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4 STRUCTURAL HEALTH MONITORING APPROACH IN STRESS STRAIN ANALYSIS OF COMPOSITE BASED PIPELINE REPAIR 4.1 Introduction As discussed in Chapter 3, the first approach in understanding the relationship between the stress strain concentrations and distributions of the pipe that contains a blunt defect is to examine it numerically using finite element analysis (FEA). The behaviour of the blunt defect before and after the composite repair was studied thoroughly and it was understood that more complex mathematical equations would need to be established if the blunt defect behaviour had to be studied analytically. Chapter 3 concludes that this numerical approach has proved that the integrity of bonding between the reinforced material (i.e. steel substrate) and reinforcing material (i.e. composite) can be analysed efficiently in terms of stress and strain distributions. However, the most important issue that has to be addressed in this chapter is how these numerical results that have been discussed in the earlier chapter are validated. It is known that the finite element (FE) is a numerical technique that finds only approximate solutions of partial differential equations (PDEs) as well as of integral equations. Inevitably, they are subject to round-off error and discretization error, as explained in Chapter 2. Although these errors can be reduced by the convergence study, the reliability of data is yet to be proved analytically or experimentally. Therefore, the most convincing way to tackle this issue was to carry out relevant experiments, not only for the purpose of validation but also to overcome any possible deficiencies in the FE method. In fact, reliable experimental data cannot be sensibly obtained if a proper methodology is not carried out first, especially in the pipeline-based composite repair. In this chapter, the temperature and pressure test rig that was able to provide a practical platform in the acquisition of strain data is presented. This second approach, which was based on a laboratory experiment, has provided an insight into the possibility of performing structural health monitoring on actual site conditions in the future. Before 128
this second approach (i.e. the experiment) is discussed in depth, it is important to highlight some fundamentals of strain measurement using electrical strain gauges and how the data were acquired by using one of the versatile and robust systems (i.e. the National Instrument CompactRio data acquisition system). These will be explained in the following section. 4.2 Data acquisition of Composite-based Pipeline Repair 4.2.1 Introduction In this data acquisition of the composite-based pipeline repair, several sensors and instruments involved. Basically, the strain gauges, sometimes called electrical conversion elements or converters, were used as the main sensors because they were able to translate small changes in dimension into an equivalent change of resistance as explained by Weymouth et al. (1979) and the Georgia Institute of Technology (2010). In other words, these sensors were able to convert the physical parameters into an electrical signal. Details of these strain gauges will be discussed further in the next section. For more reliable strain gauge measurements, proper selections of signal conditioning are equally important and required in this Study. Often, these strain gauge signal conditioners include amplifiers to boost the sensor signal level so that the measurement resolution (that has been converted from analogue to digital values) can be increased and signal-to-noise ratios can be improved (National Instruments Measurement, 2001). NI CompactRio which is a reconfigurable embedded control and acquisition system was one of the main and important instruments used in this Study. This rugged hardware includes I/O modules, reconfigurable field-programmable gate array (FPGA) chassis and real-time controller, and is programmed with Labview graphical software as referred to by National Instruments Measurement (2011). 129
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CRANFIELD UNIVERSITY MAHADI ABD MUR
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ABSTRACT One of the most common pro
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TABLE OF CONTENTS ABSTRACT ........
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3.7.1 Introduction ................
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5.6 Summary and Conclusions .......
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Figure 3.1: Schematic diagram of th
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Figure 5.4: The average temperature
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NOMENCLATURES ACFM Alternating Curr
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1 INTRODUCTION One of the most comm
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1.1 Objectives Knowing this backgro
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The methodology of this integrated
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Chapter 6 contains the summary and
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period of the major part of the exi
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Figure 2.2: Reported interest in de
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Figure 2.4: Dent damage caused by v
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presented current practices, recent
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Energy Workforce Sdn Bhd (2011) cla
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available provides real time detect
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2.3.3 Reliability Analysis of Infor
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Figure 2.9: Pipeline failure probab
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2.3.3.1 NDT Reliability and POD cur
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increase in the yield limit of stee
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the SCC assessment in their integri
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Manufacturers such as Walkers Techn
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Company L.P, 2005); Aquawrap ® pro
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monitoring, inspection, and damage
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2.6.2 Aims of Structural Health Mon
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Figure 2.16: Application fields and
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egistered by the piezoelectric sens
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discretization error. Round-off err
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notches and Neuber‘s is better fo
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maximum local stress at discontinui
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De Carvalho (2005) concludes that t
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accurate simulation of loading espe
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Based on the above facts, the opera
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3 FINITE ELEMENT ANALYSIS (FEA) IN
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Figure 3.2: Schematic diagram of th
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In this modelling work (i.e. compos
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This partition toolset also helps u
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Figure 3.6: Mesh control using Swee
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Figure 3.7: Schematic representatio
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discretization. Therefore, in this
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According to Staten et al. (2010b),
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3.5 The influence of pressure on th
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each pressure value remains constan
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Axial Stress, σa (S22) was referre
Page 97 and 98: Figure 3.14 shows a graph of analyt
Page 99 and 100: the notch defect is found to be in
Page 101 and 102: One of the contributions of this st
Page 103 and 104: Table 3.4: Convergence tests on var
Page 105 and 106: Figures 3.16 and 3.17 show that the
Page 107 and 108: Figure 3.20 shows that as the relat
Page 109 and 110: 3.7.4 Concluding Remarks A biaxial
Page 111 and 112: yarns change and lateral contact be
Page 113 and 114: For predicting E2 and Gl2, a number
Page 115 and 116: Where: Ar = weight of one sheet of
Page 117 and 118: Where; The Stiffness matrix is trad
Page 119 and 120: simulations for the hoop strain at
Page 121 and 122: Figure 3.24: Finding the hoop stres
Page 123 and 124: Table 3.8: The effect of repair len
Page 125 and 126: four up to 18 layers. In this study
Page 127 and 128: hoop and axial stress concentration
Page 129 and 130: Table 3.11: Predicted Elastic Const
Page 131 and 132: Table 3.13: Axial Stress v/s L/W ra
Page 133 and 134: Hoop Stress (MPa) Figure 3.3: Hoop
Page 135 and 136: However, Frost (2008) and Alexander
Page 137 and 138: Table 3.17: Ratio of Axial Stress N
Page 139 and 140: axial load (e.g. buried pipelines t
Page 141 and 142: 3.10 Numerical Strain Analysis of C
Page 143 and 144: Figure 3.36 shows the contours befo
Page 145 and 146: Stress Concentration Factor 2 1.8 1
Page 147: In fact, for Notch 40 with 18 plies
Page 151 and 152: 4.2.2 Strain Gauge Selection and Cr
Page 153 and 154: Finally, a method used to calculate
Page 155 and 156: Where, and are the maximum and mini
Page 157 and 158: should be between 20 and 28 bar and
Page 159 and 160: welded weld neck flange at both end
Page 161 and 162: Figure 4.7: Sensor and heating elem
Page 163 and 164: Figure 4.9: A summary of data acqui
Page 165 and 166: One of the objectives of doing this
Page 167 and 168: Figure 4.14: A schematic diagram of
Page 169 and 170: Table 4.1: Strain gauge readings at
Page 171 and 172: microstrain 3.00E-04 2.50E-04 2.00E
Page 173 and 174: However, the axial load transfer is
Page 175 and 176: Mircostrain 500 450 400 350 300 250
Page 177 and 178: Since the defect is not a flat notc
Page 179 and 180: Again, the epoxy resin plays a sign
Page 181 and 182: Table 4.4: Study at the defect area
Page 187 and 188: 14.25% in hoop strain and 23.5% in
Page 189 and 190: consideration for the selection of
Page 191 and 192: 5.4 Methodology of Thermal Expansio
Page 193 and 194: Figure 5.1: Some preventive measure
Page 195 and 196: 5.4.1 The Fundamentals of the Therm
Page 197 and 198: 5.5 Analysis of Results 5.5.1 The t
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Thermal Output (strain ) 0.0002 0.0
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(Strain ,ε) Figure 5.12: Coefficie
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(Strain ,ε) 0.0002 0.00018 0.00016
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Table 5.1: The strain readings afte
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maximum shear strain increase as th
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The above results show that shear s
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shear strains becomes more stable a
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for future safe design and operatio
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has been fully cured. Poor surface
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6.3 Primary PhD Achievements The ea
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In Chapter 5, the CTE was determine
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ASM International (2002), "Thermal
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Bucinell, R. B. (2001), Calculating
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Proceedings of OMAE'01 20th Interna
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Greenwood, R. (2002), UKOPA Pipelin
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Kotrechko, S. A., Krasovskii, A. Y.
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Mousavi, S. E., Xiao, H. and Sukuma
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Raju, I. S. and Newman, J. C. (1986
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Tennyson, R. C. and Mufti, A. A. (2
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Xue, L., Widera, G. E. O. and Sang,
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General Technical Specifications: T
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Photos of the Design and Build of t
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Composite Installation Process usin
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APPENDIX 3 - STRAIN GAUGE INSTALLAT
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Figure 7: Mylar tape was stuck onto
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Figure 19: Repeating the above proc
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2) Electrical Insulation Test Resul
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