Norhazilan Md Noor

A fuzzy analytic network process method for risk prioritization in freeway PPP projects: an Iranian case study

Risk assessment is one of the most important factors in achieving success in public-private partnership (PPP) projects. Some relationships between risks in freeway projects have been established. The occurrence of each risk can worsen the effects of others such as a negative impact of financial risks on construction risks. This paper is aimed at prioritizing significant risks in freeway PPP projects applying a fuzzy analytic network process (FANP) method for overcoming the problems of interdependencies and feedback among different risk-ranking alternatives. Data on the study have been collected through a literature review, an interview and a questionnaire survey distributed to experts in the field of freeway PPP projects. The obtained results have shown that financial, legal and political risks are the most significant groups, although improper design, changes in the value of granted lands and the termination of concession are the most important risks. The findings help with strengthening the capabilities of developing countries for risk management in freeway PPP projects.

Hybrid SWARA-COPRAS method for risk assessment in deep foundation excavation project: an Iranian case study

AbstractExisting risks in deep foundation excavation projects is a major issue in developing cities. With the rapid increase in the number of various deep foundation and excavation projects in big cities of Iran, many accidents related to deep excavation have been reported every year. These accidents affected delay and increased cost of project implementation. Therefore identification and assessment of risks of these accidents is essential. The aim of the research was to develop a framework to overcome limitations of previous approaches to assess of risks in excavation projects. According to the complexity of a problem and the inherent uncertainty, the framework adopted SWARA (Step-wise Weight Assessment Ratio Analysis) and COPRAS (COmplex PRoportional ASsessment) methods through introducing new criteria for risk assessment. Data was collected through interview, a literature review and a questionnaire survey distributed to excavation project experts. A case study of deep foundation excavation in Shiraz wa...

Microbial Corrosion of API 5L X-70 Carbon Steel by ATCC 7757 and Consortium of Sulfate-Reducing Bacteria

Various cases of accidents involving microbiology influenced corrosion (MIC) were reported by the oil and gas industry. Sulfate reducing bacteria (SRB) have always been linked to MIC mechanisms as one of the major causes of localized corrosion problems. In this study, SRB colonies were isolated from the soil in suspected areas near the natural gas transmission pipeline in Malaysia. The effects of ATCC 7757 and consortium of isolated SRB upon corrosion on API 5L X-70 carbon steel coupon were investigated using a weight loss method, an open circuit potential method (OCP), and a potentiodynamic polarization curves method in anaerobic conditions. Scanning electron microscopy (SEM) and energy dispersive X-ray spectroscopy (EDS) were then used to determine the corrosion morphology in verifying the SRB activity and corrosion products formation. Results from the study show that the corrosion rate (CR) of weight loss method for the isolated SRB is recorded as 0.2017 mm/yr compared to 0.2530 mm/yr for ATCC 7757. The Tafel plot recorded the corrosion rate of 0.3290 mm/yr for Sg. Ular SRB and 0.2500 mm/yr for Desulfovibrio vulgaris. The results showed that the consortia of isolated SRB were of comparable effects and features with the single ATCC 7757 strain.

Corrosion Study on X70-Carbon Steel Material Influenced by Soil Engineering Properties

Soil as a corrosive medium is probably of greater complexity than other environment. This paper studies the influence of soil engineering properties towards metal loss of buried X70 carbon steel coupons. The study focuses on soil engineering properties which are soil moisture content, clay content and plasticity index. A total of 160 pieces of X70 carbon steel coupon were buried in 5 different locations in Peninsular Malaysia for a period of 12 months to study the effect of the abovementioned parameters towards metal loss caused by soil-corrosion. The samples were retrieved periodically for every 3 months to determine its weight loss and consequently the corrosion rate. It was found that the rapid growth of corrosion is relatively correlated with the high moisture content of soil. Yet, corrosion initiated at a slow pace for high plasticity soil and clayey soil. The highest and the lowest corrosion growth rate were calculated at 0.218mm/year and 0.051mm/year respectively. No strong indication can be found to relate the dominant influence of soil engineering properties towards measured corrosion rate of buried steel coupons.

A new hybrid fuzzy cybernetic analytic network process model to identify shared risks in PPP projects

A proper risk management strategy is essential in property management. For controlling and reducing risks on Public-Private Partnership (PPP) project, risk allocation is a major component of PPP risk management. Identifying appropriate shared risks and optimal risk allocation in a structured way is a complex process. The aim of this study is to develop a quantitative approach for equitable risk allocation with attention to identifying dependencies between risk allocation criteria and barriers. The paper presents an approach in the form of a hybrid Fuzzy method and Cybernetic Analytic Network Process (CANP) model for identifying shared risks. The approach involves the use of Fuzzy sets to convert linguistic principles and experiential expert knowledge into systematic quantitative analysis and the CANP to solve the problem of dependency and feedback between criteria and barriers as well as selection of shared risks. A case study is presented to demonstrate the use of the model in selecting shared risks. The study involves development of 10 criteria and 8 barriers. Finally, of 40 significant risks, 14 risks are successfully allocated between the public and private sector in Iranian PPP projects.

The Consequence Assessment of Gas Pipeline Failure due to Corrosion

In this paper, a qualitative consequence assessment method for damaged urban natural gas pipelines is proposed. It focuses on identifying reputation loss factors according to stakeholders’ (investors, customers, employees, and communities) perceptions. The analytical hierarchy process (AHP) method is applied to prioritize these factors. Results show that the loss of customer confidence ranks as the highest contributor to an operator’s reputation loss due to a pipeline accident. Thus, better risk assessment of pipeline damage due to corrosion will be achieved with the inclusion of reputation loss in the consequence assessment. Hence, decision making in pipeline repair, inspection, and maintenance can be improved as well as a company’s annual profit margin.

Underground Corrosion Model of Steel Pipelines Using In Situ Parameters of Soil

A simple yet practical model to estimate the time dependence of metal loss (ML) in underground pipelines has been developed considering the in situ soil parameters. These parameters are soil resistivity, pH, moisture content, chloride content, and salinity. The time dependence of the ML was modeled as Pmax ¼ ktn, where t is the time exposure, k is ML constant, and n is the corrosion growth pattern. The results of ML and in situ parameters were analyzed using statistical methods such as data screening, linear correlation analysis, principal component analysis, and multiple linear regressions. The best model revealed that k is principally influenced by ressistivity, and n appears to be correlated with chloride content. Model optimization was carried out by introducing several observation criteria, namely, water access, soil color, and soil texture. The addition of these factors has improved the initial accuracy of model to an R2 score of 0.960. As a conclusion, the developed model can provide immediate assessment of corrosion growth experienced by underground structures.

Microbiologically Induced Corrosion Monitoring Using Open-Circuit Potential (OCP) Measurements

This study investigates how sulfate-reducing bacteria (SRB) influence the process of microbiologically induced corrosion (MIC) of carbon steel by measuring corrosion potential using open-circuit potential (OCP) measurements. MIC is mainly influenced by Desulfovibrio vulgaris, formerly known as Desulfovibrio desulfuricans subsp. Desulfuricans, deposited as spirillum desulfuricans, which produces D(-)-lactate dehydrogenase. This strain was recommended by ATCC to be used in the tests described in ASTM. A pure colony of SRB was isolated from the Baram and Sungai Ular areas in Malaysia. An evaluation of SRB growth was performed during the test in the inoculated medium anaerobically at 37 ̊. The results showed that the corrosion potential Eoc increases in the presence of SRB in pure and mixed cultures as compared to the control sample. These results indicate that the SRB caused the metal loss on the carbon steel surface through direct corrosive action of the H2S generated by the bacteria during their metabolic process of reducing sulfates to the sulfide form.

Automated Matching Systems and Correctional Method for Improved Inspection Data Quality

Advances in computing technology, and data gathering tools provides a great opportunity in engineering area such as civil structure analysis domain to better understand its phenomenon. Our case study utilize these advances in pipeline structure in order to study the corrosion behavior that been one of the problem that leads to its failure. The availability of ILI data from MFL tools provides a better insight of corrosion process by using an efficient systems and data analysis method in order to extract important information regarding the condition of the pipeline. Our paper will discuss an implementation of automated matching systems and data correctional method that shown a promising result to improve the quality of data for future reliability assessment. The automated matching systems was evaluated using linear regression method for its sensitivity analysis whereby a modified corrosion rate method was used along with linear prediction method to verify the accuracy of the corrected data. Issues and advantage gain from this research is threefold; timeliness, accuracy, and consistencies in data sampling. This is a preliminary work towards a reliable pipeline assessment method.

Modeling of External Metal Loss for Corroded Buried Pipeline

A statistical predictive model to estimate the time dependence of metal loss (ML) for buried pipelines has been developed considering the physical and chemical properties of soil. The parameters for this model include pH, chloride content, caliphate content (SO), sulfide content, organic content (ORG), resistivity (RE), moisture content (WC), clay content (CC), plasticity index (PI), and particle size distribution. The power law-based time dependence of the ML was modeled as P = ktv, where t is the time exposure, k is the metal loss coefficient, and v is the corrosion growth pattern. The results were analyzed using statistical methods such as exploratory data analysis (EDA), single linear regression (SLR), principal component analysis (PCA), and multiple linear regression (MLR). The model revealed that chloride (CL), resistivity (RE), organic content (ORG), moisture content (WC), and pH were the most influential variables on k, while caliphate content (SO), plasticity index (PI), and clay content (CC) appear to be influential toward v. The predictive corrosion model based on data from a real site has yielded a reasonable prediction of metal mass loss, with an R2 score of 0.89. This research has introduced innovative ways to model the corrosion growth for an underground pipeline environment using measured metal loss from multiple pipeline installation sites. The model enables predictions of potential metal mass loss and hence the level of soil corrosivity for Malaysia.