Author: Salina Binti Ramli I/C No: 820610-14-5148 Matric No: MA061181 Year: 2008 Type of Degree: Master of Engineering (Civil-Structure) Supervisor: Dr. Norhazilan Bin Md. Noor Panel of Examiners: 1) Assoc. Prof. Dr. Mohamed Abdelkader El-Gelani Ismail 2) Prof. Ir. Dr. Mohd Warid Bin Hussin 3) Dr. Ahmad Kueh Beng Hong
CORROSION GROWTH PREDICTION IN SEAWATER BALLAST TANK OF BULK CARRIERS USING STATISTICAL MODEL SALINA BINTI RAMLI A project report submitted in partial fulfillment of the requirements for the award of degree of Master of Engineering (Civil-Structure) Faculty of Civil Engineering Universiti Teknologi Malaysia April 2008
I declare that this project report entitled Corrosion Growth Prediction In Seawater Ballast Tank Of Bulk Carriers Using Statistical Model is the result of my own research except as cited in references. This project has not been accepted for any degree and is not concurrently submitted in candidature of any other degree
Teristimewa untuk Ibu dan bapa tersayang; Pn. Aminah Binti Pandak Soud dan En. Ramli Bin Kassim, tunang yang banyak memberi sokongan; En. Nazrul Aizad Bin Harun serta adik-adik yang dikasihi; Mohd Shahril, Saliza, Syahirah dan Syafiqa.
APPRECIATION First of all, grateful to Allah S.W.T, after a year of struggle and hard work, with His will, this thesis is completed. Thanks to Allah for giving me the strength to complete this project and the strength to keep on living. To my supervisor, Dr. Norhazilan Md. Noor, thanks a lot for the guidance you gave in completing this thesis. All advises and help you gave, academically or non-academically, are really helpful and will never be forgotten. To all my friends, thanks a lot for all the helps. Not to forget my partner for this project, Kak Ros, really appreciate all those moments, having fun when the pressure of this project is too much for me. Not forgotten, a million of appreciation to Kak Mazura, Kak Eyza and Kak Shidah with all their helps in completing this project especially for improving my writting in English. To my mom, dad and family, thank you for all the support you gave to me. Your sacrifice is too great to be measured. I will never be here, if you have never been there for me. You ll never be forgotten. Lastly, to my beloved fiancé, Nazrul Aizad Bin Harun, all the support, spirit and inspiration from you all these years had brought me here to complete my master. Really appreciate all your patient and consent. Thanks for everything dear..
ABSTRACT Corrosion is the major cause of deterioration in marine structures. For the past few years have seen an increase in the number of reported instances of accelerated corrosion in ship s ballast tank. This is why careful attention needs to be taken to prevent the deterioration due to corrosion of ballast tank. Therefore, corrosion growth prediction is important in failure analysis. This paper developed a statistical time dependent model for corrosion depth of seawater ballast tank in bulk carriers. The model is based on available group of statistical data for corrosion of existed bulk carriers. The proposed model is benefit for future prediction of corrosion data by eliminating the dependent factors such as environment factor, material properties and operational condition. In specific, a simple simulation procedure is implemented to predict the future distribution of corrosion depth. Based on the result in simulation stage, the result were synthesized and analyzed for validity of proposed model by comparing the actual data with predicted data. The result shows that the model is reliable and practical in predicting the distribution of corrosion depth. From the study, the proposed model seems to be more flexible comparing to the available analysis method and hopefully will facilitate the engineer in the future prediction of ship failure in marine structures.
ABSTRAK Pengaratan merupakan faktor utama kepada masalah kemerosotan kualiti sesebuah stuktur laut. Jumlah pengaratan tangki balas kapal dilaporkan mengalami peningkatan yang drastic beberapa tahun kebelakangan ini. Ini adalah salah satu sebab mengapa perhatian perlu di titikberatkan dalam pengawalan pengaratan sesebuah tangki balas. Oleh sebab itu, ramalan pertumbuhan karat adalah penting dalam menganalisis kegagalan sesebuah struktur. Kajian ini dijalankan bagi menghasilkan sebuah model pertumbuhan karat di dalam tangki balas sesebuah kapal penumpang yang mana berkadaran dengan masa. Model ini dilaksanakan berdasarkan sekumpulan data kapal penumpang yang sedia ada. Model yang dicadangkan ini berguna dan dijangkakan dapat digunakan dalam membuat ramalan pertumbuhan karat bagi masa akan datang. Perlaksanaan model ini adalah berdasarkan faktor bilangan dan umur kapal dengan mengabaikan faktor-faktor lain seperti persekitaran, bahan dan keadaan operasi kapal. Seterusnya, sebuah prosedur penyerupaan yang mudah dijalankan ke atas model yang telah dibangunkan untuk meramal taburan pertumbuhan karat pada masa akan datang. Daripada proses penyerupaan yang dijalankan, kesahihan model yang dibangunkan dapat dibuktikan setelah keputusan yang diperolehi di sintesis dan dianalisis dengan membuat perbandingan secara grafik di antara data sebenar dengan data yang diramalkan. Hasil akhir menunjukkan model yang dicadangkan adalah sesuai dan praktikal dalam ramalan taburan kedalaman pengaratan. Melalui kajian ini, model yang dicadangkan diharap dapat memudahkan jurutera dalam ramalan kegagalan sesebuah struktur kapal pada masa akan datang.
TABLE OF CONTENT CHAPTER TITLE PAGE PROJECT STATUS APPROVAL SUPERVISOR APPROVAL TITLE DECLARATION DEDICATION APPRECIATION ABSTRACT ABSTRAK TABLE OF CONTENT LIST OF TABLE LIST OF FIGURE LIST OF SYMBOL LIST OF APPENDIX i ii iii iv v vi vii xi xiii xvi xvii 1 INTRODUCTION 1.1 Corrosion of Marine Structures 1 1.2 Problem Statement 2 1.3 Objectives and Aim of Research 3 1.4 Scope of Study 4 1.5 Expected Findings and Importance of Research 4 1.6 Conclusion 5
2 LITERATURE REVIEW 2.1 Corrosion 7 2.1.1 Definition 8 2.1.2 Corrosion Mechanism 8 2.2 Corrosion in Marine Structure 9 2.2.1 Corrosion by sea water 10 2.2.2 Marine Corrosion Mechanism 12 2.2.3 Corrosion Failure 14 2.2.3.1 Corrosion Failure Analysis 15 2.2.4 Form of Corrosion 16 2.2.4.1 Uniform Corrosion 17 2.2.4.2 Localized corrosion 18 2.2.4.3 Galvanic Corrosion 22 2.2.4.4 Environmental Cracking 25 2.2.5 Factor Cause Corrosion 28 2.2.6 Metal Use in Marine Engineering 29 2.2.7 Corrosion Prevention 30 2.2.7.1 Painting 30 2.2.7.2 Cathodic and Anodic Protection 31 2.2.7.3 Metal Coating for Corrosion Protection 33 2.2.8 Material and Design to Avoid Corrosion 33 2.3 Seawater Ballast Tank 34 2.3.1 Introduction 34 2.3.2 Corrosion in Ballast Tank 36 2.3.3 Coating Breakdown Mechanism in Ballast Tank 38 2.3.4 Tank Inspection 41 2.4 Marine Corrosion Model 43 2.5 Literature Review of Previous Research Papers 43 2.5.1 Empirical Model 43 2.5.1.1 Kelly, Et. All. (2007) 43 2.5.2 Mathematical Model 45 2.5.2.1 Paik, Et. All (2003) 45 2.5.2.2 Paik, Kim and Lee (1997) 51 2.5.2.3 Shengping Q, Et. All (2002) 51
3 METHODOLOGY 3.1 Introduction 53 3.2 Research Activities 55 3.2.1 Literature Review 56 3.2.2 Data Analysis 56 3.2.2.1 Data Collection 56 3.2.2.2 Analysis and Interpretation of Data 58 3.2.2.3 Histogram Development 58 3.2.2.4 Model Verification using Chi Square Test 65 3.2.2.5 Statistical modeling of corrosion models 66 3.2.3 Simulation and Prediction 66 3.2.3.1 Corrosion Depth Prediction Using Inverse 66 Transformation Method 3.2.3.2 Verifying the Validity of Proposed Model 67 Based on Simulation Results. 3.2.4 Analysis of Model Using Root Mean Square Error 67 Method (RMSE) 4 ANALYSIS AND RESULT 4.1 Introduction 68 4.2 Linear Regression Model 70 4.3 Probability Time-Dependent Model 72 4.4 Chi-Square Test 78 4.5 Simulation 80 4.5.1 Inverse Transformation Method 80 4.6 Result Analysis 81 4.6.1 Graphical Comparison 82 4.7 Root Mean Square Error Method (RMSE) 92 5 DISCUSSION AND RECOMMENDATION 5.1 Overview 95 5.2 Data Collection 97 5.3 Data Analysis 99
5.4 Simulation and Prediction 103 5.5 Recommendation 106 6 CONCLUSION 107 REFERENCES 109 APPENDIX 112
LIST OF TABLES TABLE NO. TITLE PAGE 2.1 Galvanic series of in flowing seawater 23 2.2 Gathered number of measured data set of thickness loss 48 due to corrosion in seawater ballast tank of bulk carriers (Paik and Thayambali, 2003). 2.3 Summary of computed results for mean and the COV of 49 Annualized corrosion rate of bulk carrier s seawater ballast Tank (Paik and Thayambali, 2003) 3.1 Gathered number of measured data set of thickness loss due 57 to corrosion in seawater ballast tank of bulk carriers. 4.1 Corrosion distribution data in seawater ballast tank of bulk 69 Carriers 4.2 Chi square test (average depth = 0.6443) 79 4.3 Chi square test (average depth = 0.9883) 79 4.4 Chi square test (average depth = 0.7555) 79 4.5 Comparison for group of vessel s age 18 18.5 (1 st trial) 82 4.6 Comparison for group of vessel s age 18 18.5 (2 nd trial) 83 4.7 Comparison for group of vessel s age 18 18.5 (3 rd trial) 84 4.8 Comparison for group of vessel s age 20 20.5 (1 st trial) 84 4.9 Comparison for group of vessel s age 20 20.5 (2 nd trial) 85 4.10 Comparison for group of vessel s age 20 20.5 (3 rd trial) 86 4.11 Comparison for group of vessel s age 21 21.5 (1 st trial) 86 4.12 Comparison for group of vessel s age 21 21.5 (2 nd trial) 87 4.13 Comparison for group of vessel s age 21 21.5 (3 rd trial) 88
4.14 Comparison for group of vessel s age 23 23.5 (1 st trial) 88 4.15 Comparison for group of vessel s age 23 23.5 (2 nd trial) 89 4.16 Comparison for group of vessel s age 23 23.5 (3 rd trial) 90 4.17 Comparison for group of vessel s age 25 25.5 (1 st trial) 90 4.18 Comparison for group of vessel s age 25 25.5 (2 nd trial) 91 4.19 Comparison for group of vessel s age 25 25.5 (3 rd trial) 92 4.20 RMSE value for each class of vessel s age 93 4.21 The best simulation result based on RMSE 94 5.1 Collected data 98 5.2 Mean depth and standard deviation for each vessel s age 100
LIST OF FIGURES FIGURE NO. TITLE PAGE 1.1 Organization of study 6 2.1 Schematic representation of current flow in simple 9 Corrosion cell 2.2 Regions where the metal will freely corrode 11 2.3 Crevice corrosion mechanism 12 2.4 Corrosion of metal in marine environment 15 2.5 Electrochemical cell 17 2.6 Uniform corrosion 18 2.7 Pitting corrosion 19 2.8 Crevice corrosion 20 2.9 Filiform corrosion on welded tank 22 2.10 Worm-like filiform corrosion 22 2.11 Galvanic corrosion 24 2.12 Effect of cathode-to-anode (C/A) ratio on galvanic 25 Corrosion 2.13 Stress corrosion cracking 26 2.14 Rusting due to stress corrosion cracking 26 2.15 Cathodic protection electrochemical technique 30 2.16 Cross section of vessel with single ballast tank at the bottom 35 2.17 Electrolyte process of corrosion 37 2.18 Deep pitting in ballast tank 38 2.19 Unprotected ballast tank 39 2.20 Protected ballast tank 39
2.21 Sketch of coating barrier degradation during the vessel s ballast 41 tank life 2.22 Type of marine corrosion model 43 2.23 The corrosion depth versus the ship age from thickness 49 measurements of seawater ballast tank structures (Paik and Thayambali, 2003) 2.24 The 95 percentile and above band for developing the severe 50 (upper bound) corrosion wastage model (Paik and Thayambali, 2003) 2.25 Comparison of annualized corrosion rate formulations, 50 together with the measured corrosion data for seawater ballast tank (Paik and Thayambali, 2003) 2.26 Melchers conceptual model for marine corrosion 52 3.1 Flow chart of study 55 3.2 Plot of Exponential probability density function 60 3.3 Cumulative distribution function of Exponential distribution 61 3.4 Plot of Weibull probability density function 62 3.5 Weibull cumulative distribution function 63 4.1 Linear regression analysis of mean depth and vessel s age 71 4..2 Linear regression analysis of standard deviation and 71 vessel s age 4.3 Specific histogram of ship s age 11.5-12 years 74 4.4 Specific histogram of ship s age 12.5-13 years 74 4.5 Specific histogram of ship s age 15-15.5 years 75 4.6 Specific histogram of ship s age 15.5-16 years 75 4.7 Specific histogram of ship s age 16.5-17 years 76 4.8 Histogram of all data 76 4.9 Exponential probability plot 77 4.10 Histogram of comparison for simulated and actual data 83 for group age 18-18.5 years (1 st trial) 4.11 Histogram of comparison for simulated and actual data 83 for group age 18-18.5 years (2 nd trial) 4.12 Histogram of comparison for simulated and actual data 84 for group age 18-18.5 years (3 rd trial)
4.13 Histogram of comparison for simulated and actual data 85 for group age 20-20.5 years (1 st trial) 4.14 Histogram of comparison for simulated and actual data 85 for group age 20-20.5 years (2 nd trial) 4.15 Histogram of comparison for simulated and actual data 86 for group age 20-20.5 years (3 rd trial) 4.16 Histogram of comparison for simulated and actual data 87 for group age 21-21.5 years (1 st trial) 4.17 Histogram of comparison for simulated and actual data 87 for group age 21-21.5 years (2 nd trial) 4.18 Histogram of comparison for simulated and actual data 88 for group age 21-21.5 years (3 rd trial) 4.19 Histogram of comparison for simulated and actual data 89 for group age 23-23.5 years (1 st trial) 4.20 Histogram of comparison for simulated and actual data 89 for group age 23-23.5 years (2 nd trial) 4.21 Histogram of comparison for simulated and actual data 90 for group age 23-23.5 years (3 rd trial) 4.22 Histogram of comparison for simulated and actual data 91 for group age 25-25.5 years (1 st trial) 4.23 Histogram of comparison for simulated and actual data 91 for group age 25-25.5 years (2 nd trial) 4.24 Histogram of comparison for simulated and actual data 92 for group age 25-25.5 years (3 rd trial) 4.25 Graph RMSE vs Vessel s Age 94
LIST OF SYMBOLS λ = Exponential parameter also known as failure rate µ = mean β = shape parameter δ = location parameter d ave = linear regression model of defect depth average d g = degree of freedom. E = expected frequency φ = standard normal probability f = probability density function F = cumulative distribution function k n = number of classes. μ x = mean value N = class size O = observed frequency θ = scale parameter R 2 = coefficient of determination σ 2 = variance std d = linear regression model of defect depth standard deviation σ x = standard deviation t v = age of vessel u = random variables generated x o = an offset, which is assumed to be known a priori (the smallest value) Y u = upper limit of selected class
LIST OF APPENDIX APPENDIX TITLE PAGE NO A Chi-Square Statistical Table 112 B Simulation Data Example 117 C Graphical Comparison Between Actual 155 D Exponential Model of Corrosion Growth 175 Data and Simulated Data
1 CHAPTER 1 INTRODUCTION 1.1 Corrosion of Marine Structures Corrosion is the major cause of deterioration in marine structures. The past few years have been seen an increase in number of reported instances of accelerated corrosion in ship s ballast tank (Cleland, 1994). Vessels are often made of steel and therefore these structures are too exposed to suffer various types of damage as they get older. In many forms of corrosion, pitting or grooving is forms of corrosion major involved to marine corrosion especially for ballast tank of oil tanker and bulk carrier. This localized corrosion may have serious consequences in ship s structures. It can cause severe cracking or extend wider to produce general structure deterioration. Such failure may associate with higher cost of maintenance including lost lives in some cases.
2 The area of ballast tank that most exposed to corrosion are wing part of ballast tank which situated between the holds and the shipsides. Ballast tank is the outer hull, which create the external shape of ships. Usually, the inner water ballast tank surface area is very large. To make sure the quality of ballast tank, it needs a careful attention. (Singh, 1990). Corrosion has to be avoided. It is due to the complex structure of it with frequent wetting and drying in highly corrosive salt water environment. 1.2 Problem Statement Ballast tank is one of vessel s parts that highly subjected to corrosion. Maintenance of ballast tank to prevent corrosion involves very high cost, therefore only relevant types and level of maintenances should be done to avoid excessive cost. To predict corrosion growth in ballast tank in the future, it is necessary to have a relevant estimate of the corrosion rate. An inspection to measure corrosion depths in a number of vessels ballast tank of various ages has been made. Data gathered from the inspection will be used to develop a statistical time-dependent corrosion model. This model will provide the statistical characteristic such as mean, variance, distribution of corrosion rate as a function of time ship age, making it possible to predict the corrosion rate of ballast tank of any age. Statistical and probability analysis have been suggested by previous researchers to achieve better understanding and predict the exact depth of corrosion growth. Even though this method can gives better interpretation of corrosion growth, wide application is still uncommon. The statistical model is the best method
3 to improve the complex parameter. Thus, this study is motivated by several problems existed in the corrosion failure analysis as listed in the following: a) Difficulty for plant engineer to understanding the available analysis method because of the complexity of corrosion empirical models and statistic technique. b) Errorneous data of corrosion for seawater ballast tank c) Lack of inspection data d) Corrosion models are generally developed based on experimental work at laboratory and will not gives a practical and exact simulation to the real event on site. 1.3 Objectives and Aim The aim of this study is to develop a probability time-dependent model of corrosion depth in bulk carrier s ballast tank. To achieve the aim, the following objectives have been listed which are: a) To identify the distribution of real inspection data using statistical approach. b) To develop a model for representing the growth of corrosion depth using probability method. c) To predict the future corrosion distribution using Inverse Transformation Simulation procedure. d) To compare the actual data with the predicted data generated using the proposed model.
4 1.4 Scope of Study This study will be focusing on the corrosion depth of bulk carrier s seawater ballast tank. The data used to develop a statistical model are the real data that gathered during the site inspection by ship s owner. The types of corrosion that have been considered are marine corrosion. Method that are going to be use in development of statistical model is linear/theoretical method which not consider the environment parameter. The development of statistical model in this research will enable the prediction of corrosion depths at any point of time (ship s age). Then Inverse Transformation Method which is one of element in Monte Carlo simulation will be used to assess and predict the future corrosion depth at any age of vessels ballast tank. The prediction of future distribution of corrosion depth is based on the proposed time-dependent growth model. 1.5 Expected Finding and Importance of Research The expected finding from this study is a time-dependent growth model of marine corrosion in vessels sea water ballast tank. This corrosion model will be reliable in predicting the corrosion rate of seawater ballast tank of bulk carriers at any point of time. The model is specifically tailored to be simple yet practical for on site assessment of structure remaining life-time upon corrosion attack. The proposed method is a provisional tool in predicting the future growth of corrosion defect until more data can become available. Hence, enable the use of more advance and intricate model in corrosion modeling.
5 1.6 Conclusion Figure 1.1 shows the work flow of the study. This study begins with an introduction to corrosion of marine structures, followed by a discussion on problem statement, aims, objectives and scope of study. The introduction is followed by Chapter 2, covering reviews of all topics related to corrosion and previous studies. Then, the research methodology is presented in Chapter 3. Chapters 4 covers the statistical and probability analysis of corrosion data from seawater ballast tank of bulk carriers. The steps in development of proposed model were discussed in detail in Chapter 4 together with the result of simulation then, followed by Chapter 5 with discussion and recommendation to improve the proposed model. The study ends in Chapter 6 conclusion to the study. Introduction Corrosion of Problem Aim and Scope of Expected marine structure statement objectives study findings Literature Review Corrosion background Corrosion Model Previous research work Ballast tank Research Methodology Continue to the next page
6 Analysis and Result Data collection Statistical and probability analysis Results Discussion and Recommendation Data Statistical analysis Results Conclusion Appendix Chi-Square Statistical Table Simulation Data Example Figure 1.1: Organization of study