MARINE CORROSION OF MILD STEEL AT LUMUT, PERAK

• Main Author: ONG , SHIOU TING
• Format: Thesis
• Language: English
• Published: 2012
• Subjects: TA Engineering (General). Civil engineering (General)
• Online Access: http://utpedia.utp.edu.my/9866/1/2012%20-%20Marine%20Corrosion%20Of%20Mild%20Steel%20At%20Lumut%20Perak.pdf; http://utpedia.utp.edu.my/9866/
• Institution: Universiti Teknologi Petronas

The corrosion rate in marine environments affects economic interest since the loss of steel in marine structures has impact on structural safety and performance. With emphasis to maintain existing structures in service, there is increasing interest in predicting corrosion rate at a given location for a given period of exposure. Various corrosion allowances are prescribed for structural members by different standards. There are no studies to determine the appropriate corrosion allowance for offshore steel structures in Malaysia. A field experiment is conducted for estimating the corrosion loss of mild steel under atmospheric, tidal zone and immersion zone corrosion conditions for 2 years in seawater at Boustead Shipyard, Lumut. Parameters such as pH, temperature, salinity, humidity, seawater quality and fouling effect are considered in this experiment to better understand the effects of these parameters jointly on corrosion behaviour. The research objectives are to determine the nature and rate of corrosion and the effect of immersion depth and microalgae on the corrosion rate. Two sets of corrosion coupons of Type 3 mild steel were immersed in seawater. The corrosion rate of the coupon was estimated based on the material weight loss with time. The corrosion rate is controlled by oxidation in short term and bacterial activity in long term. Corrosion rate in the splash zone is observed to be the maximum. The results are also compared with code prescriptions and discussed. A time based corrosion model is developed for sample 1 using EXCEL. The model for splash zone is given by y = 1.0455t14165 and for immersion zone is y = 5.8096t0'7971. Parametric regression model is also developed using SPSS with the parameter pH, temperature, salinity, fouling load and time elapsed. This agreed closely with results from model designed using EXCEL.