Risk Analysis and Evaluation of Strategies for Extending the Life of Large Diameter Pipelines

Transcription

1 C. L. Brito / Instituto Superior Técnico (23) Risk Analysis and Evaluation of Strategies for Extending the Life of Large Diameter Pipelines Carlos André Lima Brito Instituto Superior Técnico, Lisbon University, Av. Rovisco Pais, 49- Lisbon, Portugal Summary The condition rating and the deterioration modeling of large-diameter buried pipes is a challenging undertaking, because low rates of failure and high costs of inspection result in a severe scarcity of necessary data. The failure risk of these pipes must be evaluated and managed, as the failure of such pipes can be disastrous. Water utilities are generally very resistant to taking these pipes out of service for inspection because transmission systems often have no built-in redundancy to accommodate the loss of service. Consequently, the management of their failure risk requires a deterioration model to enable the forecast of the asset condition as well as the possibility of its failure. This document was conducted to identify and characterize the state of art for structural condition assessment of water mains. The broad definition of structural condition assessment of water mains encompasses physical modeling of pipe in the soil, understanding of pipe failure modes, empirical/statistical modeling of historical failures, and inspection of a pipe to discern distress indicator, interpretation of distress indicators into pipe condition rating and modeling deterioration to forecast future failures. Statistical models can be an important tool to the utilities, contributing to a surgical planning of inspections and intervention. Among the statistical models, the Markov chain model can be particularly useful for the management of the facilities in the study because their peculiarities allow obtaining a forecast of the development of condition state, based on only the state of a given condition instant. To apply the probabilistic model in question is necessary to have a pre-classification system and allocation condition states of large diameter pipes, which system was also been developed in this document. As a case study is applied a Markov model to records of inspections to pipelines operated by EPAL. The study aims at the development and analysis of strategies for maintenance and life extension of pipelines. This investigation theme is considered promising, providing a strong base for develops a financial model, which applied with the degradation model, may be capable to providing an integrated approach for optimizing intervention strategies in water mains. - -

2 C. L. Brito / Instituto Superior Técnico (23) Keywords: Condition assessment of large water mains; Markovian chain model; risk analysis; Lifetime extension of pipelines for water supply. Background Technologies for condition assessment of water mains The best mode for investigation the condition of water distribution systems is based on a two-phase method. The first step involves a preliminary assessment of the structural condition, hydraulic capacity, leakage and water quality on a system-wide basis using data that should be collected by utilities. The second step involves a more detailed investigation of specific problems. Data used in case study are based on visual inspections. Factors that contribute to water mains deterioration Many factors can affect the rate of deterioration corresponding to water distribution systems. These factors can be divided into three groups; Physical; Environmental; Operational; Structural failure of water mains Water mains typically break when the extent of degradation is sufficient that the main is no longer able to resist the forces acting on it. Recent works indicates that failure often takes place in multiple stages rather than in a single episode. Next table summarizes the structural failure modes for each of the common adductor materials. Water Main Material Structural Failure Modes Cast Iron Ductil Iron Circumferential and Longitudinal breaks; split bell; corrosion through holes; bell shear. Corrosion through holes. Concrete Pressure Pipe Abestos Cement Mat experience ruptures due to loss of prestressing upon multiple wire failure. Circumferential breaks; Longitudinal splits

3 C. L. Brito / Instituto Superior Técnico (23) High Density Polyethelene Joint imperfections; mechanical degradation from improper installation methods. Steel Corrosion through holes, large diameter pipes are susceptible to collapse Longitudinal breaks due to excessive PVC mechanical stress; Susceptible to impact failure in extreme cold condition. Water mains deterioration models Managing the failure risk of infrastructure assets is improved with the use of a deterioration model to enable the forecast of the asset condition. Deterioration models of water mains can be classified into two main categories; physical models and statistical models. Physical models are scientifically more robust and wildly applicable but they are limited by existing knowledge and available date. In contrast, the statistical models can be applied with various levels of input data. The Markovian process, used in case study, is a statistical model-probabilistic model. Markovian process Markovian deterioration process The proposed Markov deterioration model is especially suited for assets which data are scarce. Data scarcity results from the fact that most often these adductors are difficult to access and expensive to inspect. The risk needs to be evaluated and managed because the failure of such pipes can have disastrous consequences. The Markovian deterioration process requires that condition of the deteriorating system be encoded as an ordinal condition state. The condition assessment of a large buried pipe comprises two steps. First need to inspect the pipe using some techniques and after is necessary to interpret these distress indicators to determine the condition state of the pipe. The deterioration process is modeled as a flow of membership from one condition state to the next lower condition state. At least two consecutive observations of the asset condition are needed in order to validate the proposed model. The Markovian process is a stochastic process with a markovian property

4 C. L. Brito / Instituto Superior Técnico (23) Markovian property A stochastic process is said to have the Markovian property if : P{ X t+ = j I X = k,x = k,,x t- = k t-, X t =i}= P{ X t+ =j I X t =i} [] for t=, and every sequence I,j, k, k t- This Markovian property says that the condition probability of any future event, given any past event and the present state, is independent of the past event and depends only upon the present state. Transition probabilities and stationary transition probabilities The conditional probabilities P {X t+ =j I X t =i} for a Markov chain are called transition probabilities. Consider the three points in time: t =r is a past time t =s is the current time t`=s+t is t time units into the future If the transition probabilities are independent of s, so that P{X(t+s)=j I X(s) = i } = P{ X(t) =j I X()=i} [2] For all s>, they are called stationary transition probabilities. The Markovian property (with stationary transition probabilities) implies that P{T i >t+s I T i >s } = P { T i >t} [3] - 4 -

5 C. L. Brito / Instituto Superior Técnico (23) It says that the probability distribution of the remaining time until the process transtis out of a given state always is the same. The random variable is memoryless, the process forgets its history. There is only one continuous probability distribution that possesses this property the exponential distribution. Translation of pipe inspection results into condition ratings An important step towards the assessment and management of failure risk in large-diameter water mains is to observe distress indicators through scheduled inspections and translate these into condition ratings. In case study, the translation of pipe inspection results into condition ratings was made using a proposed pointscore protocol developed in this document. Weights for structural defects are assigned based on the relative consequence of each one on water mains. The proposed weights range from to 25. Inspection records, provided by EPAL, are divided in 7 meters segments, corresponding this distance to the length between conduct joints. These records were obtained based on man entry and visual inspection. Pipe condition ratings Segment total score is the sum of all defect weights. After the scores are tailed, the totals are used to rate the condition of all pipe. In this work was used a scale of 25 deduct values for condition rating and a five grade rating, where =excellent, 2=good, 3=fair, 4=poor, 5=imminent collapse. Table 2 illustrates the point score scheme of proposed protocol. Condition states Point socre < >25 Case study All data used on study has been obtained from EPAL which is a major water utility in Portugal. Data corresponding to Castelo do Bode adductor, which is the most important piece of all system and it contributes around 6% of the company s production capacity. At least two consecutive observations of the asset condition are needed in order to build the intensity matrix (Q), and apply the markovian process to obtain a deterioration model. Table 3 illustrates the sections that were inspected twice

6 C. L. Brito / Instituto Superior Técnico (23) Sections Extension (m) First inspection Second inspection ND(mm) Adutor de Castelo de Bode -Túnel de Malpique 82 April 29 November 2 8 Adutor de Castelo de Bode -Túnel do Bode 5 November 28 November 2 3 Adutor de Castelo de Bode-Túnel Zootécnica 246 Aprill 29 November 2 8 Adutor de Castelo de Bode-Túnel do vale de Santarém 88 April 29 November 2 8 Adutor de Castelo de Bode- Troço entre a V6B e Túnel da Azambuja 882 April 29 November 2 8 Next table illustrates the number of condition rating transitions between 7 meters segments. Initial state/final state Next table illustrates the sum of time intervals between observations whose initial state is i

7 C. L. Brito / Instituto Superior Técnico (23) Initial state i (years) It is then possible to calculate the Q matrix. Q= [4] [5],qij represents the probability rate of transition between consecutive states,nij the number of elements that moved from state i to state j and the sum of time intervals between observations, whose initial state is i. So, the intensity matrix is:.7.7 Q= Is necessary to know the evolution of transition probabilities, Pij, over time

8 Probabilities Probabilities PProbabilities Probabilities C. L. Brito / Instituto Superior Técnico (23) ( ) [5] Analysis was conducted for a 8 years period. Pij evolution over the time are illustrated in next figures. Knowing the Pij evolution is possible to obtain the deterioration curve of Castelo do Bode adductor.,8,6,4, Time[years] P P2 P3 P4 P5,8,6,4, Time[years] P22 P23 P24 P25,9,8,7,6,5,4,3,2, Time[years] P33 P34 P35,9,8,7,6,5,4,3,2, Time[years] P44 P45 Strategies for life extension It s important to compare various maintenance strategies, analyzing them economically and compare the quality of service. Considering that the life of a reinforced concrete pipes is about 5 years and crossing this information with Markov forecasts, it appears that the life of a pipeline initially in state ends when approximately 6% of the sections analyzed are in the condition state

9 Probabilities C. L. Brito / Instituto Superior Técnico (23) Next figure illustrates this fact.,9,8,7,6,5,4,3,2, Time[years] P5 End of life Maintenance scenarios Then are proposed and explained 4 maintenance scenarios. The adductor life ends when 6% of their extension is in fifth condition state. Maintenance scenario This scenario allows the conduct reaches the end of its useful life without performing any maintenance action, proceeding to a full replacement after 5 years. Maintenance scenario This scnenario predicts inspections in or 2 in 2 years and replacement of parts which are in the condition state 5. The new segments are in condition state 2. Maintenance scenario 2 This scenario is identical to maintenance scenario, but are replaced those segments who are in condition state 4 and 5. Maintenance scenario 3 The number of substitutions per intervention is limited to % of all segments. The new segments are in condition state 2. When reaching the end of life all the segments are replaced

10 benefít/cost benefit/cost C. L. Brito / Instituto Superior Técnico (23) Analysis of maintenance scenarios Finally it is possible to analyze and compare the various scenarios, analyzing a benefit/cost relationship. The benefit is related with risk, which is obtained analyzing the net present number of segments in condition state 5. Cost is obtained analyzing the net present value, considering various actualization rates. The following figures represent the benefit/cost value, considering inspections in and 2 in 2 years and actualization rates of 4% 6% and 8%. 2, 5,, 5,, 2 Maintenance scneraios 3 N.P.D=4% N.P.D=6% N.P.D=8% Inspections in years 2, 5,, 5,, 2 Maintenance scenraios 3 N.P.D=4% N.P.D=6% N.P.D=8% Inspections 2 in 2 years It is clear from examination of previous 2 figures that the scenario that leads to a better cost / benefit ratio is scenario, being however that causes the installation to operate with a higher risk level. - -

11 C. L. Brito / Instituto Superior Técnico (23) The scenario which concerns a poorer benefit / cost ratio is scenario 2, while still offering the lowest risk level for installation along the observed time window. Conclusions This work explored a Markov chain model to predict the deterioration suffered by conduits, serving the same prediction to perform an economic comparison and a risk analysis for all four maintenance scenarios proposed. The methodology for classification and prediction of deterioration was applied to sections of Castelo do Bode adductor, with nominal diameters equal to and greater than 8mm. Maintenance strategies proposed and analyzed do not include renewal actions, considering only the possibility of substitution. This consideration arises because the Markov process does not give indications about the type of anomalies recorded. The list of anomalies and their scores in this work lead to satisfactory results when used for classification of the conduct referred. This should not be used indiscriminately in other cases, with different diameters, materials or construction techniques. Some facts and conclusions respective the Markov Chains are presented below: Classification and prevision of condition states not consider specific causes of deterioration; For a credible prediction, the analyzed conduit must have characteristics similar to those used in the construction of the intensity matrix; The model is more reliable as more inspection intervals are considered in their construction; Since only be necessary to know the state of initial condition for obtaining a prediction of future performance, the Markov model becomes quite practical; Markovian model ignores the phase of the life cycle in which the conduct that is intended to meet the deterioration is initially; Minor repairs unregistered, made in the intervals between inspections, can induce changes in light intensity matrix obtained; Once the records are used with input from human inspections, only the apparent anomalies in the pipeline interior wall are recorded; Age,quality of the materials and the manufacturing process are factors which influence the behavior of pipes throughout its life. This factors may cause different behavior predicted by the Markov process; - -

12 C. L. Brito / Instituto Superior Técnico (23) Concern shown by utilities managers regarding the performance of the infrastructure, it is likely to arise more and more data, thus improving the performance of the Markov model. It is believed that the use of Markov chains to model the degradation of water supply systems is a promising subject. References [] Rajani,B;Kleiner, Y; Sadiq,R Translation of pipe inspection results into condition ratings using fuzzy synthetic evaluation technique. Journal of Water Supply Research and Technology. [2] WRc. (2). Drain & Sewer Systems Outside Buildings. Water Research Centre Plc, Wiltshire, UK. [3] Zheng Liu;Yehuda Kleiner and Balvant Rajani (22) Condition Assessment Technologies for Water Transmission and Distribution Systems. [4] Hillier and Lieberman.(2) Introduction to operations research