Dimitrios Zarouchas

Mechanical behaviour of thick structural adhesives in wind turbine blades under multi-axial loading

Abstract Wind turbine blades are made of integrated composite parts bonded together using structural adhesives. The blades are among the most severely multi-axial fatigue loaded structures and the bonded joints play an important role in their structural integrity. For better understanding of the mechanical performance of the bonded joints, thorough knowledge is required on the multi-axial behaviour of the bulk adhesive. In this study, tubular specimens consisting of glass/epoxy bonding paste were subjected to uniaxial (tension, compression and torsion) and biaxial (tension–torsion and compression–torsion) static tests. Different biaxial ratios were used and the stress–strain responses were recorded using strain-gauges. The imposed biaxial stress ratios influenced the stress–strain behaviour of the material system, especially the compression and the shear stress–strain. A material model was developed based on the experimental observations taking into account the non-linear behaviour and the effects of the biaxial ratios and it was implemented together with a progressive damage scenario into a finite-element model. The experimental failure patterns were compared with the numerical simulations and a good match was found.

Online Remaining Fatigue Life Prognosis for Composite Materials Based on Strain Data and Stochastic Modeling

The present study utilizes a state-of-the-art stochastic modeling with structural health monitoring (SHM) data derived from strain measurements, in order to assess the remaining useful life (RUL) online in composite materials under fatigue loading. Non-Homogenous Hidden Semi Markov model (NHHSMM) is a suitable candidate with a rich mathematical structure capable of describing the composite’s multi-state damage evolution in time. The proposed model uses as input SHM data in the form of strain measurements obtained from the Digital Image Correlation (DIC) technique to a coupon-level constant amplitude fatigue test campaign. The obtained from the stochastic model RUL estimations are compared with the actual RUL and the effectiveness of the prognosis is discussed.

Structural health monitoring data fusion for in-situ life prognosis of composite structures

A novel framework to fuse structural health monitoring (SHM) data from different in-situ monitoring techniques is proposed aiming to develop a hyper-feature towards more effective prognostics. A state-of-the-art Non-Homogenous Hidden Semi Markov Model (NHHSMM) is utilized to model the damage accumulation of composite structures, subjected to fatigue loading, and estimate the remaining useful life (RUL) using conventional as well as fused SHM data. Acoustic Emission (AE) and Digital Image Correlation (DIC) are the selected in-situ SHM techniques. The proposed methodology is applied to open hole carbon/epoxy specimens under fatigue loading. RUL estimations utilizing features extracted from each SHM technique and after data fusion are compared, via established and newly proposed prognostic performance metrics.

Comparative study of adhesive joint designs for composite trusses based on numerical models

In the context of lightweight structure design for the transportation and robotics industries, new types of composite structures are being developed, in the form of trusses made of fiber-reinforced polymer composite members of small diameter (a few millimeters thick at most). Some concepts of wound trusses can be found in the literature, but in more general cases, for which a predefined wound truss shape is not usable, individual truss members must be joined together. The axial strength of the composite members allow them to carry a high load, and the joints between those members should be strong enough to carry this load as well. With the objective of developing an efficient joint design for an application in thin composite trusses (member thickness ranging from 0.5 to 5xa0mm), finite element models of several adhesive joint designs were built, and their strengths were compared. The comparison was made using the same joint configuration (number of members, member cross-sectional area, joint dimensions) and loading conditions. Adhesive failure was considered in this study, and the strength of each design was determined from the value of the peak maximum principal strain in the adhesive layer, as this failure criterion is suitable for the toughened adhesive material used in the models. A trade-off between the strength, weight and manufacturability of each joint design was made in order to conclude on their overall performance. Results suggested that, among the joint designs modelled, round-based composite rods inserted in a tubular metallic piece are the most efficient in terms of strength-to-weight ratio.

The use of acoustic emission and composite peel tests to detect weak adhesion in composite structures

ABSTRACT Adhesive bonding is one of the most promising joining technologies for composite aircraft. However, to comply with current aircraft certification rules, current safety-critical bonded joints, in which at least one of the interfaces requires additional surface preparation, are always used in combination with redundant mechanical fasteners, such as rivets and bolts. This lack of trust in bonded structures is mostly linked to the fear of lack of adhesion or a “weak bond”. The aim of this paper is to tackle this challenge by assessing the ability to use composite peel tests and acoustic emission (AE) technique to assess adhesion quality and distinguish a good bond quality from a “weak bond”. Composite Bell Peel (CBP) tests and Double-Cantilever-Beam (DCB) tests were performed on contaminated and non-contaminated CFRP bonded specimens. The results show that peel strength drops significantly at the location of the contaminated interface that has led to weak adhesion, as a result from adhesive failure. The AE signals obtained during DCB tests show different features for cracks growing at the interface (“weak bonds”) and inside the adhesive layer (cohesive failure). In addition to this, scattering of the AE signals were observed in the contaminated specimens with “weak bonds”.

A Mechanics-informed Method for Real-time Acoustic Emission Source Classification During Fatigue Loading of Composite Structures

This paper presents a new approach aiming to improve the classification method of Acoustic Emission activity with a material mechanics perspective and to provide the means for real-time classification. This mechanics-informed approach consists of using the instantaneous fatigue cycle phase as hit labels. Two different types of materials were tested under Tension-Tension fatigue loading at R=0.1. The main goal was to trigger matrix cracking as the dominant failure mechanism and measure the stiffness degradation. In order to validate the approach, the stiffness degradation was measured using Digital Image Correlation. From the fatigue cycle phase labelling of hits, at least two distinct clusters were observed: first, the hits occurring mainly in the loading phase of the fatigue cycle, whichs activity correlates with the rate of stiffness degradation in the test specimens; and second, the hits occurring in the lower part the unloading phase of the fatigue cycle.

Online Remaining Useful Life Prognosis for Composite Materials Based on Acoustic Emission and Strain Data

The procedure of fatigue damage accumulation in composite structures, is a complex phenomenon due to the multiphase nature of composites, the variation of inherent manufacturing defects, the randomness of loads, the stochastic activation of different damage mechanisms and an incomplete knowledge about the physics behind the evolution and interaction of damage mechanisms. In order to develop a robust model, which will reliably estimate the remaining useful life of the structure, we hypothesize that the damage accumulation process is of a stochastic nature and we propose a framework that combines a stochastic model with structural health monitoring data. In this study, the Non-Homogenous Hidden Semi Markov model and acoustic emission and strain data extracted from fatigue tests of open-hole quasi-isotropic carbon fibre reinforced polymers are selected. The damage accumulation is a hidden process and the goal of the framework is to correlate the structural health monitoring data with the parameters of the model and identify the hidden relationship. In conclusion, the remaining useful life estimations of each structural health monitoring technique are compared with the actual remaining useful life and based on performance metrics it was found that the strain data provided more accurate predictions.