Fatigue crack growth characterization of layered composite materials using acoustic emission. Alexander LEITER

Transcription

1 Fatigue crack growth characterization of layered composite materials using acoustic emission 28th September 2016 Alexander LEITER Supervisors Cranfield University: Dr. Isidro DURAZO-CARDENAS Dr. Daniel GAGAR Supervisor Politecnico di Milano: Prof. Giuseppe SALA MSc in Aeronautical Engineering School of Industrial and Information Engineering ACADEMIC YEAR 2015/2016

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3 ii Abstract Natural Gas (NG) is mainly used for the generation of electricity. It is transported in liquefied form at -160 C in vessels with specially insulated storage tanks. An advanced insulation material is used to protect the internal surface of the structure from both cryogenic conditions and fire; however, when damaged, fatigue cracking occurs under low frequency wave-induced vibrations experienced by the vessel. Mechanical tests were performed under cyclic loading, along with online fatigue crack monitoring using acoustic emission (AE) and resistive crack gauges to characterise growth behaviour. It was found that there is a general reduction in crack growth rate da/dn with increasing stress intensity factor range K as crack growth approaches the layered interfaces, which is also independent of the stress range. Furthermore, estimates of da/dn and crack length obtained from AE signals are in close agreement with measurements from resistive crack gauges. Keywords: Insulation material; Layered composite; Fatigue crack growth; Acoustic Emission (AE); Resistive crack gauge; Crack length estimation.

4 CONTENTS iii Contents Abstract List of Figures List of Tables ii v vi 1 Introduction 1 2 Aim and Objectives 3 3 Literature review Fatigue crack growth near an interface Fatigue crack monitoring techniques Acoustic emission (AE) Research Method Material Fatigue crack growth test Crack propagation Acoustic emission Optical microscope Environmental Scanning Electron Microscope Hardness test Results and discussion Crack propagation Crack growth rate AE signals compared to crack growth Sorting of AE signals Crack length estimation Analysis of the crack path Summary 42 7 Conclusions 43 Acknowledgements 44 References 45

5 LIST OF FIGURES iv List of Figures 1 LNG tanker [modified from carrier]. 1 2 Fatigue crack paths: cracks propagated (a) temporarily and (b) permanently along the interface [8] a) Fatigue crack growth, crack initiated in weaker ferrite phase; b) Optical micrograph of the crack profile [9] Examples of fracture modes at fibre/matrix interface [12] Schematic of a CVM sensor [16] Characteristics of an AE signal [24] AE at peak load and fatigue crack length when applying a single overload [25] Scheme of the research method One of the specimens used for testing Specimen with the machined notch Crack length sensor mounted on the specimen AE sensors mounted on the bottom of the sample Fatigue test set up Bending test, left: 3-point configuration; right: 4-point configuration [28] Force diagram of the 4-point bending configuration [7] Cross-section of the specimen with stress distribution Interface of LabView for recording the data Assembling of the AE elaboration system [31] Standard channel setup [30] Parameter setup [30] Example of the 3D Screen Crack length in function of number of cycles - Sample Crack length in function of number of cycles - Sample Crack length in function of the number of cycles - Sample Crack growth rate in function of crack length - Sample Crack growth rate in function of K - Sample AE counts and crack length as a function of the number of cycles - Sample AE counts and crack length as a function of the number of cycles - Sample AE counts and crack length as a function of the number of cycles - Sample Sorting of AE signals regarding the load cycle (modified from [33]) Kernel density estimation of AE signals - Sample AE counts (60%) and crack length in function of the number of cycles - Sample AE counts (60%) and crack length in function of the number of cycles - Sample AE counts (60%) and crack length in function of the number of cycles - Sample AE counts/cycle (100%) and crack growth rate in function of K Sample Approximation with power trend lines of AE counts/cycle (100%) and crack growth rate in function of K Sample Crack length estimation - Sample

6 LIST OF FIGURES v 38 Crack length estimation - Sample Crack length estimation - Sample Sample 1 (segmented) after test and micrograph of the crack Sample 2 (segmented) after failure and micrograph of the crack after Test Sample 3 after failure

7 LIST OF TABLES vi List of Tables 1 Average values of sample dimensions Test parameters of the different fatigue tests

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9 1 INTRODUCTION 1 1 Introduction Natural gas (NG) is a natural resource that, amongst others, is used as fuel and to generate electricity and heat [1]. In 2013 one quarter of the primary energy consumption in the EU-28 can be attributed to the use of natural gas [2]. The most economical way to transport the gas is in liquefied form (LNG) [1], through pipeline networks or by shipping in large vessels (Figure 1) [2]. Therefore, the gas is condensed by cooling it to around -160 C and by maintaining a pressure below 1 bar [3]. These cryogenic conditions make the storage of the LNG challenging. As the LNG interacts with the steel structure of the tanker, the steel will embrittle, which could lead to catastrophic failure of the entire structure. To prevent this, a thermal protection must be applied [4]. Figure 1: LNG tanker [modified from carrier]. A layered composite material was developed. It is intended to protect the steel from the effects of hydrocarbon pool and jet fires as well as from the cryogenic conditions [5]. Figure 1 shows a typical insulation coating of LNG storage tanks. The fire protection layer, from now on referred to as material A, when exposed to heat, will react and intumesce. This reaction starts at the external surface and propagates toward the substrate, as the heat penetrates the coating [6]. However due to its high specific heat capacity it is also suitable for protecting steel structures against extremely low temperatures [4]. Regarding the technical data sheet [5], Material A is a high performance epoxy intumescent fire protection coating system. The coating is sprayed on the substrate until the desired thickness is achieved. If required a carbon-glass fibre composite mesh reinforcement can be installed at mid thickness [5]. To increase the thermal insulation, a layer acting as thermal barrier should be installed between substrate and material A. This insulation material is a high performance thermal insulator, which has been tested in cryogenic conditions and has proven to prevent low temperature embrittlement of steel. This material is referred to as material B from now onwards. Typical thicknesses are 4-20 mm and 5-50 mm for material A and material B layers respectively [5].

10 1 INTRODUCTION 2 It was observed, when the composite material is damaged, fatigue cracking occurs under low frequency wave-induced vibrations experienced by the vessel. In a previous analysis this coating was analysed in terms of fracture toughness, fatigue and fatigue crack growth [7]. During the fatigue tests an unusual behaviour of the crack growth was noticed; the crack growth rate decreased continuously as the crack was propagating.

11 2 AIM AND OBJECTIVES 3 2 Aim and Objectives The aim of this work is the material characterization of fatigue crack growth in advanced insulating materials using online monitoring techniques. Three different objectives were defined: Perform mechanical tests to initiate and grow fatigue crack Implement instrumentation for online fatigue crack monitoring Verify the fatigue crack growth behaviour using different methods Before starting with the tests, various scientific works were studied to gain more detailed knowledge about fatigue crack growth and acoustic emission. The following section describes different crack growth behaviours and some fatigue crack monitoring techniques examined in the past by different authors.

12 3 LITERATURE REVIEW 4 3 Literature review 3.1 Fatigue crack growth near an interface The fatigue crack growth behaviour near an interface has been studied by different authors. Tilbrook et al. [8] analysed crack paths in layered graded ceramic composites by using an alumina-epoxy system. A notch was introduced in the graded composite parallel to the interface of the epoxy layer. Figure 2 shows that during the fatigue bending tests the crack propagated and deflected toward the compliant layer due to greater release of potential energy. When reaching the interface, the crack deflected and propagated along the interface when this was weak or otherwise continued propagating in the next layer. It was found that the crack propagation can be influenced by introducing different types of layers. While a weak layer makes the fatigue crack deflecting, a tougher one can absorb the energy of crack propagation and decreases or even constrains the fatigue crack growth. It was shown that the interface had a considerable effect on the crack propagation and deflection [8]. Figure 2: Fatigue crack paths: cracks propagated (a) temporarily and (b) permanently along the interface [8]. Other studies investigated fatigue cracks that were propagating toward a perpendicular interface. Suresh, Sugimura, and Tschegg [9] studied the crack propagation in a bimaterial, consisting of ferritic and austenitic phases. Firstly the crack was initiated in the softer and weaker ferritic phase. Afterwards the crack was initiated in the harder and stronger austenitic phase. During the first test the fatigue crack growth rate decreased continuously, as shown in Figure 3. As the crack got closer to the interface, the plastic zone around the crack tip interacted with it and increased the resistance to propagation. Therefore the crack began to deviate from the original growth direction, which decreased the

13 3 LITERATURE REVIEW 5 propagations rate further below the threshold growth rate of 10ˆ-10 m/cycles, before the crack passed through the ferrite/austenite interface. However, when the crack was initiated in the harder phase the crack growth behaviour was totally different. The crack growth rate slightly increased near the interface and the crack propagated through it without being deflected. Figure 3: a) Fatigue crack growth, crack initiated in weaker ferrite phase; b) Optical micrograph of the crack profile [9]. Sugimura et al. [10] and Pippan, Flechsig, and Riemelmoser [11] explain the principle of this behaviour in bi-material systems. The formers used austenitic stainless steel and ferritic lowcarbon steel for their study; the latters used pure iron and ferritic steel. When the plastic zone in front of the crack interacts with the interface, the effective stress intensity at the crack tip changes [11]. If the crack is initiated in the weaker material the effective stress intensity at the crack tip is smaller than the applied one, as the plastic zone at the crack tip is reduced. Thus the crack growth is slowed down and gives an effect of crack tip shielding. The opposite occurs when a crack is initiated in the stronger material. The effective stress intensity at the crack tip is higher, which accelerates the fatigue crack growth [11]. Regarding Sugimura et al. [10] the effective stress intensity at the crack tip governs weather the crack propagates trough the interface or not. Furthermore Pippan et al. [11] analysed interlayer systems. It emerged that with a strong interlayer in a weak material, the crack bifurcates when approaching the interlayer. However, using a weak interlayer in a strong material, the crack advances through the interlayer interface and becomes arrested and bifurcates within the interlayer [11]. Finally, Ahn et al. [12] explain the interfacial crack behaviour of fibre reinforced composites. Results showed that the crack will be deflected along the fibre/matrix interface, when this is weak. Contrary if the interface is strong, the crack will grow through the fibre. Figure 4 shows different fractures modes at the fibre/matrix interface. The fracture mode characterizes the material behaviour. While the deflected crack tends to make the composite more though, the penetrated one tends to make it more brittle.

14 3 LITERATURE REVIEW 6 Figure 4: Examples of fracture modes at fibre/matrix interface [12]. In summary, all these authors found that the interface and layer properties have a high influence on the fatigue crack growth. When the crack approached the interface from the weaker layer, the following characteristics were observed: reduction in crack growth rate, crack bifurcation and crack deviation 3.2 Fatigue crack monitoring techniques Modern structures must withstand different environments for long periods. Structural health monitoring techniques can reduce maintenance costs by continuously monitoring structural parameters and evaluating the integrity of the structure [13]. For crack and damage detection, two main sensing techniques can be used; direct and indirect sensing [14]. On one hand, the former sensors are in direct contact with the damage and are therefore more reliable. However a large amount of sensors is needed [14]. Direct sensing techniques uses for instance resistive crack gauges, discrete strain sensors and comparative vacuum monitoring (CVM) sensors. Vanlanduit, Guillaume, and Van Der Linden [15] used a resistive crack gauge to determine the crack length during fatigue tests. It is made of several resistor strands connected in parallel. As the crack propagates, circuits of the broken strands are opened and the total resistance is increased. The total resistance can be correlated to crack length. The distance between the different strands and therefore the resolution of the gauge was 0.25 mm. Yao and Glisic [14] explained the use of strain sensors for detecting fatigue cracks. A material fails at a specific stress value. However, it is much easier to monitor the

15 3 LITERATURE REVIEW 7 strain, which is correlated to the stress, than directly monitoring the stress. Roach [16] used the CVM method for crack detection. CVM sensors are bonded on the surface. Small channels are incorporated in the adhesive, which are alternatively exposed to vacuum and atmospheric pressure. Figure 5 represents a schematic of a CVM sensor. As a crack penetrates this channels the internal pressure changes due to leakage, which indicates the presence of cracks. Figure 5: Schematic of a CVM sensor [16]. On the other hand, for indirect sensing, the sensors are not in direct contact with the damage. Therefore a smaller amount of sensors is needed, which although are not as good as direct sensors in terms of noise filtering [14]. Indirect sensing methods exploit for example vibrations, impedance or ultrasonic techniques. Vibrations of the surface, detected by piezoelectric sensors, can be utilised to identify hidden fatigue crack growth. The sensors detect physical movements, which are converted in electrical charges [17]. Electromechanical impedance were used by Park et al. [18]. Structural changes in the samples modify the structural mechanical impedance and so also the electrical one of the piezoelectric material. Finally, ultrasonic techniques use pulser and receiver transducers [13]. Ultrasonic waves are scattered at crack surfaces. As a consequence the reflections in cracked areas differ from those in undamaged areas and indicate the presence of damage [19]. 3.3 Acoustic emission (AE) Events as crack initiation, crack growth and delamination release elastic waves [20]. As soon as these approach the surface, piezoelectric transducers detect the signal, which becomes amplified, filtered and subsequently analysed [21]. Phenomena as crack initiation, crack growth, crack opening and closure and dislocation movement can be identified [22]. The use of AE is interesting when analysing composite materials; it is possible to analyse and classify the different types of damage: inter alia matrix cracking, fibre breakage and fibre-matrix deponding/delamination [23]. The main advantage is that fracture events can be monitored during a test or in service. However the interpretation of the signals is not straightforward [21]. Regarding Roberts and Talebzadeh [24] typical AE signal characteristics are counts, amplitude, duration, rise time and energy, as shown in Figure 6.

16 3 LITERATURE REVIEW 8 Figure 6: Characteristics of an AE signal [24].

17 3 LITERATURE REVIEW 9 To reduce the influence of external noise only peaks higher than the threshold value are captured [24]. Huang et al. [22] give another example of noise reduction, the so-called location filtering technique. This involves four AE sensors, which were distributed in a line; two on each side of the notch. The signal was only recorded when the inner sensors captured the signal before the outer ones. Otherwise it could be assumed that the signal was an external noise and was not related to crack growth. Lindley, Palmer, and Richards [25] mentioned the separation of AE signals; the signals that occurred close to the peak load and those close to the minimum load. While the former were related to the process of fatigue crack growth, the latter were related to the process of crack closure. This was achieved by counting only the acoustic emissions within a certain load range. For instance, for analysing the crack growth only the upper 40% of the load range were initially considered. However to reduce the crack closer emission noise the range was reduced to the top 20%. Morton et al. (as cited in [25]) studied the fatigue crack behaviour of aluminium and magnesium alloys and correlated the fatigue crack growth rate (da/dn) with the peak load emission rate (N ). The Paris law and a similar power law represent both processes respectively. da dn = C0 Kn (1) N = C 1 K m (2) A similar correlation can be made with the theoretical Forman equation, which takes account of more parameters. da dn = C 2 K p (1 R)(K c K max) N = C 3 K q (1 R)(K c K max) In these relations K=stress intensity factor range, K c=critical stress intensity factor, K max=maximum stress intensity factor, R=load ratio and the remaining parameters are different constants. Berkovits and Fang [20] specified a relation between da/dn and N. By substituting (1) in (2) and rewriting the resulting expression, the correlation can be identified: ( ) Φ N da = C 4 (3) dn with C 4 = C 1 and Φ = m. This relation allows to calculate the crack length increment or directly the crack length if the initial crack length is C m/n n 0 known. Lindley et al.[25] showed the relation between acoustic emission and fatigue crack growth by applying a single overload. It is referred to as a single overload when, during fatigue test, the load is rising once above the normal maximum load. In this case residual plastic deformations result in a zone of compressive stresses around the crack tip, which leads to crack growth retardation [26]. In Figure 7 can be seen that the AE and fatigue crack growth are closely correlated. Initially the AE were around 32 counts/cycle and the crack was growing considerably. As soon as the overload was applied, the crack practically arrested and the AE signals significantly dropped. Only after cycles the crack growth gradually restarted and the AE increased. At the end the crack assumed the initial growth rate and the AE levelled off at around the

18 3 LITERATURE REVIEW 10 initial value [25]. Figure 7: AE at peak load and fatigue crack length when applying a single overload [25]. This confirmed that the crack growth is associated with the emission of acoustic signals. However, the analysis of the AE signal and the subsequently crack length estimation are not straightforward. In some materials also other phenomena, as inclusion for example, emit stress waves. In general the emissions depend on three factors: material, loading and geometry. Research of fatigue crack behaviour near an interface with the use of acoustic emission on insulation layered materials has not been studied in the past. Therefore no specific articles or work could be found with regard to the application of AE on these materials. However the understanding and monitoring of fatigue crack propagation is of fundamental importance to prevent catastrophic failure of insulation materials as discussed in section 1. This report aims to relate the data obtained from resistive crack gauges to those from the AE. To fill a critical knowledge gap and to make the most of the AE signals, three different objectives regarding the use of AE were defined in this work: Collecting data and evaluate the quality of the signal Separate the AE signals regarding the loading cycle Perform crack length estimation This section helped to understand on one hand the crack growth behaviour of different materials and on the other a general application of AE. Even though these studies

19 3 LITERATURE REVIEW 11 were not strictly related to this work, with the combination of them it was possible to make some assumption about what to expect. The carbon-glass fibre mesh is expected to decrease the fatigue crack growth in a similar way as a harder interlayer. However the discontinuity of the fibres might affect the crack growth behaviour along the specimen. For this reason it could be interesting to section the samples and observe the crack path in different locations. Once this interlayer has been penetrated, the crack growth rate is expected to increase as the crack propagates. The rise although should not be drastic, because the crack approaches the material A/material B interface fairly soon. Hardness tests are expected to confirm that material B is harder than material A. Therefore the propagation rate should decrease again before reaching this interface. The hardness values of material B are much lower compared to the carbon-glass fibre mesh and so the growth rate is supposed to alter not as much as it did the first time.

20 4 RESEARCH METHOD 12 4 Research Method At the beginning a literature research was conducted in order to understand which problems have already been studied and how they have been clarified. Subsequently the fatigue tests were carried out. Three samples were tested in this study and are referred to as Sample 1, Sample 2 and Sample 3 in this report. Different tests were performed and were terminated when reaching about 1 million of cycles without fracturing the sample. Afterwards some parameters were changed and another test was continued. The scheme in Figure 8 gives a brief outline of the research method of this study. Figure 8: Scheme of the research method. 4.1 Material All the samples were produced and supplied by the sponsoring company. They were composed of a material A layer with a mesh reinforcement, a carbon-glass fibre composite, embedded in the middle. Above it there was a layer of material B, as represented in Figure 9. Both layers presented a high porosity; material A appeared slightly more porous than the material B. The dimensions of the samples varied between different samples, as well as along the length of each sample. The specimens were approximately 200 mm in length, 50 mm in width and 27.5 mm thick. The material A and the material B layers had a thickness of around 12.5 mm and 15 mm respectively. The preparation of the samples was fairly simple. Firstly the sides of the samples were polished by using a metallographic plate with a 240 grit paper, to flatten the surfaces. As the samples were moulded the external surfaces needed to be polished, which contributed to the difference in dimension of the various specimens.

21 4 RESEARCH METHOD 13 Figure 9: One of the specimens used for testing. Subsequently the specimens were sent to a workshop, where the notch was machined into material A. This configuration is intended to simulate real conditions, as cracks likely initiated in this material. Figure 10 shows the notch with a depth of 3 mm. With this dimension it did not penetrate the carbon-fibre mesh and so the fatigue crack growth behaviour near the mesh interface could be investigated. Figure 10: Specimen with the machined notch. Before the various sensors were mounted on the specimens the dimensions were measured with a Vernier Calliper at 4 different locations. For calculation purposes the average of these values were taken. Table 1 summarizes the different values.

22 4 RESEARCH METHOD 14 Table 1: Average values of sample dimensions. length l [mm] width w [mm] thickness t [mm] Sample Sample Sample Finally the sensors were mounted. The resistive crack gauges were positioned on the sides of the specimen, just above the notch. They were aligned with the notch apex, with approximate 0.5 mm of accuracy (Figure 11). This gauges are composed of several resistor strands connected in parallel and the total resistance is related to the crack length. While Sample 1 had only one gauge on each side, on Sample 2 a second one was mounted on the top of the first one before the second test was continued. In this way it was possible to monitor the crack growth near the fibre mesh, as well as near the material A/material B interface. Figure 11: Crack length sensor mounted on the specimen. Two AE sensors were symmetrically placed at the bottom of the specimen with a silicon rubber paste (Figure 12). On Sample 1 they were attached about 6 cm distant from the notch. However for the following two samples this distance was reduced to 5 cm to capture more AE signals.

23 4 RESEARCH METHOD 15 Figure 12: AE sensors mounted on the bottom of the sample. 4.2 Fatigue crack growth test The fatigue tests were performed on a calibrated servo-hydraulic DMG testing machine of 20kN load capacity. Figure 13 represents the test set up with the mounted sample. All the samples were loaded in such a way that the lower face of material A was always in tension, while the upper face of the material B was always in compression. The stress values were chosen by taking the most suitable values from [7]. These values gave results, which were the easiest to interpret and analyse. The stress ratio and the frequency were kept constant at 0.1 and 2 Hz respectively. The stress values are dependent on the geometry of the samples. As their dimension varied with the different specimens, it was necessary to evaluate the maximum and minimum load for each specimen, which produced the specific stress values. Table 2 at the end of this section summarizes the values for the various specimens.

24 4 RESEARCH METHOD 16 Figure 13: Fatigue test set up.

25 4 RESEARCH METHOD 17 In the following part of this section, the relation that correlates the load with the stress was derived. The fatigue crack growth test was carried out by using a four-point bending configuration. This configuration is slightly more complicated than a three-point configuration, but gives a constant bending moment in the centre section of the specimen. Contrary, a three-point configuration would introduce a variable bending moment along the axial direction and a shear force at the centre, where the notch was introduced (Figure 14) [27]. Figure 14: Bending test, left: 3-point configuration; right: 4-point configuration [28]. Figure 15 shows the force diagram of the four-point bending configuration of the fatigue test. With a simple equation it is possible to calculate the bending moment in function of the load P and the axial distance z: M x(z) = P 2 z, 0 z 50mm P 2 z P [ ( )] L l P (L l) z =, 50mm < z 90mm Therefore the bending moment at the centre of the specimen could be calculated as follows: P (L l) M x = 4 Once the bending moment is known, the stress could be calculated with the Navier equation, by applying the Saint-Venant beam theory [29]: σ z(y) = Mx I x y with M x the applied bending moment and I x the moment of inertia with respect to the x-axis (Figure 16).

26 4 RESEARCH METHOD 18 Figure 15: Force diagram of the 4-point bending configuration [7]. Figure 16 shows the cross-section of the specimen and the stress distribution caused by the bending moment M x. It can be seen that the stress σ z varies proportional with the distance (y) to the principle axes of inertia x. While the + indicates tension, the - indicates compression [29]. Figure 16: Cross-section of the specimen with stress distribution. For a rectangular specimen the moment of inertia with respect to the x-axis can be calculated easily. I x = wt3 12 The maximum stress at the notch must be the same for all tests and specimens, so that the different results can be compared. However, the dimensions of the specimens were not constant and therefore it was necessary to vary the maximum bending moment, in order to obtain the same stress values at the surface of the specimens. When

27 4 RESEARCH METHOD 19 substituting I x, M x and y in the Navier equation, the following expression is obtained: σ z,max = Mx,max I x t 2 = 6 Mx,max = 3 P max(l l) (4) wt 2 2 wt 2 In this equation only the maximum load P max is variable. The other parameters, L and l, were fixed at the beginning and were kept constant for all the tests; w and t were depended on each specimen. The last step was to calculate σ max in function of the stress range σ and the stress ratio R. This was necessary because all the tests were performed with a defined stress range and stress ratio. σ = σ max σ min R = σmin σ max When combining both equations the following expression is obtained: σ max = σ 1 R Table 2 lists the various test parameters. The stress ratio R and the bending frequency f were maintained constant throughout all the tests. On Sample 1 only one test (Test 1) was performed, which was terminated after about 1 million of cycles. The stress range was considered too low and was increased for further tests on Sample 2. On this sample three tests were carried out. Test 2.1 and Test 2.2 were stopped at roughly 1 million of cycles. The stress values from Test 2.2 were higher than those from Test 2.1 and Test 1. Test 2.3 was the last test and used the same parameters in terms of stress as the previous test. This test terminated with a through crack fracture of Sample 2. Finally, on Sample 3 one test was carried out. The same parameters as for the last tests on Sample 2 were used and it finished after fracture occurred. Table 2: Test parameters of the different fatigue tests. Sample 1 Sample 2 Sample 3 Test 1 Test 2.1 Test 2.2 Test 2.3 Test 3 R f [Hz] σ [MPa] σ min [MPa] σ max [MPa] Crack propagation The sensors are composed of various resistor strands, spaced 0.25 mm apart each other. Therefore the resolution of these resistive crack gauges was 0.25 mm. As the crack propagates it breaks resistor strands, which increases the total resistance. The value of the resistance can be related to the fatigue crack length. However this is not straightforward, because the variation of the resistance is not constant. Thus the sensors had to be calibrated before using.

28 4 RESEARCH METHOD 20 During the test the resistance of both resistive crack gauges was noted as a function of time, which then was converted to the corresponding number of cycles. The values were saved every 10 min automatically by using the LabView software (Figure 17). Additionally the values were saved manually at the beginning of the test, as a rapid crack propagation was expected. At the end of the test all the data were imported in Excel, where they have been sorted and analysed. Figure 17: Interface of LabView for recording the data. 4.4 Acoustic emission For the AE analysis the PCI-2 system from Physical Acoustics was used. It contained two channels with the ability of simultaneous capturing and progressing AE data. The system consists of a based system (AE system chassis, integrated computer and PCI-2 cards), sensors, preamplifier and connecting cables. Figure 18 shows the assembling of the AE elaboration system. The AE sensors use the piezoelectric effect of PZT for detecting stress waves when they reach the surface and transforming them into an electrical signal. They were connected to a pre-amplifier, where the extremely low amplitude AE signal was amplified and filtered. The based system is connected downstream of the pre-amplifier. [30]

29 4 RESEARCH METHOD 21 Figure 18: Assembling of the AE elaboration system [31]. To correlate the AE signal with the load applied by the fatigue testing machine, both were connected. The latter transformed the value of the load into a voltage output, which then was recorded by the AE system. In this way it was possible to monitor the AE signals in function of the load and cycle, which was of fundamental importance for being able to sort the AE signals with regard to the load cycle. The software used for data acquisition was AEwin. Before starting with the data acquisition some parameters had to be defined. Firstly the values of the threshold and preamplifier were defined (Figure 19). Initially both values were set to 45 db. However after the first test it emerged that the AE data acquisition was not as numerous as expected. Therefore for the following tests the threshold value was reduced to 40 db and the AE sensors were placed closer to the notch. Subsequently the various measurable AE parameters that should be recorded were selected (Figure 20). During the test all the data were recorded and displayed in real time on the screen (Figure 21). Figure 19: Standard channel setup [30].

30 4 RESEARCH METHOD 22 Figure 20: Parameter setup [30]. Figure 21: Example of the 3D Screen. 4.5 Optical microscope After the tests were carried out the specimens were observed under the optical microscope and with the ESEM (Environmental Scanning Electron Microscope). As optical microscope a Nikon ME600 Eclipse was used. The advantage of the optical microscope was the possibility to look at the samples between each test with no need of preparation. The magnification was large enough to be able to see the crack path. At the end of tests the samples were sectioned longitudinally through the centre. Owing to this it was possible to examine more sections per sample.

31 4 RESEARCH METHOD 23 After the samples were cut some polishing was necessary. This was carried out by using a very fine grit paper (2500). The coarser ones were too aggressive and tended to fill the crack with the abrasive material, making the crack not perceptible. 4.6 Environmental Scanning Electron Microscope The Phillips XL30 was used. It was required to use the ESEM instead of the SEM (Scanning Electron Microscope), because the samples were mainly composed of epoxy and so not conductive. Apart from examining the crack path, the ESEM was expected to be suitable to detect the branching of the crack. However regarding this the results were not as assumed to be. As the sample broke it was not possible to clearly find or identify micro cracks or branching near the fracture line. However, as a result of the fracture the fracture surface could be examined. 4.7 Hardness test The hardness of the different layers is an essential parameter in terms of fatigue crack growth and is vital to understand the growth behaviour near the material A/material B interface. For having some up-to-date values a harness test was carried out. Due to the high porosity of the material a micro hardness tester, from Matsuzawa Seiki, was used. Furthermore the high porosity made the determination of the hardness not straightforward, because the resultant indent was not always perceptible. The test was performed with a load of 100 g for 15 s, because it gave the clearest results.

32 5 RESULTS AND DISCUSSION 24 5 Results and discussion In this section the results from the different samples are summarized and analysed. Firstly the data obtained from the resistive crack gauges and the AE are considered. Subsequently this results are compared with the crack path, captured with the optical microscope. Some parts of the following discussion is focused on the results of Sample 2, as these data are the most significant and describe the behaviour until failure. 5.1 Crack propagation Figure 22 - Figure 24 show the crack propagation of Sample 1, 2 and 3 respectively. The blue dashed lines represent the different interfaces. The first one represents the glass-carbon fibre mesh and second one the material A/material B interface. Furthermore the grey solid lines define the transition between different tests performed on one sample. To obtain this graph, the data of both sensors were considered and averaged. Even though the crack length is measured by means of resistive crack gauges it represents an estimation; sensors were mounted only on the surface of each side. Values confirmed that the crack length on both sides differed slightly but continuously. The difference usually was less than 1 mm, which corresponded to four resistor strings. However the maximum difference of nearly 5 mm was reached just before the sample broke. Furthermore it was observed that sometimes one of the glass-carbon fibres was located near the surface. In this case the corresponding sensor was continuously under reading with respect to the opposite sensor. This is reasonable due to the resistance to propagation imposed by the fibres. When comparing the different samples it can be seen that all of them behaved differently. The crack in Sample 1 (Figure 22) did not penetrate the first interface. The crack growth slowed down very quickly after the beginning. The crack seemed to be arrested before the test reached cycles, the predefined runout limit. This sample was subsequently sectioned to examine the fatigue crack path in different location. As a consequence the stress range was increased for Sample 2 (Figure 23). The cracking behaviour during Test 2.1 is similar to the previous one. After the runout limit was nearly reached the test was stopped and a new one continued. For this new test the stress range was increased again. All the following tests (Test 2.2, Test 2.3 and Test 3) were performed using the same stress values. During Test 2.2 the crack grew considerably. However fracture occurred only after Test 2.3. Sample 3 (Figure 24) was tested since the beginning with the largest stress range. Fracture occurred before reaching 10,000 cycles and the fracture mode was different compared to Sample 2. Reason for this might have been the aged conditions of the specimen.

33 5 RESULTS AND DISCUSSION 25 Figure 22: Crack length in function of number of cycles - Sample 1. Figure 23: Crack length in function of number of cycles - Sample 2.

34 5 RESULTS AND DISCUSSION 26 Figure 24: Crack length in function of the number of cycles - Sample Crack growth rate To illustrate the fatigue crack growth behaviour, Figure 25 represents the crack growth rate in function of the crack length. Only the data from Sample 2 are plotted as these give an overall concept. It can be seen that the crack growth rate decreases with increasing crack length. This is reasonable as the distance to the interface decreases and the plastic zone in front of the crack starts to interact with the glass-carbon fibres. Agreeing with the information from section 3 the resistance to crack propagation seems to increase and the crack growth slows down considerably. As soon as the stress range is increased (Test 2.2) the crack growth accelerates before slowing down when approaching the first interface. This behaviour is very similar to the crack growth in metals, illustrated in Figure 3 in section 3. Once the first interface is penetrated and the effects of the fibres are not perceptible anymore the crack growth rate picks up again. However it appears that it is interface fairly soon influenced by the second. The crack growth starts dropping even before the crack is 1 mm away from the first interface. The reduction was expected as the hardness of material A was double compared with material B. Nevertheless care must be taken when looking at the region between 8 and 10 mm. In this area no resistive sensor was mounted and therefore no additional data points were recorded. The two sensors were mounted about 2 mm apart from each other to make sure to capture as much data as possible near the second interface and before failure occurs. Consequently the crack growth behaviour just before the second interface cannot be studied in depth. However when looking at the graph in Figure 23 the growth behaviour in front of the second interface looks similar than in front of the first one. The reduction in growth rate seems not as dramatic as in front of the glass-carbon fibre mesh. Finally, during Test 2.3 only a few data points have been captured. The reason for

35 5 RESULTS AND DISCUSSION 27 this is the rapid acceleration of fatigue crack growth after the interface is penetrated and just before fracture occurs. Figure 25: Crack growth rate in function of crack length - Sample 2. Before analysing the results from AE, it is necessary to calculate the stress intensity factor range K to be able to compare later crack propagation with AE by using equation (3). K can be calculated as follows [32]: K = f(a/t) σ πa = f(a/t) 6 M πa wt 2 = f(a/t) 3 P (L l) πa 2 wt 2 This expression considers only pure bending stresses. By substituting σ and M with the expression from equation (4), the last expression is obtained. Finally for evaluating the function f(a/t) a simple notch was considered, which can be expressed as follows [32]: ( a ) ( a ) 2 ( a ) 3 ( a ) 4 f = t t t t With this equation it is possible to calculate K in function of the crack length. Figure 26 represents the crack growth rate in function of K for Sample 2. For more comprehensibility the graph was plotted with a continuous line, even though only discrete values were measured. All the features described above can be seen in Figure 26 as well. To summarise, a general reduction of the crack growth rate with increasing K as crack growth approaches the interfaces can be observed. This trend is independent of the stress range. The crack growth rate rapidly increases before final failure occurs.

36 5 RESULTS AND DISCUSSION 28 Figure 26: Crack growth rate in function of K - Sample AE signals compared to crack growth During the different tests a huge amount of AE data have been recorded. Figure 27 - Figure 29 show the AE counts and the crack length in function of the number of cycles from the three samples. No obvious correlation between AE counts and crack propagation can be observed. However these graphs give an idea of how many data points have been acquired. For Sample 3 (Figure 29), the AE counts are plotted in relation to 1,000 cycles instead of 50,000 as for both other samples. This was necessary because the test lasted less than 10,000 cycles. Figure 27: AE counts and crack length as a function of the number of cycles - Sample 1.

37 5 RESULTS AND DISCUSSION 29 Figure 28: AE counts and crack length as a function of the number of cycles - Sample 2. Figure 29: AE counts and crack length as a function of the number of cycles - Sample 3.

38 5 RESULTS AND DISCUSSION Sorting of AE signals As mentioned by Lindley et al. [25], the AE signals occurring near the peak load can be attributed to the mechanism of crack propagation. Therefore it was essential to sort the AE signals regarding the load cycle. Figure 30 shows an example, where only 60% of the upper load range is considered. Consequently only the AE signals occurring within this load range are studied. Figure 30: Sorting of AE signals regarding the load cycle (modified from [33]). This can be described more clearly with Figure 31. The red points in the x-y plane represent the AE signals, which are attributed to the number of cycles and the load of their occurrence. The points within the 30% range, for instance, would correspond to the upper 30% of the load cycle. Additionally this two parameters were used for calculating the kernel density estimation. It can be seen that a lot of AE emissions occurred at lower loads. At higher loads they mainly occurred when the crack was propagating.

39 5 RESULTS AND DISCUSSION 31 Figure 31: Kernel density estimation of AE signals - Sample 1. This evidences the importance of considering the appropriated range. A too wide range might include the noise from the crack closure and a too narrow one might exclude crucial features related to crack growth. For this composite material, 60% of the upper load range seems to be appropriate to reduce AE data without losing critical information. From now on, the e.g. 60% of the upper load cycle and the corresponding AE signals are simply referred to as 60%. Figure 32 - Figure 34 represent 60% of the AE counts and the crack length in function of the number of cycles. For Sample 1 (Figure 32) a drastic reduction of AE counts can be observed. At the beginning of the test, when the crack is growing, the amount of AE data varies only slightly with respect to 100%. In this region the AE counts are of one order of magnitude more than at the end when the crack is arrested. For Sample 2 (Figure 33) the reduction of AE data is more modest. The most obvious reduction is in the middle of Test 2.2. This is in agreement with the crack growth, as in this part the crack slowed down in front of the first interface. Surprisingly, the number of AE counts reduced also at the end of Test 2.3, where the crack growth accelerated before fracture. When analysing the AE data just before fracture, it is revealed that the most AE signals were released at very low loads. For this reason it might be necessary to use more than 60% for performing an accurate crack estimation. Sample 3 (Figure 34) behaves completely different. Compared to 100%, only an insignificant variation can be observed, because the AE signals occurred near the peak load. This different behaviour could confirm a different fracture mode between Sample 2 and 3.

40 5 RESULTS AND DISCUSSION 32 Figure 32: AE counts (60%) and crack length in function of the number of cycles - Sample 1. Figure 33: AE counts (60%) and crack length in function of the number of cycles - Sample 2.

41 5 RESULTS AND DISCUSSION 33 Figure 34: AE counts (60%) and crack length in function of the number of cycles - Sample Crack length estimation Equation (3) establishes that the AE emission rate is related to the crack growth rate. Figure 35 illustrates AE counts/cycle and the crack growth rate in function of K for Sample 2. It is important to notice that it represents 100% of the AE. Only with this large range it was possible to capture enough AE data for describing accurately the last part of the test. Looking at the overall trend of the curve it can be observed that it follows the one from the crack growth rate. By studying the characteristics of the AE emission rate it is possible to characterise the fatigue crack growth and subsequently estimate the crack length while it propagates. Figure 35: AE counts/cycle (100%) and crack growth rate in function of K Sample 2. In this work the material properties related to fatigue are not known. Therefore it is

42 5 RESULTS AND DISCUSSION 34 necessary to extract first the parameters C 4 and Φ: ( ) Φ N da = C 4 (5) dn This was done by analysing more in detail the crack growth and the AE emission rate. Figure 36 shows the same graph as in Figure 35. However only two segments of each curve are emphasised; the whole segment of Test 2.1 and the initial one of Test 2.2. Dividing the graph regarding the stress values might give more accurate results for a subsequent crack length estimation. Additionally, power trend lines are used to approximate each segment. By doing so it is possible to express the relation between the crack growth and the AE emission rate related to K. Figure 36: Approximation with power trend lines of AE counts/cycle (100%) and crack growth rate in function of K Sample 2. The first segment can be approximated with the following relations: da dn = K N = K By substituting, the following expression with both parameters is obtained. Subsequently when rewriting this expression it is possible to obtain the crack growth rate in function of the AE emission rate. N = ( da dn ) 3.13 ( ) da dn = N 1/3.13 (6)

43 5 RESULTS AND DISCUSSION 35 The same can be done for the second segment. da dn = K N = K ) 0.64 ( N = da dn ( ) da dn = N 1/0.64 (7) With equation (6) and (7) the crack length estimation was performed. While the first one was used to estimate the crack growth during Test 2.1, the second one was used from the beginning of Test 2.2 until the failure of the sample. The crack increment in mm for a specific number of cycles was successively calculated: a = da number of cycles 1, 000 dn Knowing that the notch was about 3 mm deep for all the samples the crack length could be estimated. The results from Sample 2 are presented in Figure 37. The blue data on the graph represent the crack length measured by the resistive crack gauges. The orange ones refer to the crack length estimation made by using AE. It was found that the crack length estimation is correlated to the crack length measurement. Even though it does not follow exactly the crack length measurement, the main characteristics of crack growth are clearly evident. It can be seen that both values differ more at higher numbers of cycles. The maximum difference is just above 2 mm, which corresponds to an error of about 14%. This could be influenced by several factors. As 100% of the AE data were used, crack closure noise should be captured what could explain the continuous overreading of the crack length estimation. Furthermore, Berkovits and Fang [20] mentioned the high amount of AE signals at the beginning of each test, justified by the initial yielding of the material. This period is followed by an absence of AE signals before they regain intensity at crack initiation. However, in this study a notch was already machined into the specimens and so it does not seem to significantly influence the crack length estimation. Moreover approximations made during the data processing and finally calculating the indefinite parameters contribute to a certain inaccuracy. This quantity although is difficult to quantify. For further studies it is essential to analyse the AE emission during different tests with changing parameters, as stress range, stress level and bending frequency. Additionally it is vital to evaluate the optimum set up parameter of the AE system, for instance threshold and preamplifier values and sensors position.

44 5 RESULTS AND DISCUSSION 36 Figure 37: Crack length estimation - Sample 2. For completeness the results of the crack length estimation of Sample 1 and 3 is illustrated in Figure 38 and Figure 39. The procedure was identical as for Sample 2 and is not described further. For Sample 1 the range had to be reduced to 30% to obtain reasonable results. The results from Sample 3 are obtained by using 60% of the AE data. The parameters C 4 and Φ are not constant for all the specimens. This indicates their dependence not only on the material but also from the individual conditions.

45 5 RESULTS AND DISCUSSION 37 Figure 38: Crack length estimation - Sample 1. Figure 39: Crack length estimation - Sample 3.

46 5 RESULTS AND DISCUSSION Analysis of the crack path For supporting the evaluated crack growth behaviour, the crack paths of the three samples were analysed. Figure 40 - Figure 41 illustrate the segmented samples after all tests were performed. When possible the crack path was observed with the optical microscope before fracture occurred. The white horizontal lines are the resistor strands of the resistive crack gauge. Sample 1 (Figure 40) did not fail and without microscope the crack is hardly visible. The micrograph shows the crack, which propagated until reaching the first interface. The crack grew fairly straight and no branching was detected. This could indicate that in this section no fibre, which would have deviated the crack, was present. Figure 41 gives a good example of the cracking behaviour in front of the interface. The micrograph presents the crack on Sample 2 before the last test was performed on it. The crack was deviated by more than 60 from its original crack path and grew along the interface. Additionally crack branching is clearly visible. In agreement with the information from section 3 the fibres imposed resistance to the crack growth. For Sample 3 (Figure 42) no micrograph, showing relevant information, could be produced. However it can be seen that the fracture mode is different compared to Sample 2. The reason for this might be the aged conditions of Sample 3. It seems that the stress level was too high for this conditions. Furthermore no effect of the mesh was perceptible.

47 5 RESULTS AND DISCUSSION 39 Figure 40: Sample 1 (segmented) after test and micrograph of the crack.

48 5 RESULTS AND DISCUSSION 40 Figure 41: Sample 2 (segmented) after failure and micrograph of the crack after Test 2.2.

49 5 RESULTS AND DISCUSSION 41 Figure 42: Sample 3 after failure.