use of fiber Bragg grating (FBG) sensors, which operates in near infrared region (Bragg wavelength λB = 830 nm) to monitor the damage accumulation in composite is reported. The spectra ∼830 nm of the embedded FBG sensor in 0°/90° woven cloth/vinyl ester composite were distorted and broadened due to fatigue loading, as expected. These distortions in FBG spectra indicate asymmetric and nonuniform strain distributions along the grating length of the FBG sensors due to the accumulation of damage during fatigue loading regimes. This information is useful for formulating a fundamental relationship between FBG spectral changes and the damage accumulation of composite structures. The results demonstrate that the sensitivity and durability of the embedded FBG sensors fabricated by conventional writing techniques at 830 nm range and monitored using inexpensive Si-based source and arrays were excellent for health monitoring of composite structures.

Use of FBG Sensors for SHM in Aerospace Structures

This paper discusses the use of Fibre Bragg grating sensors (FBG) in structural health monitoring (SHM) of Fibre reinforced polymer (FRP) aerospace structures. The diminutive sensor provided the capability of embedding inside FRP structures in order to monitor vital potential locations for damage. Some practical problems associate with manufacturing process of FRP with embedded FBG sensors, interrelation of distortion to FBG spectra with damage, and interpretation of FBG spectral responses for identifying the damage will be discussed.

Quantitative and qualitative analyses of mechanical behavior and dimensional stability of styrene-based shape memory composites

The effect of glass fiber reinforcement on the mechanical properties and geometrical shape stability during the thermomechanical cycle of the shape memory polymer composite has been investigated. A substantial improvement in the mechanical properties due to glass fiber reinforcement has been realized. However, unexpected deformation has been observed during heating process, particularly in the first thermomechanical cycle. This unanticipated deformation negatively affects the geometrical shape stability of the composite, and as a consequence the geometry preciseness of the structural parts manufactured with shape memory polymer composites will be reduced. In this article, the unanticipated thermal deformation in the shape memory polymer composites during the heating has been observed experimentally, and constitutive relationships to describe this behavior have been developed. Furthermore, an application of a constant tensile load during the heating process on the shape memory polymer composite part was found to be a reliable solution to reduce the thermal distortion effect and improve the geometric stability of the composite. The results showed that developed constitutive relations have shown a good agreement with the experimental results. Furthermore, the proposed applied tensile load has shown significant improvement in the shape memory polymer composite samples’ geometrical shape stability when subjected to a temperature increase.

Estimation of strain of distorted FBG sensor spectra using a fixed FBGfilter circuit and an artificial neural network

Fibre Bragg Grating (FBG) sensors are extremely sensitive to changes of strain, and are therefore an extremely useful candidate for Structural Health Monitoring (SHM) systems of composite structures. Sensitivity of FBGs to strain gradients originating from damage was observed as an indicator of initiation and propagation of damage in composite structures. To date there have been numerous research works done on distorted FBG spectra due to damage accumulation under controlled environments. Unfortunately, a number of related unresolved problems remain in FBG-based SHM systems development, making the present SHM systems unsuitable for real life applications. This paper reveals a novel configuration of FBG sensors to acquire strain reading and an integrated statistical approach to analyse data in real time. The proposed configuration has proven its capability to overcome practical constraints and the engineering challenges associated with FBG-based SHM systems. A fixed filter decoding system and an integrated artificial neural network algorithm for extracting strain from embedded FBG sensor were proposed and experimentally proved. Furthermore, the laboratory level experimental data was used to verify the accuracy of the system and it was found that the error levels were less than 0.3% in strain predictions.

The effect of viscoelasticity on fatigue behaviour of polymer matrix composites

This chapter details the effect of viscoelasticity on fatigue behaviour of polymeric matrix composites. The viscoelastic effects on composite materials under static and dynamic loading are explained using linear viscoelastic analysis. The details of the governing parameters of the fatigue process, such as stress ratio, temperature and the loading frequency are also presented with fatigue life prediction models. Finally, three fatigue life prediction models that have included fatigue and static-fatigue processes in the predictions will be discussed and compared with some experimental data.

Preface: Special Issue of Materials and Manufacturing Processes: “Sensors, Actuators, and Intelligent Processing”

Recent development of smart materials and structures has opened a new page in the materials science and engineering discipline. The use of embedded as well as surface mounted sensors and/or actuators can provide structural information of structures subjected to different kinds of stress generated by mechanically-induced, thermallyinduced, and/or inherent-residual loadings. Some of these damages, located inside the structures, cannot be visuallyinspected till a catastrophic failure occurs. In advanced composite structures, delamination normally is the most severe damage in all types of their applications. The new design of Airbus A380 and Boeing 787 have substantially used composite materials, both carbon and glass fiber types for their primary and secondary structures, delamination of the structures due to foreign object impacts, and thermallyinduced internal cracks may cause the degradation of their structural performance. By using such tiny sensors, embedded inside the structures, we can measure the structural response in real time. Thermography, vibration-control and measuring devices, and embedded fiber-optic sensors have been employed to measure the health condition of composite structures. Due to the size of the sensors, they would not induce any adverse effect to the structures. Some damages can also be assessed by using piezoelectric transducers with incorporated embedded sensors to measure the sound wave propagation characteristics to identify the type and location of damages. All aforementioned nondestructive evaluation techniques require the need of in-depth understanding of the signal characteristics in relation to the type and severity of damages. Wave transmitted responses through different types of composites, such as glass fiber reinforced plastics, carbon fiber reinforced plastics, cementitious materials, and hybrid composites, may vary due to different properties of these materials. In this special issue, all contributors have focused on different aspects of sensors, actuators, and intelligent processing to address the need and importance of new technologies for identifying damages and measuring the structural performance of different kinds of structures.

Use of an elasto-plastic model and strain measurements of embedded fibre Bragg grating sensors to detect Mode I delamination crack propagation in woven cloth (0/90) composite materials

Mode I fracture analysis being employed to study delamination damage in fibre-reinforced composite structures under in-plane and out-of-plane load applications. However, due to the significantly low yield strength of the matrix material and the infinitesimal thickness of the interface matrix layer, the actual delamination process can be assumed as a partially plastic process (elasto-plastic). A simple elasto-plastic model based on the strain field in the vicinity of the crack front was developed for Mode I crack propagation. In this study, a double cantilever beam experiment has been performed to study the proposed process using a 0/90-glass woven cloth sample. A fibre Bragg grating sensor has embedded closer to the delamination to measure the strain at the vicinity of the crack front. Strain energy release rate was calculated according to ASTM D5528. The model predictions were comparable with the calculated values according to ASTM D5528. Subsequently, a finite element analysis on Abaqus was performed using ‘Cohesive Elements’ to study the proposed elasto-plastic behaviour. The finite element analysis results have shown a very good correlation with double cantilever beam experimental results, and therefore, it can be concluded that Mode I delamination process of an fibre-reinforced polymer composite can be monitored successfully using an integral approach of fibre Bragg grating sensors measurements and the prediction of a newly proposed elasto-plastic model for Mode I delamination process.

Development of fracture and damage modeling concepts for composite materials

An overview of proposed micro-crack based damage models for fibre reinforced composite plates is presented. A critical analysis has been performed on the potential application of those models for damage accumulation analysis of wide range fibre reinforced composite materials. The flaws and drawbacks of those models were critically analysed and presented in the text. Interestingly, it has been found that some proposed models can be extended or modified to address unresolved issues in crack propagation and damage accumulation in fibre reinforced composites. It can be concluded that the micromechanical approach alone is not sufficient to evaluate complete damage accumulation of composite and a significant theoretical modifications are required for existing brittle damage models before applying them to fibre reinforced composite materials. The goal of the current paper is an overview of the numerical approaches and approaches’ limitation of plate with multiply cracks problem. The used approaches is discussed and summarized. Equations for two or three dimensions of plate is given for studying effect of crack density on effective moduli. The insensitive effective moduli to the sizes, orientation and location of individual microcracks is also discussed. In addition, the problem associated with limitation of the exciting approaches with increasing cracks density conditions is summarized to approve that necessary modifications the numerical approach and corrections are required. Due to an increase interest in using a fracture mechanics based on microcracks numerical approaches to assess the damage of composite structures, the laminated composites selected as example. The micromechanics approach is not enough to evaluate damage and also most of current theoretical need modification for simulate real conditions.

Prediction of obsolete FBG sensor using ANN for efficient and robust operation of SHM systems

ncreased use of FRP composites for critical load bearing components and structures in recent years has raised the alarm for urgent need of a comprehensive health mentoring system to alert users about integrity and the health condition of advanced composite structures. A few decades of research and development work on structural health monitoring systems using Fibre Bragg Grating (FBG) sensors have come to an accelerated phase at the moment to address these demands in advanced composite industries. However, there are many unresolved problems with identification of damage status of composite structures using FBG spectra and many engineering challenges for implementation of such FBG based SHM system in real life situations. This paper details a research work that was conducted to address one of the critical problems of FBG network, the procedures for immediate rehabilitation of FBG sensor networks due to obsolete/broken sensors. In this study an artificial neural network (ANN) was developed and successfully deployed to virtually simulate the broken/obsolete sensors in a FBG sensor network. It has been found that the prediction of ANN network was within 0.1% error levels.