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Simola et al. (2009) present several project studies with the purpose of investigating reasonable and practical requirements that should be set for assumptions about the accuracy of how inspection reliability is quantified in terms of POD. Their pilot studies resulted in a set of recommendations related to the quantification of inspection qualification. In addition, if defect growth can be modelled further, it is possible to link inspection qualification results, risk reduction and inspection intervals. According to Reboud et al. (2010), POD curves relate the detectability of a flaw to its size. For a specific inspection method, the POD expresses the probability that it is a flaw of a certain size that will be detected, assuming this flaw is actually present in the inspected component. Traditional POD curves are estimated from experimental data, the large amount of data required makes the determination of a reliable POD curve very expensive and time-consuming if there is a lack of support and contribution by the relevant organisations as addressed by Brennan et al. (2009) earlier. One of the solutions is using a simulation approach. Reboud et al. (2010) have used CIVA, a software for statistical tools, enabling POD computations to bring a cheaper and faster complement to POD studies. These simulation-based POD calculations have been recently introduced in the NDE community as reported by Jenson et al. (2009). 2.4 Maintenance Strategy Maintenance strategy is one of the important sub-components of the life extension programme which is under the pipeline integrity system as referred to in Figure 1.2 in Chapter 1. There is the possibility of ending up with a catastrophic disaster caused by ageing and/or other factors if this strategy is not properly carried out by operators. An example of damage or disaster due to ageing has been studied by Kotrechko et al. (2002). They conclude that from their low temperature testing results, the long- term operation does not affect the microscopic cleavage resistance (minimum brittle- fracture stress) of steel and has no influence on the strain-hardening exponent. But the 26
increase in the yield limit of steel caused by ageing is the main cause of the drop in its toughness after 30 years of operation. However, the risk of this damage due to lack of maintenance strategy should be proved by statistical model. Hence, Thodi et al. (2008) define risk as the product of probability of failure of an undesirable event and its likely consequences. The main steps in risk-based integrity modelling are the estimation of the probability of structural failure and its consequences. In their study, the maintenance plan or strategy has also been included in their consequence analysis (Thodi et al. (2008). In order to make sure the maintenance strategy is successful, operators and protective system providers must work together. Gunalton et al. (2008) highlight that TOTAL is working closely with manufacturers to improve the characteristics of repair systems and to complete them by additional components if needed. The gap between the performance of the existing systems and TOTAL‘s requirements are evaluated. One example of a very successful Life Extension programme is that of the Composite Hull Embedded Sensor System (CHESS) as highlighted by Todd et al. (2007). CHESS is used to measure global bending in ship hulls, local strain in selected areas and strain in the waterjet propulsion system. Fibre Bragg Grating (FBG) sensors are used and Finite Element Method (FEM) analysis is performed in their life extension programme. In pipeline repair maintenance, there has been the established development of a high strength, lightweight, monitored reinforced thermoplastic pipe called a Smart Pipe that can be used for the rehabilitation of an existing pipeline, or as a stand alone replacement (Smart Pipe Company, 2008). Qinetic (2006) has also developed OptaSense distributed acoustic sensing that can detect threats before any damage occurs such as combating third party interference, condition monitoring, leak detection and pig monitoring etc. In order to address single critical integrity threats found at several locations of a pipeline system, Scrivner and Alexander (2008) have developed an Engineering-Based Integrity Management Program (EB-IMP). The uniqueness of this development is the integration of actual pipeline data coupled with analysis and testing 27
Page 1: CRANFIELD UNIVERSITY MAHADI ABD MUR
Page 4 and 5: ABSTRACT One of the most common pro
Page 7 and 8: TABLE OF CONTENTS ABSTRACT ........
Page 9 and 10: 3.7.1 Introduction ................
Page 11: 5.6 Summary and Conclusions .......
Page 14 and 15: Figure 3.1: Schematic diagram of th
Page 16 and 17: Figure 5.4: The average temperature
Page 18 and 19: NOMENCLATURES ACFM Alternating Curr
Page 21 and 22: 1 INTRODUCTION One of the most comm
Page 23 and 24: 1.1 Objectives Knowing this backgro
Page 25 and 26: The methodology of this integrated
Page 27 and 28: Chapter 6 contains the summary and
Page 29 and 30: period of the major part of the exi
Page 31 and 32: Figure 2.2: Reported interest in de
Page 33 and 34: Figure 2.4: Dent damage caused by v
Page 35 and 36: presented current practices, recent
Page 37 and 38: Energy Workforce Sdn Bhd (2011) cla
Page 39 and 40: available provides real time detect
Page 41 and 42: 2.3.3 Reliability Analysis of Infor
Page 43 and 44: Figure 2.9: Pipeline failure probab
Page 45: 2.3.3.1 NDT Reliability and POD cur
Page 49 and 50: the SCC assessment in their integri
Page 51 and 52: Manufacturers such as Walkers Techn
Page 53 and 54: Company L.P, 2005); Aquawrap ® pro
Page 55 and 56: monitoring, inspection, and damage
Page 57 and 58: 2.6.2 Aims of Structural Health Mon
Page 59 and 60: Figure 2.16: Application fields and
Page 61 and 62: egistered by the piezoelectric sens
Page 63 and 64: discretization error. Round-off err
Page 65 and 66: notches and Neuber‘s is better fo
Page 67 and 68: maximum local stress at discontinui
Page 69 and 70: De Carvalho (2005) concludes that t
Page 71 and 72: accurate simulation of loading espe
Page 73 and 74: Based on the above facts, the opera
Page 75 and 76: 3 FINITE ELEMENT ANALYSIS (FEA) IN
Page 77 and 78: Figure 3.2: Schematic diagram of th
Page 79 and 80: In this modelling work (i.e. compos
Page 81 and 82: This partition toolset also helps u
Page 83 and 84: Figure 3.6: Mesh control using Swee
Page 85 and 86: Figure 3.7: Schematic representatio
Page 87 and 88: discretization. Therefore, in this
Page 89 and 90: According to Staten et al. (2010b),
Page 91 and 92: 3.5 The influence of pressure on th
Page 93 and 94: each pressure value remains constan
Page 95 and 96: Axial Stress, σa (S22) was referre
Page 97 and 98:
Figure 3.14 shows a graph of analyt
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the notch defect is found to be in
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One of the contributions of this st
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Table 3.4: Convergence tests on var
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Figures 3.16 and 3.17 show that the
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Figure 3.20 shows that as the relat
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3.7.4 Concluding Remarks A biaxial
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yarns change and lateral contact be
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For predicting E2 and Gl2, a number
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Where: Ar = weight of one sheet of
Page 117 and 118:
Where; The Stiffness matrix is trad
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simulations for the hoop strain at
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Figure 3.24: Finding the hoop stres
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Table 3.8: The effect of repair len
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four up to 18 layers. In this study
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hoop and axial stress concentration
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Table 3.11: Predicted Elastic Const
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Table 3.13: Axial Stress v/s L/W ra
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Hoop Stress (MPa) Figure 3.3: Hoop
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However, Frost (2008) and Alexander
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Table 3.17: Ratio of Axial Stress N
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axial load (e.g. buried pipelines t
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3.10 Numerical Strain Analysis of C
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Figure 3.36 shows the contours befo
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Stress Concentration Factor 2 1.8 1
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In fact, for Notch 40 with 18 plies
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this second approach (i.e. the expe
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4.2.2 Strain Gauge Selection and Cr
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Finally, a method used to calculate
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Where, and are the maximum and mini
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should be between 20 and 28 bar and
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welded weld neck flange at both end
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Figure 4.7: Sensor and heating elem
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Figure 4.9: A summary of data acqui
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One of the objectives of doing this
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Figure 4.14: A schematic diagram of
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Table 4.1: Strain gauge readings at
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microstrain 3.00E-04 2.50E-04 2.00E
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However, the axial load transfer is
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Mircostrain 500 450 400 350 300 250
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Since the defect is not a flat notc
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Again, the epoxy resin plays a sign
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Table 4.4: Study at the defect area
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Mircostrain 300 250 200 150 100 50
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Mircostrain 600 500 400 300 200 100
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14.25% in hoop strain and 23.5% in
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consideration for the selection of
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5.4 Methodology of Thermal Expansio
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Figure 5.1: Some preventive measure
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5.4.1 The Fundamentals of the Therm
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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
Page 205 and 206:
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
Page 217 and 218:
6.3 Primary PhD Achievements The ea
Page 219 and 220:
In Chapter 5, the CTE was determine
Page 221 and 222:
ASM International (2002), "Thermal
Page 223 and 224:
Bucinell, R. B. (2001), Calculating
Page 225 and 226:
Proceedings of OMAE'01 20th Interna
Page 227 and 228:
Greenwood, R. (2002), UKOPA Pipelin
Page 229 and 230:
Kotrechko, S. A., Krasovskii, A. Y.
Page 231 and 232:
Mousavi, S. E., Xiao, H. and Sukuma
Page 233 and 234:
Raju, I. S. and Newman, J. C. (1986
Page 235 and 236:
Tennyson, R. C. and Mufti, A. A. (2
Page 237 and 238:
Xue, L., Widera, G. E. O. and Sang,
Page 239 and 240:
General Technical Specifications: T
Page 241 and 242:
Photos of the Design and Build of t
Page 243 and 244:
Composite Installation Process usin
Page 245 and 246:
APPENDIX 3 - STRAIN GAUGE INSTALLAT
Page 247 and 248:
Figure 7: Mylar tape was stuck onto
Page 249 and 250:
Figure 19: Repeating the above proc
Page 251:
2) Electrical Insulation Test Resul
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