Master of Science in Materials Science

Permanent URI for this collectionhttp://192.248.9.226/handle/123/15929

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Browsing Master of Science in Materials Science by Author "De Silva GIP"

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    item: Thesis-Abstract
    Developing a model to predict the propagation of sulfide stress corrosion of steel used for petroleum pipelines
    (2021) Deemantha MBA; De Silva GIP
    Sulfide stress corrosion (SSC) is a deleterious type of corrosion that is abundant in petroleum refineries. SSC easily attacks oil country tubular goods (OCTG) in petroleum refineries. The main factors that affect SSC can be identified as the pressure/tensile stress applied on the metal, H 2 S concentration and time period. It can be identified that the environmental conditions of petroleum refineries provide optimum conditions for the initiation and propagation of SSC. Therefore petroleum refinery plants conduct timebasis routine inspections to detect the sulfide stress corrosion. When a severe corrosion is detected at an inspection routine, pipelines are required to be replaced. The unusual behavior of the propagation of SSC cracks may lead drastic failures before it is identified through an inspection routine. Therefore the petroleum industry is expecting to use an accurate model that can predict the initiation and propagation of sulfide stress corrosion. However, the mechanism of SSC has not been clearly revealed yet. The principle aim of this study is developing a model that can predict the propagation of depth of sulfide stress corrosion in API 5L Grade B steel as a function of applied load (tensile load), pH value and time duration. API 5L Grade B steel was procured from Sri Lanka petroleum corporation as a seamless pipe. The model has been established based on the experimental values of depth of sulfide stress corrosion under different predetermined test environmental conditions kept within the pH value of 2.7 – 3.5, applied load of 400 – 800 N and time duration of 15 – 45 days. The depth of sulfide stress corrosion was measured using the scanning electron microscope images of cross sections of corroded steel specimens. The temperature and the pressure of the test environments were maintained at 24±3 0 C and 1 atm respectively. Further, the model was validated by another data set obtained within the aforementioned, same ranges of parameters. All the laboratory experiments were conducted in accordance with ANSI/NACE TM0177-2016 standard test method. In addition to the development of the model, the propagation behavior of SSC was investigated under the above mentioned different test environmental conditions. The microstructures that were observed through scanning electron microscope (SEM) and SEM/EDAX elemental profile plots were obtained to investigate the Sulfur distribution within the crack. According to the experimental results, it was able to develop a model that predicts the propagation of depth of sulfide stress corrosion. The model prediction values were in good agreement with the experimental values. However model tends to underestimate the depth of corrosion values when time duration closes to 30 days. Since the model has been constructed and validated within the pH value from 2.7 to 3.5, applied loads from 400 N – 800 N and time durations from 15 days to 45 days, the model is expected to be given the accurate predictions only within the aforementioned test environmental conditions. The SEM images of cross sections of corroded specimens showed that crack initiation occurred after 15 days at all different test environmental conditions. Further, crack propagation occurred transversely, developing branches through the cross section until 30 days of time duration and the behavior of the propagation of crack was completely changed at 45 days of time duration.
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    item: Thesis-Abstract
    Development of a mathematical model to relate the ageing parameters to hardness and tensile strength of al 6063 alloy
    (2023) Sivanujan S; De Silva GIP
    Deformations, failures, and the wearing-off effect are common in Al 6063 structures due to their low strength and hardness, respectively. Industries have age-hardened Al 6063 alloy to improve its properties to a specified level depending on the components being produced. Industries do trials before production and check to see if the product has achieved its required levels of properties. This trial-and-error method is time-consuming, and further, it is not acceptable from an engineering perspective. For this reason, industries are looking for a model that will provide an accurate prediction of the hardness and tensile strength for the parameters associated with aging. In this research, a mathematical model was developed to predict the most efficient combination of aging parameters to achieve the required tensile strength and hardness of Al 6063. The model was developed based on the experimental tensile strength and hardness values for the 25 combinations obtained by varying aging time and temperature at five levels. Tensile strength and hardness were measured using the universal tensile testing machine and the Vickers hardness tester, respectively. Further, the model was developed using the SPSS statistical software and validated with data sets obtained from the literature. For the purpose of finding the most efficient combination of tensile strength and hardness, the model was developed as a computer program based on the Python programming language. In addition to the development of the model, the influence of precipitate size distribution on the tensile strength and hardness variation of Al 6063 alloy with aging temperature and time was investigated. Micro-structures were observed, and precipitate types were identified using a scanning electron microscope and an energy dispersive spectrometer (SEM/EDS). The precipitate size distribution was determined based on SEM images using MIPAR image analysis software. Beyond the peak age stage, a significant increase in the percentage of precipitates larger than 1.5 μm and a decrease in the percentage of precipitates smaller than 0.75 μm were accompanied by a decrease in tensile strength and hardness.