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Paper published at the Journal of Pipeline Engineering: A practical approcah to pipeline corrosion modelling: Part2 - Short-term integrity forecasting

Paper published at the Journal of Pipeline Engineering: A practical approcah to pipeline corrosion modelling: Part2 - Short-term integrity forecasting

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    • 1st Quarter, 2009 19A practical approach in pipeline corrosion modelling: Part 1 – Long-term integrity forecastingby Dr Érika S M Nicoletti* and Ricardo Dias de SouzaPetrobras Transporte SA, Rio de Janeiro, RJ, Brazil N OWADAYS, MANY MAJOR MARKETS worldwide depend upon an increasingly-ageing pipeline infrastructure to supply most energy demands. As corrosion damage accumulation is usually expected under typical pipeline service conditions, forecast metal-loss growth over time is a key element in their integrity management; but there is little industrial guidance on this issue. The current work has been undertaken aiming to provide a corrosion rate model by means of straightforward stochastic treatment of metal-loss ILI data. This first part will present a model framework regarding long-term scenarios and remaining-life predictions, based on a cost-effective pecuniary threshold for the system’s future remedial actions. The concept of local activity breaks new ground by merging two traditional approaches: the individual defect and the pipeline segment corrosion growth rates. The model’s underlying assumptions are detailed, together with its mathematical framework; an empirical balance has been established between over- and under-conservative premises, and the accuracy of the results has been considered suitable for forecasting intervals of up to 30 years. The technique provides powerful information with no need to carry out any further expensive and/or laborious analyses: the whole algorithm could be easily put into practice using commercial mathematical packages. In order to illustrate the model’s applicability, four case studies will be presented.Nomenclature H: defect odometer [m] l: maximum defect length [mm] Dt1: pipeline service life under original operating lf: defect forecast length [mm] conditions [years] LSEGi: local segment length [m] Dt2: pipeline service life under posterior operating N: total number of active corrosion sites conditions [years] n: vicinity parameter Dtc: coating degradation lag [years] Ri: individual defect dimension corrosion rate [mm/ Dtf: forecasting lag [years] year] Dts: pipeline service life [years] RDi: local defect dimension corrosion rate [mm/year] sdi: forecast dimension standard deviation [mm] RDij: individual corrosion rate at a nearby defect [mm/ sRi: local depth corrosion rate standard deviation [mm] year] s: scoring factor for service condition changes d: maximum metal-loss depth [mm] w: maximum defect width [mm] Df: maximum metal-loss forecast dimension [mm] wf: defect forecast width [mm] Dj: pig-reported dimension (depth, width and length) [mm] dj: pig-reported defect depth [mm] Epig: tool measurement error [mm] (at 80% confidence level) Fh: service conditions linearization factor F OR OVER ONE hundred years pipelines have been used to transport hydrocarbons from their distant location to refineries and onwards to consumers. Many major world markets nowadays depend upon this increasingly-ageing pipeline infrastructure to supply most*Author’s contact details:tel: +55 21 3211 7264 of their energy demands. It is unfortunate that ageingemail: erika_nicoletti@petrobras.com.br adversely affects a pipeline’s integrity, and it can suffer from
    • 20 The Journal of Pipeline Engineeringmany types of damage under typical service conditions. hand, long-term scenario predictions are typically associated with the system’s economic viability forecasting (andCorrosion has historically been the greatest time-dependent estimating its remaining life); such analyses are usuallythreat to pipeline integrity. The process itself reduces the better served with accurate modelling.local metal cross-section, affecting the remaining strengthand, consequently, reducing the pipeline’s containment Despite both algorithms being developed with the aim ofcapacity in the area of the damage. incorporating them into a company’s proprietary defect- assessment software [6], they can also be easily implementedOperators can quantify corrosion in their systems through using any common commercial mathematical package.periodic metal-loss in-line inspections (ILI). Subsequently, Accordingly, both are presented in only their most simplisticthe system’s fitness-for-purpose can be assessed at each interpretations. The underlying assumptions of the models,point by carrying out damage tolerance analysis using, as and the descriptive formulations, will be described andinput, ILI data and required service conditions [1, 2]. discussed. Real cases studies will then be presented to illustrate the methodology anticipated results and overallHowever, given that pig inspections show only the state of performance, before final conclusions are given.static damage at the time of the inspection, integrityforecasting must take into account corrosion growthestimates. Furthermore, although the phenomenon of Theoretical backgroundcorrosion is widely known, a plethora of factors impact theprocess kinetics along a pipeline’s length, and the inherent The corrosion process is irreversible: once it takes place,randomness generally associated with real field conditions, metal-loss damage at a particular site can only either grow,makes its mechanistic modelling a complex task. This or remain the same over time, the latter being a sign of siterequires highly-skilled work, the difficulties of which are inactivity (and possible repassivation).often compounded by an inconvenient lack of historicaldata concerning many of the process control parameters. As time goes by, it is expected that new active sites will arise,Thus, it has become common practice to adopt an empirical while some of the existing ones will cease growing.approach, mostly based on worst-case scenarios Additionally, time-dependent defect enlargements usually(recommended practices and/or historical data) [3, 4]. slow down over time although, as a general rule,However, such procedures usually give rise to highly- deterministic approaches treat those processes as linear [7,inaccurate forecasts, particularly when dealing with long- 8]. Valor et al. [9] suggest the following should be taken intoterm scenarios. account:Indeed, the US’ Office of Pipeline Safety estimated that the • the slowing down effect: 0-10% of reduction in pastability to accurately forecast corrosion rates could save corrosion ratesAmerican pipeline companies more than US$ 100 million • the cessation of growth effect: 0-20% of the numberper year through reduced maintenance costs and accident of sites nucleated per yearavoidance [5]. • new defect nucleation: 0-65% of the number of sites nucleated per yearFortunately, ILI metal-loss mapping reflects either unknownservice condition variances and/or local electrochemical Conversely, probabilistic models often use the followingmechanism abnormalities, providing a good background, distributions in order to represent:insofar as processing past behaviour is concerned, forcorrosion-rate inferences. • nucleation time – exponential and Weibull [9, 10] • number of sites nucleated over time: Poisson [9]The current work aims to develop a simplified methodology • growth rate: gamma, log-normal, or extreme-valueto allow reasonably-accurate pipeline-integrity forecasts, distributions [6, 10, 11]chiefly by using ILI data. Two basic algorithms have beenconstructed: the first, which is presented in this paper, has The Bayesian approach and the Markovian process havebeen directed to long-term scenarios. The second part of also been widely used in probabilistic framework modellingthe methodology has targets short-term predictions, and [12-15].will be published in the second art of the paper [in the June,2009, issue of the Journal of Pipeline Engineering]. Given that metal-loss measurements reflect operational condition variations and the overall randomness of theThe main differences between the algorithms result from corrosion process itself, the proper treatment of ILI datatheir diverse application expectations. Short-term scenarios can lead to reasonable estimates of past behaviour [16-18].are usually applied in order to define reinspection intervalsand rehabilitation scopes. As operational pipeline safety In order to determine the corrosion rate, damage must beand reliability often depends on the result, conservative quantified at two different points in time. However, inapproaches have always been preferable. On the other order to avoid the usual laborious defect-matching
    • 1st Quarter, 2009 21procedures [5, 19], the current model has been adapted to – eventually – measurement bias, with a confidenceuse a single ILI data set. Also, the model has been constructed level of 80%. The mathematical framework to beunder the premise of a linear relationship existing with the presented is independently applied to the anomalyprocess’s past behaviour. Its breakthrough came with the populations located on the external and internalassumption that only adjacent metal loss represents the surfaces. New defect generation, as well as the ratecorrosion activity at each point, which will be described of cessation of defect growth, are considered to befurther below. negligible.The local corrosion activity principle • Nucleation time: defect populations are assumed to be instantaneously nucleated at the first exposure toThe authors consider it a rational assumption that all corrosive conditions.metal-loss located in close vicinity and on the same side ofthe pipe wall (external/internal) is under similar conditions • Defect growth: determined based on the pastof corrosion attack. If, regarding the variations in corrosion behaviour of local corrosion activity. The details ofactivity along a pipeline’s length, it is expected that future this premise regarding external and internal surfaceservice conditions remain similar, then future corrosion corrosion are described below.growth can be predicted based on the metal-loss anomalypopulation located in the defect neighbourhood. • Coating protection effectiveness: the coating condition is considered to be perfect at the time ofTo define the range of each defect’s environment, a vicinity pipeline commissioning. All pipeline coatingparameter must be empirically determined, using the holidays are considered to be instantaneouslyrelationship expressed in Equn 1. Each defect will also have generated after a specific coating degradation lag.its associated characteristic length, as defined by Equn 21. The protection effectiveness is assumed to be 0% at all active sites of external corrosion, and 100% in 2n+1 > = 7 (1) holiday-free regions. Water and air permeation time dependency is not taken into consideration. L Si = Hi + n − Hi − n (2) • Coating degradation lag: must be empirically definedFigure 1 illustrates the principle in a pipe section from case based on coating data history and engineering beststudy 4. All the anomalies displayed are internal metal-loss, judgment.and channelling can be clearly noted. Two anomalies havebeen arbitrarily chosen to exemplify the neighbourhood’s • Cathodic protection: is assumed to remain in adelimitation mechanism: for the purpose of illustration, steady-state condition throughout the entire servicethe lower recommended value for the vicinity parameter life of the pipeline.has been used in the figure (n = 3). Note that only axialproximity is taken into account: n anomalies immediately • Probability density functions (PDFs): defect depthup- or downstream are considered as belonging to each dimensions and corrosion rates are described bydefect’s local population. Gaussian PDFs. It is worth noting that, given that each defect’s corrosion rate is represented in termsA number of additional simplistic assumptions have been of a local average, there is a normalizing effect on themade, and a general outline of them will be given in the overall depth corrosion rate data set2.following paragraphs. • Process characterization: irreversible, evolving at a Mathematical framework constant rate, and at discrete time intervals. Corrosion rates PDFs • Defect population: ILI reported metal-loss anomalies trimmed, based on the empirical criterion defined The probability density functions should be individually in Equn 3: defined, taking account of the damage accumulated in each defect neighbourhood, according to the previously-outlined 2Et principle of local corrosion activity3. If a significant change Dj ≥ (3) in the system’s operating conditions takes place after any 1.28 where Et represents tool the measurement error and 2. Pipeline geometry, material features, and the axial and circumferential corrosion rates, have only been considered deterministically, as will be the allowable damage as a consequence.1. The parameter n should be adjusted in order to obtain an average 3. Clustering criteria should preferably be applied after a futuresegment length not exceeding 1-2 km. morphology forecast, not before.
    • 22 The Journal of Pipeline Engineeringparticular event, then a factor Fh is defined accordingly, while Equn 2 should be used to define its neighbourhoodusing Equn 4; otherwise, Fh is assumed as 14. characteristic length. Δt1 + sΔt2 Fh = (4) Future defect morphology Δt s The average dimensions of future defects can be calculatedInternal defects from Equn 6a, and Equn 6b is used to determine the associated dispersion.Individual defect growths (radial, axial, and circumferential)are determined by means of Equn 5a. The subsequent D f = D i .RLi .Δt f (6a)application of the local corrosion activity principle leads tothe determination of the corrosion rate average for thedefect population located in the adjoined region by using ⎛ E ⎞ 2 σ Df = Δt f (σ Li ) + ⎜ t ⎟ 2Equn 5b, while the dispersion is obtained from Equn 5c. (6b) ⎝ 1.28 ⎠Furthermore, the characteristic length associated with eachdefect neighbourhood (Lseg) can also be defined, as previouslydiscussed. Damage toleranceHence, each flaw on a pipe’s inside surface will have onesingle PDF representing its depth corrosion growth rate, There are a number of metal-loss assessment criteria thatwhile axial and circumferential rates, as well as its can be used to determine damage tolerance. The mostneighbourhood characteristic length, are deterministically simplistic and widely known is ASME B31.G, which onlydefined. takes into account axially-oriented corrosion defects submitted to internal pressure loading. Depending on the particular system’s damage characteristics (which can include Di Ri = (5a) circumferential- or even helically-oriented defects), or the Δt s existence of axial loads (such as those geotechnically or j=i+ n thermally induced), an appropriate criterion should be chosen to deterministically find out the maximum allowable ∑R j defect depth as a function of its forecast width and length, RLi = Fh j=i−n (5b) (2n + 1) according to Equn 7. d a = f (l f , w f ) (7) j=i+ n ∑ (R − Rj ) 2 Li σ Li = j=i−n (5c) 2n Probability of exceedance The future defect depth (df) shall not exceed its allowable depth (da) [22, 23], as represented by the limit-state functionExternal defects in Equn8:It is proposed that pipeline coating holidays are consideredstationary. Thus, circumferential and axial growth rates are d f − da < 0 (8)assumed as zero at all active sites located on the pipeline’sexternal surface. Equation 5d represents the depth growth In the current approach, df is characterized by a normalrate, considering the lag in coating degradation. distribution, while da is deterministic. This means that the probability of a pipeline exceeding the limit-state condition dj at each defect can be determined as the area on the right- Rdi = (5d) hand side of the allowable depth under the df PDF (see Δt s − Δt c Fig.2)5.Equations 5b and 5c must therefore also be applied in Economic remediation rateorder to characterize the defect’s depth corrosion rate PDF, The economic remediation rate which provides cost-effective operation must be ascertained by a pipeline’s own operator, considering each case individually. It is outside the scope of4. The scoring factor for changes in service conditions (s) should bedetermined based on historical data (coupons/probes, comparison ofmultiple ILI data or computation simulations) and engineering bestjudgment [20]. 5. Most commercial packages have standard functions to perform this.
    • 1st Quarter, 2009 23 Pipeline 1 Pipeline 2 Pipeline 3 Pipeline 4 Diameter (in) 16 14 22 16 Minimum 8.7 8.2 6.3 7.9 thickness (mm) Pipe material X60 X65 X40/46 X35 Length (km) 184 228 98 98 Service life (yr) 26 36 32 41 MAOP (kg/sqcm) 100 97 21-56* 31-41*Table 1. Constructionand operational data. *worst case scenario hydraulic simulated range.this work to accomplish a full perspective into problem, but • Pipeline 1: an onshore pipeline carrying dry gassome of the factors that must be taken into account in such since its operation began. Accumulated corrosionan analysis include: damage was slight on both the external and internal pipeline surfaces. • technical and economic viability of alternative pipeline systems, or other modes of transportation • Pipeline 2: an onshore gas pipeline that has been • the ratio between the cost of a new pipeline and the used to transport both wet and sour products. estimated maintenance costs of the existing one Accumulated internal corrosion is severe although, • the impact of a possible delivery shortage on the on the other hand, almost no external metal-loss local economy indications have been reported as a result of the • current, and possible future, economic scenarios dryness of the of region crossed by this pipeline, in the NE of Brazil.Restriction on the model’s applicability • Pipeline 3: a trunk line responsible for transportingAs the whole model is based on averaging the behaviour of all of one refinery’s crude oil supply. During itsthe local corrosion process, its application is not operational life, it endured production waterrecommended to systems where hot-spot mechanisms (such pumped through recurrently, together with someas stray current, under-coat corrosion, etc.) are significant high-BSW content product. Long shut-down periodsfeatures. were also a regular occurrence. Internal corrosion damage is quite severe and channelling damage is general. In order to meet an increase in demand, anCase studies increase in flow capacity was required. The resultant new service conditions were simulated by the worst-In order to illustrate the model’s application, four case case hydraulic scenarios, and the maximumstudies have been chosen, the input data for which is operational pressure profile was defined accordingly.summarized in Table 1. A brief introduction is given foreach, before the model results and overall performance are • Pipeline 4: an onshore line which has been used todiscussed. transport naphtha and crude oil, the latter usually Fig.1. Local corrosion activity.
    • 24 The Journal of Pipeline Engineering Fig.2. The probabilistic limit-state function. with a high BSW content. Again, production water POE threshold range of 10-4-10-5, and the economic transportation was a frequent occurrence together remediation rate specified for each case, it can be concluded with extensive shutdown periods. The whole pipeline that pipeline 3 could be safely operated for almost 30 years, has bad channelling damage, as shown in Fig.1. while pipeline 4 would be cost-effectively operational for approximately 20 years at most.Results and discussion Conversely, with the exception of pipeline 1, Figs 6 and 7The model’s output data from the four case studies are show that internal corrosion developing over 30 yearssummarized in Table 2, while Fig.3 shows the overall would be a direct threat. Pipeline 4 is not expected tonormalized local corrosion activity. Figures 4 and 5 present maintain its present use for long, while the operationalthe expected probability of exceedance for safe operations reliability of pipelines 2 and 3 will not be cost-effective for(at the required levels) without repair to the 200 most more than 20 and 10 years, respectively.critical metal-loss areas in each case study, for the next 20and 30 years, respectively. Pipeline 2 was not analysed for As a result of applying these forecasts, the company’s boardexternal corrosion, due the lack of significant indications of directors has undertaken the following:on its external surface. In view of a desirable operational Pipeline 1 Pipeline 2 Pipeline 3 Pipeline 4 Population - filtered 213 - 867 222E Vicinity parameter (n) 5 - 5 5XT Local corrosion rates GaussianE distribution parameters 0.08-0.006 - 0.053-0.004 0.80-0.006R [mm/year]NA Pecuniary remediation rate Cost-effective coating repairs 50 - 100 100L number Remaining life Expected under > 30 - 30 20 historic conditions [years] Population - filtered 337 10,370 50,325 23240I Vicinity parameter (n) 5 10 20 15NT Local corrosion rates GaussianE 0.065-0.008 0.080-0.006 0.045-0.003 0.081-0.007 distribution parametersRN Pecuniary remediation rateA Cost-effective coating repairs 40 80 80 50L number Remaining life Based under Table 2. Modelling 30 15-20 10 5 historic conditions [years] parameters and output.
    • 1st Quarter, 2009 25 00052 00002 0 0 0 51 0 0 0 01 0005 0 2 3 0, 0 6 3 0, 0 0 4 0, 0 4 4 0, 0 8 4 0, 0 2 5 0, 0 6 5 0, 0 0 6 0, 0 4 6 0, 0 8 6 0, 0 2 7 0, 0 6 7 0, 0 mm/yearFig.3. Internal corrosion rate Local Individualhistogram for pipeline 3.Fig.4. 20-year POE forecast of theworst external metal-loss anomalies.Fig.5. 30-year POE forecast ofthe worst external metal-lossanomalies.
    • 26 The Journal of Pipeline Engineering Fig.6. 10-year POE forecast of the worst internal metal-loss anomalies. Fig.7. 20-year POE forecast of the worst internal metal-loss anomalies. • pipeline 4 was converted to specified diesel between the conceptual design and commissioning stages, transportation; mostly as consequence of the complexities concerning the • a major rehabilitation project is being carried out legal agreements with landowners through whose land the on pipeline 3, together with several mitigating actions pipeline will be routed, together with the tougher regulations (including a new strategy regarding production regarding environmental and operational issues. water); • a brand new pipeline is under construction to Pipeline operators therefore need to forecast their systems’ replace pipeline 2 (mainly in order to supply the remaining lives with reasonable long-term accuracy. Despite local market’s forecast rising demand) while an corrosion being the major time-dependent threat to ageing alternative use for pipeline 2 is being studied. pipeline systems, there is little available guidance concerning corrosion modelling for real pipeline service conditions, and the subject remains controversial.Conclusions The current work has been developed to support theNowadays, new onshore pipeline systems must be planned operator’s long-term strategic planning, by providing awell in advance. Sometimes almost a decade can pass straightforward stochastic model to forecast the remaining
    • 1st Quarter, 2009 27life of corroded pipelines. As input data, the newly-developed 2. R.Bea et al., 2003. Reliability based fitness-for-servicemodel requires pipeline geometry and material properties, assessment of corrosion defects using different burst pressurethe worst-case scenario for operational pressure, a good- predictors and different inspection techniques. 22ndquality set of metal-loss ILI data, and also the economic International Conference on Onshore Mechanics and Arctic Engineering, June 8-13, Cancun.threshold for the system’s future remediation. The 3. NACE RP-0775. Preparation, installation, analysis andpioneering concept of local corrosion activity was interpretation of corrosion coupons in oilfield operations.introduced, and the underlying simplistic assumptions are 4. NACE SP0502, 2008. Pipeline external corrosion directdetailed together with the entire mathematical framework. assessment methodology.The definitions and roles of the empirical parameters have 5. J.M.Race, S.J.Dawson, L.Stanley, and S.Kariyawasam, 2006.also been described. Predicting corrosion rates for onshore oil and gas pipelines. International Pipeline Conference, Calgary.A balance has been established between over- and under- 6. S.B.Cunha, A.P.F.Souza, E.S.M.Nicoletti, and L.D.Aguiar,conservative assumptions, and the model had been 2006. A risk-based inspection methodology to optimize in- line inspection programs. The Journal of Pipeline Integrity,considered suitable for forecasting periods of up to 30 pp133-144.years. Its algorithm is set out in detail and it can easily be 7. M.Ahammed, 1998. Probabilistic estimation of remainingimplemented using standard commercial mathematical life of a pipeline in the presence of active corrosion defects.packages. International Journal of Pressure Vessels and Piping, 75, pp321- 329The technique provides powerful information with no 8. S.L.Fenyvesi, H.Lu, and T.R.Jack, 2004. Prediction ofneed for further expensive or laborious analyses. The use of corrosion defect growth on operating pipeline. Proc.the model has already proved to be particularly relevant to International Pipeline Conference, October 4 - 8, Calgary,forecasting critical problems long before they present any Canada. 9. A.Valor, F.Caleyo, L.Alfonso, D.Rivas, and J.M.Hallen, 2007.real threat. The model has also been used to give rise to Stochastic modeling of pitting corrosion: a new model foractive mitigation planning, such as a review of inhibitor initiation and growth of multiple corrosion pits. Corrosionstrategy and definition of the scope of coating rehabilitation Science, 49, pp559–579.projects. 10. A.Ainouche, 2006. Future integrity management strategy of a gas pipeline using Bayesian risk analysis. 23rd World GasAdditionally, if more-sophisticated mathematical packages Conference, Amsterdam.are available, the model could be easily adapted to 11. P.J.Laycock and P.A.Scarf. Exceedances, extremes,incorporate further refinements, incuding: extrapolation and order statistics for pits, pitting and other localized corrosion phenomena. Corrosion Science, 35. no 1-4, pp135-145, 193. • non-Gaussian behaviour (for which an automatic 12. J.L.Alamilla and E.Sosa, 2008. Stochastic modelling of best-fitting-distribution tool is required) corrosion damage propagation in active sites from field inspection data. Corrosion Science, 50, pp1811–1819. • full limit-state approach: pipeline geometry and 13. J.L.Alamilla, D.De Leon, and O.Flores, 2005. Reliability material properties could also be considered based integrity assessment of steel pipelines under corrosion. probabilistically (if convolution integrals can be Corrosion Engineering, Science and Technology, 40, 1. easily solved) [2, 10, 24] 14. S.A.Timashev, 2003. Updating pipeline remaining life through in-line inspection. International Pipeline Pigging • any specifics of a system’s history could be taken Conference, Houston. 15. S.A.Timashev et al., 2008. Markov description of corrosion into consideration by making the necessary defect growth and its application to reliability based inspection adjustments to the model’s premises and and maintenance of pipelines. Proc. 7th International Pipeline assumptions. Conference, Calgary. 16. G.Desjardins, 2002. Optimized pipeline repair and inspection planning using in-line inspection data. Pipeline Pigging,Acknowledgments Integrity Assessment, and Repair Conference, Houston. 17. B.Gu, R.Kania, S.Sharma, and M.Gao, 2002. Approach toThe authors thank Petrobras Transporte SA for permission assessment of corrosion growth in pipelines. 4th Internationalto publish this paper, and their colleagues Dr Sérgio Pipeline Conference, Calgary. 18. G.Desjardins, 2001. Predicting corrosion rates and futureCunha, Carlos Alexandre Martins, and João Hipólito de corrosion severity from in-line inspection data. MaterialsLima Oliver for many enlightening discussions and Performance, August, 40,8.contributions. 19. J.M.Race et al., 2007. Development of a predictive model for pipeline external corrosion rates. Journal of Pipeline Engineering, 6, pp15-29.References 20. R.B.Eckert and B.Cookingham, 2002. Advanced procedures for analysis of coupons used for evaluating and monitoring1. B.Gu, R.Kania, and M.Gao, 2004. Probabilistic based internal corrosion. CC Technolgies, Doublin, OH, USA. corrosion assessment for pipeline integrity. Corrosion 2004, 21. ASME B 31G. Manual for determining the remaining strength NACE International, New Orleans. of corroded pipelines.
    • 28 The Journal of Pipeline Engineering22. H.Plummer and J.M.Race, 2003. Determining pipeline 24. G.Pognonec, 2008. Predictive assessment of external corrosion growth rates. Corrosion Management, April. corrosion on transmission pipelines. 7th International23. F.Caleyo et al., 2002. A study on the reliability assessment Pipeline Conference, Calgary. methodology for pipelines with active corrosion defects. International Journal of Pressure Vessels and Piping, 79, pp77-86. Technical Writing A–Z: A Commonsense Mister Mech Mentor, Volume I: Guide to Engineering Reports and Theses, Hydraulics, Pipe Flow, Industrial HVAC & British English Edition Utility Systems by Trevor M. Young by James A. Wingate Topics include: format and content of reports and theses; Gain practical knowledge from frank, colorful cases and copyright and plagiarism; print and Internet reference cita- learn to solve mechanical problems related to hydraulics, tion; abbreviations; units and conversion factors; significant pipe flow, and industrial HVAC and utility systems with figures; mathematical notation and equations; writing styles these organized solutions to the problems involving: water TITLES OF and conventions; frequently confused words; grammatical errors and punctuation; commonsense advice on issues and steam hammer phenomena; gravity flow of liquids in pipes; siphon seals and water legs; regulating steam pres- such as getting started and holding the reader’s attention. sure drop; industrial risk insurers’ fuel gas burner piping INTEREST 2005 256 pp. Softcover ISBN: 0-7918-0237-X valve train; controlling differential air pressure of a room with respect to its surroundings; water chiller decoupled Order No. 80237X $29 (list)/$23 (ASME member) Order sets of 10 copies at a special price. Order No. 80236S $199 primary-secondary loops; pressure drop calculations of incompressible fluid flow in piping and ducts; water chillers FROM American Edition: in turndown; hydraulic loops; radiation heat transfer; and 2005 256 pp. Softcover ISBN: 0-7918-0236-1 thermal insulation. Order No. 802361 $29 (list)/$23 (ASME member) ASME PRESS Order sets of 10 copies at a special price. Order No. 80236S $199 2005 160 pp. Softcover ISBN: 0-7918-0235-3 Order No. 802353 $45 (list)/$36 (ASME member) Pipeline Operation and Maintenance: Pipeline Design and Construction: A Practical Approach A Practical Approach, Second Edition by M. Mohitpour, J. Szabo, and T. Van Hardeveld by M. Mohitpour, H. Golshan and A. Murray Covering pipeline metering, pumping, and compression, the book covers day-to-day concerns of the operators and This second edition includes updated codes and standards maintainers of the vast network of pipelines and associated information, solutions to technical problems, additional ref- equipment and facilities that deliver hydrocarbons and erences, and clarifications to the text. It offers straightfor- other products. It is a useful reference for veterans and a ward, practical techniques for pipeline design and con- training tool for novices. struction, making it an ideal professional reference, training tool, or comprehensive text. 2004 600 pp. Hardcover ISBN: 0-7918-0232-9 Order No. 802329 $125 (list)/$99 (ASME member) 2003 700 pp. Hardcover ISBN: 0-7918-0202-7 Order No. 802027 $110 (list)/$88 (ASME member) Order Now! North America: www.asme.org • Europe: www.ihsatp.com