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 i
DECLARATION ii
DEDICATION iii
APPRECIATION iv
ABSTRACT v
ABSTRAK vi
TABLE OF CONTENT vii
LIST OF TABLE xi
LIST OF FIGURE xiii
LIST OF SYMBOL xvi
LIST OF APPENDIX 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 (1st trial) 82
4.6 Comparison for group of vessel’s age 18 – 18.5 (2nd trial) 83
4.7 Comparison for group of vessel’s age 18 – 18.5 (3rd trial) 84
4.8 Comparison for group of vessel’s age 20 – 20.5 (1st trial) 84
4.9 Comparison for group of vessel’s age 20 – 20.5 (2nd trial) 85
4.10 Comparison for group of vessel’s age 20 – 20.5 (3rd trial) 86
4.11 Comparison for group of vessel’s age 21 – 21.5 (1st trial) 86
4.12 Comparison for group of vessel’s age 21 – 21.5 (2nd trial) 87
4.13 Comparison for group of vessel’s age 21 – 21.5 (3rd trial) 88
4.14 Comparison for group of vessel’s age 23 – 23.5 (1st trial) 88
4.15 Comparison for group of vessel’s age 23 – 23.5 (2nd trial) 89
4.16 Comparison for group of vessel’s age 23 – 23.5 (3rd trial) 90
4.17 Comparison for group of vessel’s age 25 – 25.5 (1st trial) 90
4.18 Comparison for group of vessel’s age 25 – 25.5 (2nd trial) 91
4.19 Comparison for group of vessel’s age 25 – 25.5 (3rd 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 (1st trial)
4.11 Histogram of comparison for simulated and actual data 83
for group age 18-18.5 years (2nd trial)
4.12 Histogram of comparison for simulated and actual data 84
for group age 18-18.5 years (3rd trial)
4.13 Histogram of comparison for simulated and actual data 85
for group age 20-20.5 years (1st trial)
4.14 Histogram of comparison for simulated and actual data 85
for group age 20-20.5 years (2nd trial)
4.15 Histogram of comparison for simulated and actual data 86
for group age 20-20.5 years (3rd trial)
4.16 Histogram of comparison for simulated and actual data 87
for group age 21-21.5 years (1st trial)
4.17 Histogram of comparison for simulated and actual data 87
for group age 21-21.5 years (2nd trial)
4.18 Histogram of comparison for simulated and actual data 88
for group age 21-21.5 years (3rd trial)
4.19 Histogram of comparison for simulated and actual data 89
for group age 23-23.5 years (1st trial)
4.20 Histogram of comparison for simulated and actual data 89
for group age 23-23.5 years (2nd trial)
4.21 Histogram of comparison for simulated and actual data 90
for group age 23-23.5 years (3rd trial)
4.22 Histogram of comparison for simulated and actual data 91
for group age 25-25.5 years (1st trial)
4.23 Histogram of comparison for simulated and actual data 91
for group age 25-25.5 years (2nd trial)
4.24 Histogram of comparison for simulated and actual data 92
for group age 25-25.5 years (3rd 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
dave = linear regression model of defect depth average
dg = degree of freedom.
E = expected frequency
φ = standard normal probability
f = probability density function
F = cumulative distribution function
kn = number of classes.
μx = mean value
N = class size
O = observed frequency
θ = scale parameter
R2 = coefficient of determination
σ2 = variance
stdd = linear regression model of defect depth standard deviation
σx = standard deviation
tv = age of vessel
u = random variables generated
xo = an offset, which is assumed to be known a priori (the smallest value)
Yu = 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
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