Operational based corrosion analysis in naval ships
M.T. Gudze
a,*, R.E. Melchers
ba
Defence Science and Technology Organisation, Maritime Platforms Division, 506 Lorimer Street, Melbourne 3207, Australia b
Centre for Infrastructure Performance and Reliability, School of Engineering, The University of Newcastle, Australia
a r t i c l e
i n f o
Article history: Received 4 January 2008 Accepted 20 August 2008 Available online 12 September 2008 Keywords: A. Mild steel B. Modelling studies B. Weight loss C. Atmospheric corrosion C. Microbiological corrosion
a b s t r a c t
Life extension of ageing steel structures such as naval ships requires consideration of plate thickness losses due to corrosion, particularly when protective measures such as paint coatings and sacrificial pro-tection are not entirely effective. Traditionally, corrosion prediction models for ships take no account of the operational profile. Consequently, the corrosion models have an inherently high variability with poor corrosion prediction capability. A new corrosion model for the prediction of corrosion loss in the seawater ballast tanks of naval vessels has been developed. The model incorporates previously available corrosion models for immersion corrosion and atmospheric corrosion and takes account of operational and envi-ronmental variables. Experimental validation is presented for a trial on an operational naval vessel.
Ó 2008 Published by Elsevier Ltd.
1. Introduction
Increasingly, it is important for corrosion rate analysis to be performed on steel structures such as ships, offshore platforms and bridges to determine their safe operating life and for the devel-opment of effective and efficient maintenance practices. Optimal timeframes for asset availability and for planned redundancy also demand information about corrosion rates [1]. Corrosion loss affects the effective load capacity of steel plating through causing plating thickness loss. General or ‘uniform’ corrosion as estimated from mass loss experiments is of main interest. It may involve the coalescence of multiple corrosion pits, as evident by visual obser-vation of unprotected mild or low alloy steels as used in the con-struction of the majority of ships, including naval vessels.
The design of steel ships typically incorporates a corrosion allowance, i.e. an amount of corrosion loss that can be tolerated before the structural system is considered compromised. For com-mercial ships such as bulk carriers and tankers the extent of corro-sion loss is monitored through classification society ship surveys
[2]. Corrosion protection measures include paint coatings and sac-rificial anode systems for immersed areas. However, these meth-ods are not always wholly effective, and continual maintenance usually is required but not always applied. In extreme cases, repair and replacement of structural details may be necessary, incurring very considerable cost penalties due to direct repair costs and to delay costs. It follows that the estimates of the expected rate of
deterioration are important inputs for optimal maintenance and repair decisions for ships.
Ships are exposed to a range of corrosion environments and as a result the patterns of corrosion vary widely. Ballast tanks and void spaces, and cargo holds in commercial ships such as bulk carriers, usually are exposed to quite different corrosion environments and this can influence the rate of corrosion. The structural details and the orientation and position within the space within a given envi-ronment also will cause different corrosion patterns and rates[3]. For immersion environments, influences on corrosion include chemical factors such as salinity, oxygen content, pH and presence of pollutants; physical factors such as temperature and pressure; and biological factors such as bacteria and biomass[4]. For ballast tanks the immersion environment usually is considered the most critical but in modelling the corrosion process attention might also need to be given to the occurrence of repeated wet–dry cycles as a result of the tanks being filled and emptied to adjust the freeboard trim of the ship[5,6]. In addition, the presence of sacrificial anodes may have some influence, although they are effective only under immersed conditions and for uncoated areas. Thus, a de-ballasted tank will not be protected. It follows that the amount of corrosion in a ballast tank is a function of the environment, the type of cor-rosion protection and the tank status. Apart from corcor-rosion protec-tion and operaprotec-tional practices, the main influence on the environmental parameters is the result of the conditions encoun-tered during operations – what might be called the trading route, including geographical influences[3].
The present paper uses two previously developed corrosion models to construct a model for the ‘uniform’ corrosion loss to be expected in seawater ballast tanks of a typical naval vessel.
0010-938X/$ - see front matter Ó 2008 Published by Elsevier Ltd. doi:10.1016/j.corsci.2008.08.048
*Corresponding author. Tel.: +61 3 9626 8162; fax: +61 3 9626 8181. E-mail addresses: matthew.gudze@dsto.defence.gov.au, mgudze@gmail.com (M.T. Gudze).
Contents lists available atScienceDirect
Corrosion Science
Seawater ballast tanks are of particular interest, since they often have the highest rates of corrosion due to high internal humidity and the difficulty of access for maintenance. In order to validate the proposed corrosion model, an experimental trial was con-ducted using unpainted mild steel coupons exposed inside the sea-water ballast tanks of an operational naval ship. Herein results are presented for the modelling parameters involved as compared with observed coupon corrosion loss and measured environmental conditions.
2. Models for estimating corrosion of steel structures
The earliest corrosion models were developed entirely from empirical data sourced from thickness measurement surveys. Most data relates to bulk carriers and tankers and was obtained from many ships and for various locations within ships [7]. Impetus for this work may have been added by concerns over the ageing of ships, particularly of bulk carriers, and the numerous marine accidents resulting in structural failure and serious environmental consequences[8]. Because of the criticality of these matters, ship corrosion models increasingly are required to be of high quality and to produce accurate prediction of likely corrosion loss and its extent[9].
Earlier corrosion loss models presented corrosion loss in terms of a constant ‘corrosion rate’, implying a constant rate of plate thickness reduction over time. The better efforts also included an estimate of the nominal or calculated variation[5,10]. This allowed these models to be used in structural reliability analyses[11–14]
although typically these models exhibited a high degree of vari-ability and thus tended to produce poor estimates of the lifetime risk of failure.
A more refined approach, still empirically based, took into ac-count the physical phenomena of the corrosion process. Three stages were considered: (1) the effective life of the coating before corrosion begins, (2) the generation of initial corrosion pitting points, and (3) the subsequent progress of corrosion[15,16]. In some cases the latter was described by a non-linear function such as
dðtÞ ¼ a tb ð1Þ
where d is the depth of pitting or corrosion loss as a function of time t and both coefficients a and b are obtained from empirical fits to the data. Sometimes they have been presented as random variables with probability distributions obtained to obtain a good fit to the empirical data. Corrosion models that account for the physical pro-cesses of corrosion, for paint life estimates and for a gradual break-down of coatings before the onset of non-linear corrosion also were proposed[14,17,18]. For example, the progression of corrosion was proposed in the form[17]
dðtÞ ¼ d1ð1 et=stÞ ð2Þ
where
s
tis the transition time, d(t) is the thickness of corrosionwastage at time t and d1is the long-term thickness of corrosion
wastage.
In all cases the corrosion models require calibration to empirical corrosion loss data to determine the values of parameters in the model. For example, data for annual corrosion rates used by Yamamoto and Ikegami[15]were sourced from 27 very large bulk carriers with 7581 data points. The coefficient of variation (COV) ranged from 0.51 to 0.74[3]. Paik et al.[14,19]applied data from 7503 data points from 44 bulk carriers with a minimum COV of 0.66, however, most were above 1.0. These studies represent a thorough presentation of corrosion loss data, however, due to the large variations it has limited value for prediction and assessment of remaining life[3]. Moreover, since these models are based on
historical data and on data collected from many ships operating under quite varied operational conditions, they have very limited capability to be used in predictive studies for any one particular vessel.
A different approach to corrosion loss modelling is to base the modelling effort to a greater or lesser extent on the actual pro-cesses involved in the corrosion process[20,21]. This means that models must take some levels of account of the various factors known to be important in the corrosion of steel in natural seawa-ters, including oxygen concentration[22], marine growth and bac-teriological effects [23], pit formation and growth [24] and diffusion of reactants through the rust layer[25–27]. A model that has been developed along these lines is now available[20]. It has mean seawater temperature as the main parameter[28]and has been calibrated to corrosion data obtained for mild and low alloy steel coupons exposed to near-surface seawater conditions. Tem-perature is particularly relevant for ships since the effect of opera-tion at elevated temperatures has been implicated in a number of catastrophic failures of bulk carrier ships[29]. This model forms the main part of the model described herein for ballast tank corrosion.
The other form of corrosion relevant to ship structures and to ballast tanks is marine atmospheric corrosion. The model proposed by Gardiner and Melchers[30]accounts for the chemical and phys-ical processes of ship corrosion in an enclosed atmospheric envi-ronment and, as is usual for atmospheric corrosion, depends on temperature, time of wetness and salt deposition, but also on the voyage time[31]. This model forms the second part of the model for ballast tank corrosion.
In developing corrosion loss models account must be taken of the operational profile of the ship, as highlighted by Gardiner and Melchers[3]. They considered the topside ballast tanks, double bottom ballast tanks and cargo spaces in bulk carriers. Factors in-clude tank status, effectiveness of protective coatings and presence or otherwise of sacrificial anodes. It is considered that a similar ap-proach is required for the ballast tanks in naval vessels.
3. Models for immersion and enclosed atmospheric corrosion
3.1. Immersion corrosion
Immersion corrosion occurs when the seawater ballast tanks are fully ballasted, i.e. fully filled with seawater. Assuming a high degree of loss of coating protection, the corrosion process may be represented using the phenomenological marine immersion corro-sion model proposed by Melchers[20]. The mean value corrosion loss model as a function of exposure time, and the parameters describing the model are shownFig. 1.
The immersion corrosion model consists of five phases[32]that describe the phenomenon of corrosion progression. Phase 0 con-sists of very short-term kinetic and bacterial influences that may be ignored in practical applications. Phase 1 represents the situa-tion when the rate of corrosion is controlled by the diffusion of oxygen from the seawater. It may be modelled, closely, as a straight line, implying a constant corrosion rate (r0). Phase 2 is
non-linear and controlled by the rate of oxygen diffusion through the (increasing thickness of the) rust layers, assumed, theoretically, to be have uniform diffusion properties. Evidently, there is a smooth transition from Phase 1 to Phase 2. Phase 2 will proceed until point AP is reached, at which time anaerobic conditions begin to occur under the rust layers next to the corroding steel. In prac-tice there is likely to be a smooth transition around AP as not all points on a corroding surface are precisely at the same stage[20]. Phase 3 is the theoretical start of predominantly anaerobic con-trolled corrosion, associated with the metabolic activity of sulphate
reducing bacteria (SRB). At first this activity is high owing to the high availability of nutrients but as this settles down the corrosion rate slows to the rate described by Phase 4. This may be modelled, closely, as linear with time. The model has been proposed in a probabilistic setting with the mean value function for corrosion loss given by f(t, T) as a function of time (t) and temperature (T)
[20]. Each phase may be described mathematically as follows:
f ðt; TÞ ¼
r0¼ 0:0539ð2Þ0:1Tmm year1 Phase 1 ðaÞ
½3ðEt þ FÞ1=3mm Phase 2 ðbÞ ra¼ 0:066 exp ð0:061TÞ mm year1 Phase 3 ðcÞ
rs¼ 0:045 exp ð0:017TÞ mm year1 Phase 4 ðdÞ
8 > > > > < > > > > : ð3Þ
The coefficients E and F are functions of temperature[33]. The point AP is described by parameters caand time ta, given by[20]
ta¼ 6:61 expð0:088TÞ ð4Þ
ca¼ 0:32 expð0:038TÞ ð5Þ
Also, the parameter csis[20]
cs¼ 0:075 þ 5678T4 ð6Þ
The parameter functions (Eqs.(3)–(6)) have all been obtained from fitting long-term corrosion data to the model[20]. Recently [32]
slight modifications have been proposed for Eqs. (1d and6but these do not significantly affect the results given herein.
In addition to the mean value corrosion loss curve a zero mean uncertainty estimate is available[34]. This was derived from corro-sion coupon weight loss data as summarized inTable 1.
3.2. Enclosed atmospheric corrosion
The model adopted for the atmospheric corrosion inside the ballast tanks when de-ballasted is that developed by Gardiner and Melchers[30]. It describes the corrosion loss of unprotected mild steel as a linear function of time and is given by[30]
Mass loss=voyage ¼ WF VT ðk1þ k2½Salt þ k3TÞ ð7Þ
The units of mass loss are millimetres, WF is the percentage wetting fraction, VT is the voyage time in years, [Salt] is the salt concentration in parts per million (ppm), T is temperature (°C) and k1, k2and k3are constants.Table 2shows a range of sample
values of the constants as derived from published data. It is seen that there is considerable variability, not attributable to any partic-ular influencing factor[30].
4. Ballast tank corrosion model
The two corrosion models outlined above were used to develop the operational-based ballast tank corrosion model. The key oper-ational profile inputs to this model are (i) the geographical sea area of operation of the naval vessel and (ii) the ballast condition.Fig. 2
shows the flowchart relating these to corrosion loss. It begins by defining the geographical area of operation of the vessel to deter-mine the temperature via a sea surface temperature (SST) data set. Then, depending on the ballast condition, either the immersion corrosion model or the enclosed atmospheric corrosion model is selected to estimate ballast tank corrosion loss. The variability of the ballast tank corrosion model is derived directly from the zero mean uncertainly estimates (Table 1) given for the phenomenolog-ical marine immersion corrosion model.
The geographical sea area of operation of the ship, with the time of year of operation, will determine the average temperature likely to be experienced in the ballast tank. It may be assumed that the internal temperature of the ballast tank is approximately equal to the external SST, since the ballast tanks are at or below the waterline and there is only a (highly conductive) steel plate sepa-rating the inside of the tank from the external seawater. The SST was obtained from the World Ocean Atlas 1998[35]and resolved for each ocean area[36]and for each month.Fig. 3shows an exam-ple monthly dataset, with the various ocean areas defined. This data was used in both the phenomenological marine immersion and enclosed atmospheric corrosion models.
As indicated inFig. 2the ballast condition affects the corrosion environment and hence the component corrosion model that is ap-plied. In general, it is difficult to predict the status of the ballast tank for any given period and for the different geographical regions through which the vessel may travel. The approach taken to esti-mate this was to consider the log of the ballast condition over a period of 70 days for a typical active naval vessel. This indicated that for some 25% of the time the tank is fully ballasted (Fig. 4). This figure was assumed as indicative for all long-term corrosion predictions.
5. Example 1 – three-year output
As an example, consider now the prediction of the corrosion loss over a period of three years for a vessel operating in a sea area located on the eastern Australian sea board.Fig. 5shows plots of typical outputs for daily and cumulative corrosion loss for (a) immersion corrosion only, i.e. for the fully-ballasted tank, (b) en-closed atmospheric corrosion only, i.e. for the de-ballasted tank
Fig. 1. Marine immersion corrosion model for mild steel for near-surface ‘at sea’ conditions[20].
Table 2
Values of constants for enclosed atmospheric corrosion model[30]
Study k1 k2 k3 1 0.0474 0.00611 0.00629 2 0.688 0.00359 0.028 3 0.146 0.00439 0.00663 4 0.127 0.00787 0.00953 5 0.08 0.0014 0.00654 6 0.005 0.00241 0.00568 Table 1
Zero mean uncertainty estimates
Component variability Standard deviation[35]
Coupon (rc) (0.006 + 0.0003T)(t/ta)
Composition (rcomp) (0.016)(t/ta)
and (c) the combination of these conditions based on simulated ballast cycles given inFig. 4.Fig. 5d shows the SST input from this
operational area during this period. These outputs of the ballast tank corrosion model will now be described.
In applying the immersion corrosion model some simplifica-tions were made. Firstly, a best-fit equation was used to determine the time of transition between Phase 1 and Phase 2 (Fig. 1). This point was represented by
t1!2ðtÞ ¼ 0:003t 0:1814t þ 2:668 ð8Þ
Also, the mathematics for Phase 2 was simplified by determin-ing a best-fit equation for the coefficients E and F as a function of temperature (T). The functions are complex and for simplicity they were simplified by considering only temperatures above 10 °C (as is realistic for ballast tanks). The functions used were
EðTÞ ¼ 0:0031e0:0471T ð9Þ
FðTÞ ¼ 6e6T2
þ 0:0003T 0:0039 ð10Þ
In applying the atmospheric corrosion model an estimate was required for the surface salt concentration and the wetting frac-tion. For the constants (k1, k2 and k3) average values estimated Fig. 2. Operational simulation program flowchart (based on Gardiner and Melchers[3]).
Fig. 3. Monthly average sea surface temperatures[35]as applied with the sea areas defined by British Maritime Technology[36].
fromTable 2were used – seeTable 3. It should be noted that these values were derived from published experimental results with exposure times of not more than one year[30]. Typical ship ballast tanks may corrode for longer than this since the minimum time be-tween inspection and repair for navy vessels typically is about 1.5 years.
Since the relative humidity in ballast tanks is typically above 70% for most of the time[30], it was assumed, conservatively, that the wetting fraction (WF) was 0.8. This means that there will be sufficient moisture for corrosion to proceed on the exposed areas
of steel for 80% of the time. It was also assumed that the ship will be on a continued voyage, so that the voyage time becomes the time of exposure. Thus Eq.(7)simplifies to
Fig. 5. Simulated three-year corrosion predictions showing daily and cumulative corrosion loss for operations on the eastern Australian seaboard for (a) 100% immersion corrosion, (b) 100% enclosed atmospheric corrosion and (c) a mixture of immersion and enclosed atmospheric corrosion based on simulated ballast tank conditions. Sea surface temperatures (d) for this operational region are also shown and cumulative corrosion loss outputs also exhibit error bars representing variability of one standard deviation.
Table 3
Values of constants used in the enclosed atmospheric corrosion model
k1 k2 k3
Corrosion lossðmmÞ ¼ 0:8tðk1þ k2½Salt þ k3TÞ ð11Þ
where t is the exposure time in years.
Finally, as a first approximation a salt concentration of 10 ppm was used for all predictions. Using this value together with the other inputs produced an one-year corrosion rate of 0.12 mm/year at 20 °C. Interestingly, this compares favourably with empirical values given for tanker ships[37]. To estimate the importance of the salt concentration level, a sensitivity analysis was carried out. This showed that the one-year corrosion rate at 20 °C increased to 0.25 mm/year when the salt concentration was increased to 50 ppm.
Fig. 5also shows the daily and cumulative corrosion losses for the simulated ballast conditions, i.e. using tank status data (Fig. 4) and using outputs for both immersion and atmospheric cor-rosion. The daily corrosion loss curve is seen to have two parts. The first part represents the (approximately sinusoidal) change as a re-sult of the changing seasonal temperatures as relevant for the en-closed atmospheric corrosion model. The second part consists of the spikes. These are for immersion corrosion under the ballast condition and are the result of the changing phases with time in the immersion corrosion model. It might be noted that the change in ballast condition does not affect the progression of the phase transitions in the immersion corrosion model.
It is highly liked that the frequency of ballasting would affect the interaction of the two models, however, at present they are seen as mutually exclusive. In practice, it is likely that there will be some interaction between the corrosion losses in the ballasted and the un-ballasted conditions, and this should be reflected in the models used. This has not been considered in the present work. Also, in practice naval ships are not operated in one particular geo-graphical sea area as assumed above. Moreover, there will be var-iation in the operations and this will affect the ballasting profile. In order to obtain an estimate of these influences, a set of realistic data for the geographical area of operation was applied. The data was derived from navy fleet activity schedules. Fig. 6shows the SST data using known geographical locations of the ship and
Fig. 7shows the resulting cumulative corrosion losses using these temperature inputs.
6. Example 2 – lifetime corrosion loss scenario
The objective of the ballast tank corrosion model lies in the pdiction of how much corrosion is likely to occur in unprotected re-gions of the seawater ballast tanks and in using that information to optimise protection and repair measures. An alternate application is to use the prediction of corrosion likely to occur as a function of operational conditions such that the operational profile of the ship can be managed to achieve or exceed a desired minimum lifetime.
Fig. 8shows the simulated corrosion loss outcomes for a ship oper-ated in colder waters early in its life so as to reduce early corrosion, followed by higher corrosion losses later, as it is operated in war-mer waters.
7. Experimental validation
To validate the proposed corrosion loss model, corrosion data was collected by exposing unpainted mild steel coupons in a sea-water ballast tank of an operational naval vessel. The on-board trial employed lasted 541 days during which tank water temperature, humidity and ballast condition were monitored.
Because it was not possible to interfere with the structure of an operating naval vessel, the nearest that could be achieved to esti-mate the mass loss due to corrosion of ship’s plating was the use of corrosion coupons. These were necessarily separate from the ship’s plating. During the exposure period temperature, relative humidity and ballast tank status were monitored as the modelling work showed these to be the critical parameters.
Fig. 6. Sea surface temperature plot using known geographical locations of a naval vessel.
Fig. 7. Cumulative corrosion loss in sea water ballast tanks using actual
7.1. Method and installation
A total of 64 coupons of mild steel composition similar to that of the ship’s plating were sourced from the shipyard where the ship was built. The coupons were laser cut to a size 100 50 mm from a 4 mm thickness D36 grade steel plate. The coupons edges were de-burred and holes were pattern-drilled for identification purposes.
The coupons were prepared for exposure by sand-blast clean-ing, measuring for size (length, width and thickness to 0.01 mm) and weighing to the nearest 0.0001 g. The coupons were attached to a test pod made from 150 mm diameter standard PVC pipe using a nylon nut and bolt and spaced from the pod using a short length of vinyl tubing. Two test pods were used, each suspended by ropes from the internal stiffeners within the tank and sufficiently far from plating and stiffeners so as to reduce the likelihood of damage to the hull structure during ship operations (Fig. 9).
A snorkel-like sensor unit was constructed to house the individ-ual sensors for air temperature, relative humidity and water level. It was placed in the upper space of one of the compartments of the ballast tank used for the trial (Fig. 9). The temperature sensor uti-lised was a Type K thermocouple (chromel and alumel). The ballast condition of the tank was recorded using a polysulphide drop float switch and the relative humidity was measured using a Vaisala 50Y HUMITTER Humidity and Temperature probe fitted with an INTERCAP capacitor-type humidity sensor. The humidity sensor has an operating range 0–100% RH (±2% RH at 20 °C) with a 0– 1 V DC output[38]. Because humidity sensors are known not to re-act well to a marine environment, it was not expected that the life of the humidity sensor would be very long but might at least sur-vive a few weeks and thereby provide some useful information in the early stages of the trial.
The moisture proof data logger box (360 200 150 mm) con-tained a Datataker DT50 low voltage data acquisition unit with power supplied via re-chargeable 6 V battery. A 5–12 V DC con-verter was also required in order to power the humidity sensor during data readings. The data logger box was installed in the com-partment immediately above the seawater ballast tank. Connec-tions to the sensor unit required a cable penetration through the deck head. In order to minimize interference with the structure of the ship, a special temporary hatch cover with a through-deck fitting was manufactured for this purpose. The ballast level,
humidity and temperature within the tank were recorded through-out the trial period.
A series of four exposure periods with coupon recoveries at three months period were planned. At each time point the data was downloaded from the data logger, its batteries recharged and one set of coupons recovered. Vessel operations dictated the actual recovery time points. The first set of 16 coupons was recov-ered after 94 days. Further sets of 16 coupons were recovrecov-ered at 211, 294 and 541 days of exposure. The last set of coupons could not be collected close to the planned 12 months period due to the extended operation of the ship during this time.Fig. 10shows the external condition of coupons after each of the exposure periods.
7.2. Results and observations
After collection the coupons were cleaned and weighed accord-ing to well-established corrosion testaccord-ing principles. Cleanaccord-ing was performed using Clarke’s solution according to designation C.3.1 of ASTM G1 (1994)[39]. A summary of corrosion loss measure-ments is shown inTable 4.
Fig. 11shows the recorded temperature, humidity and ballast condition over the complete period of the trial. Although consider-able effort was made to protect the humidity sensor seawater splashing on to the capacitor eventually rendered it non-func-tional. As noted, this was not unexpected. It is evident from the trace shown in Fig. 11 that the effectiveness of the sensor de-creased some time after the first ballasting period and that this be-came more serious subsequently. Hence the later humidity data should be disregarded.
7.3. Comparison to model predictions
The results from the shipboard trial were compared with the output from the corrosion model.Fig. 12shows a comparison be-tween the predicted sea surface temperature (as used in the corro-sion model) and the shipboard temperature recorded inside the ballast tank. Over the total experimental period, the (absolute) mean daily difference between the two data sets is 1.3 °C, with the overall mean difference being around 0.05 °C.
Both temperature data sets, i.e. predicted sea surface tempera-ture and the ballast tank observed temperatempera-ture, were used in the
model to estimate the corrosion loss as a function of exposure time. The estimates are shown inFig. 13. Also shown inFig. 13
are the four average corrosion losses determined from the corro-sion coupons. The error bars represent one standard deviation of
variability from the ballast tank corrosion model at the times cor-responding to that of the observed corrosion loss.
The observed corrosion losses and the components of the corro-sion model also can be compared, assuming these were acting
alone. Only the case of recorded tank temperatures is considered here. The possibilities are (i) immersion only, corresponding to the ballast tank being continually filled and (ii) atmospheric, corre-sponding to the ballast tank being continually empty but humid.
Fig. 14shows the results together with the combination model fromFig. 13and the data points for the actually observed corrosion losses.
8. Discussion
Although a very small part of a naval vessel, the ballast tanks are known to dominate maintenance activity due to the highly aggressive internal environment and the criticality of this part of
the vessel in its operations. It follows that accurate predictions are desirable and therefore the assumptions made in the models are of interest.
It was assumed that the marine immersion corrosion model developed for coupon data is applicable to immersion corrosion in seawater ballast tanks. Further work may be needed to confirm this. The model assumes ‘at sea’ conditions that are defined as fully oxygenated and for unpolluted fresh seawater with typical coastal seawater bacteriological content[28]. It needs to be established whether this is a valid assumption for typical ballast waters in na-val vessels. For example, it would be expected that a ‘freshly’ bal-lasted tank would contain fully oxygenated seawater, however, within the enclosed ballast tank environment this may be depleted with time as a result of on-going corrosion. This could induce the early onset of anaerobic bacteriological activity and hence corro-sion. It is also assumed that the bacteriological component of sea-water would be similar to that experienced inside the tanks. However, due to the lack of natural sunlight within the tank of the bacteriological action could deviate from ‘at sea’ conditions.
Table 4
Average coupon thickness reduction and coefficients of variation
Time exposed in seawater ballast tank (days) 94 211 294 541 Average corrosion lossa
(mm) 0.0253 0.0965 0.1212 0.242 Coefficient of variation (COV) of corrosion loss 0.055 0.056 0.036 0.042 aNote: This is an equivalent one-sided thickness reduction and is determined from a total of 16 steel coupons after each exposure period.
Fig. 11. Environmental parameters recorded from sensors in seawater ballast tank.
Fig. 12. Ballast tank temperature from the Type K thermocouple used during the shipboard trial and compared with the predicted sea surface temperature based on geographical area and date of ship operations.
Fig. 13. Comparison of shipboard trial and simulated corrosion losses. Simulated results use the ballast tank corrosion model with inputs of either the shipboard trial water temperature or published sea surface temperature (with error bars of one standard deviation).
Fig. 14. Comparison of shipboard trial and simulated corrosion losses with similar output for the immersion model and atmospheric model acting alone (i.e. fully ballasted or fully de-ballasted predictions). Also shown are the observed corrosion losses, at corresponding times the variability of one standard deviation are shown for the combined simulated outcome.
Further, the level of pollution within ballast tanks, even for naval vessels, could differ from ‘at sea’ conditions.
The major assumption herein regarding the application of the atmospheric corrosion model was regarding the level of surface salt concentration. In the examples given above, experimentally observed data was not used but generic data was employed. An example is the nominal salt concentration of 10 ppm used herein. Evidently, the atmospheric corrosion loss estimation may be im-proved by using experimentally determined surface salt concentra-tions. The modelling procedure, of course, is not affected.
Under advanced corrosion conditions there is an apparent anomaly between the immersion and the atmospheric corrosion models when ballast conditions change. The immersion model may be in the anaerobic range but the atmospheric corrosion mod-el used herein does not recognize such a state. This is a conse-quence of the nature of the atmospheric corrosion model adopted. However, recent research has shown that anaerobic con-ditions are also likely to exist under advanced atmospheric corro-sion conditions [40]. Moreover, it is known that alternating oxidation and anaerobic conditions can exist and also that they can cause high rates of corrosion. Evidently, there remains room for improvement of the models to account for these factors.
Both the immersion and atmospheric models are based on data from coupon weight losses. Concern has been expressed about the validity of using these for continuous structures but the available evidence is that this is not an issue except for highly advanced states of corrosion when fatigue and stress issues start to affect corrosion [28]. These effects are not likely to be significant for well-maintained vessels with relatively low levels of corrosion loss.
The experimental trial extended over 541 days and produced a total corrosion loss of 0.242 mm. This corresponds to an average corrosion rate of 0.163 mm/year. It compares reasonably well with the range of rates of general corrosion in the literature. For various structural details in crude oil tankers, they are in the range 0.08– 0.21 mm/year[12]. For ballast tanks, corrosion rates of between 0.046 and 0.289 mm/year have been reported[6]with likely corro-sion loss allowance rates in ships for segregated ballast tanks of be-tween 0.04 and 0.10 mm/year for bottom shell plating and between 0.20 and 1.20 mm/year for longitudinal bulkhead web stiffeners[41]. The comparison between these values and those ob-served for the naval vessel provides a reasonable degree of confi-dence that the observations are realistic.
As noted, temperature, the main environmental variable of interest, affects the progression of corrosion with time. For predic-tions using the model a database of geographically based sea sur-face temperatures (SST) was used. However, more accurate temperature data obtained in-situ could be used, and it is of interest to compare predictions based on generic temperature data and on measured data.Fig. 12shows both the SST and the actual ballast tank temperature recorded from the Type K thermocouple. Clearly there is a good agreement, adding confidence to the assumption in the model that SST can be used to approximate the ballast tank temperature. Over the duration of the test, there is surprisingly lit-tle difference between the data sets. Some differences might have been expected since the SST data set combines temperatures spread over large areas of ocean and then has these combined to produce monthly averages. Evidently, even closer correspondence might be possible if SST data of a higher resolution were to be used, how-ever, the results shown herein indicate that greater resolution is not warranted for modelling purposes. The results indicate that with-out access to actual environmental data the use of the SST database is a rational means to predict temperatures in the ballast tanks of a naval ship giving the geographical route of the vessel is known. However, this may not be correct in the case of commercial bulk carriers with single or double hulls particularly if the holds contain
cargo (e.g. iron ore or coal) higher in temperature than ambient. This may affect the temperature inside nearby ballast tanks.
The float switch used to monitor the ballast condition during the shipboard trial provided two pieces of information, (i) the spe-cific time when the tank is ballasted and (ii) the overall ratio of time in the ballasted and de-ballasted condition. The first was used to determine which of the two corrosion loss models (immersion or atmospheric) to apply to estimate the daily corrosion losses. For long-term corrosion loss prediction, however, the exact sequencing and timing of ballasting is unlikely to be known in de-tail and the expected ratio of the ballasted to de-ballasted status of the tank is more useful. In the present investigation the tank was ballasted for about 55 days during the trial, i.e. about 10% of the to-tal time. Moreover, this may not be typical as the ballast tank instrumented was the largest on the ship and is usually the last to be ballasted with seawater as significant amounts of fuel are being consumed. It can be expected that for other ballast tanks and for other vessels the ballasting ratio would be different. The ra-tio also would depend on the size of the tank and the type of ship. It follows that where longer-term corrosion loss prediction is of interest, the exact ballast condition is unlikely to be needed, but rather the ballasting to de-ballasting ratio would be used in mod-elling. In this regard, the validity of applying the immersion and the atmospheric corrosion models separately to account for the dry–wet cycles has been assumed throughout as sufficiently accu-rate. This aspect requires further research although the indications from the modelling to date suggests that it us unlikely to be a ma-jor issue.
Relative humidity, measured during the trial, is a parameter known to be important for estimating atmospheric corrosion loss. For interior ship spaces it has been estimated that above about 90% RH the moisture content is sufficiently high for wetting of the sur-face to occur and for wet corrosion to proceed[30]. The experimen-tal observations (Fig. 11) showed that early in the trial the relative humidity was close to 100% and then declined but stayed around 70–75% for most of the trial. As noted, the later results must be treated with caution owing to the loss of calibration as the humid-ity sensor became affected by prolonged exposure to the saline environment.
Whether coupons are realistic for representing the actual corro-sion losses inside ballast tanks also is of interest. There are at least three issues: (i) the effect of dynamic loading on corrosion loss, (ii) the effect of structural orientation and (iii) the effect of corrosion protection measures.
Regarding the first, the corrosion coupons were exposed in the ballast tank as shown in Fig. 9, with the only possible external loading on them being due to sloshing forces of seawater in the tank. In contrast, structural details that make up a ballast tank would experience dynamic loading with associated flexing as a re-sult of movement of the ship through the seaway. It is possible that the dynamic flexing could accelerate the corrosion process due to some, or all, of the corrosion product spalling from the metal sub-strate. However, this is likely to be the case only when there is se-vere corrosion loss and strains are very high since it is known that moderate strains have negligible effect on corrosion loss[25].
In-situ plate thickness measurements (e.g. ultrasonics) are often used to estimate thickness losses but the resolution obtainable, while acceptable for period classification assessments, is inade-quate for on-going monitoring and for development of corrosion loss models. Actual attachment of coupons to the surface of the ship structure so as to allow transfer of strain and hence stress to the coupon might be possible in principle and has been attempted in other studies, e.g.[42], though in most cases the coupling cannot directly transfer the strains of the ship due to flexibility in the cou-pling. In the present study operational constraints did not permit this approach.
For naval ships severe levels of rust leading to spalling is unli-kely to occur due to the maintenance scheme of these structures. It may be concluded, therefore, that the use of coupons for estimat-ing corrosion loss as used in the present shipboard trial is suffi-ciently accurate to represent actual corrosion losses for ship structural details.
Much more conservative estimates of corrosion loss can, of course, be obtained from the corrosion loss models if only the early rates (r0) are considered. Both the corrosion loss models
incorpo-rated in the ballast tank corrosion model consider the initial rate of corrosion loss corresponding to the situation with little or no corrosion product build-up. Thus Phase 1 of the immersion corro-sion model may be used to estimate the governing corrocorro-sion rate if rust layers are continually removed. The atmospheric corrosion model already is based on empirical corrosion loss data in the first year of corrosion, i.e. before significant build up of rust layers.
The orientation of the structural details is likely to affect corro-sion progrescorro-sion. Generally structural members located in the low-er regions of the tanks and those horizontally aligned whlow-ere watlow-er is pooled on surfaces tend to exhibit higher corrosion rates[14]. These structural details may dominate corrosion progression in commercial bulk carriers, however for naval ships the slenderness and flare of the hull combined with smaller spaces for ballast tanks indicates that overall the plating details are more closely aligned to the vertical plane and therefore the vertical orientation is appropri-ate to represent the corrosion conditions in the naval ship ballast tank. Obviously, this issue will require further consideration when dealing with commercial vessels, such as through using horizontal and inclined coupons. However, the principles laid out in the pres-ent study remain valid.
The effect of the protective coatings and cathodic protection also is of interest. It is an important factor in simulating overall long-term deterioration of a ship structure. As noted, coating ‘life’ was not considered in the present work, mainly because the state of the art for coating life estimation is still largely empirical. Pub-lished data on coating life is scarce and the best practical approach appears to be close inspection and continual assessment of the likelihood of coating breakdown on an actual structure[41]. There is little quantitative data for developing useful models of coating breakdown[43]. Cathodic protection will limit the onset of im-mersed corrosion at defects in coatings, but will not protect in the de-ballasted condition. These topics are obvious areas for more research.
9. Conclusion
Corrosion is known to influence the useful lifetime of ship struc-tures and to affect their lifetime operating costs. Herein a model is presented for the corrosion to be expected in ballast tanks of naval vessels. The model takes direct account of the operational profile of the vessel and in particular the temperature variations as the ship operates in different geographical areas. The model also considers the variation of ballasting conditions. The model uses two previ-ously developed models, one for the corrosion of mild steel under marine immersion conditions and another for corrosion under atmospheric conditions as previously calibrated for use in enclosed spaces.
Results were presented of a shipboard trial for assessment of corrosion in the seawater ballast tanks of an operational naval ves-sel. The results show a close correlation between the corrosion model simulations and the experimental observations. Addition-ally, the measured temperatures within the ballast tank showed good correlation with those predicted using geographically sourced sea surface temperatures.
Acknowledgments
The work reported herein was a collaboration between the Uni-versity of Newcastle, Australia and the Defence Science and Tech-nology Organisation, Department of Defence, Australia. The authors appreciated the support provided by the Royal Australian Navy in permitting the shipboard field trial in the ballast tanks aboard an operational naval ship.
References
[1] R.E. Melchers, The effect of corrosion on the structural reliability of steel offshore structures, Corrosion Science 47 (10) (2005) 2391–2410.
[2] C. Gardiner, R.E. Melchers, Operational parameters affecting bulk carrier corrosion, in: Proceedings of AME’98 Meeting the Needs of Industry, AME-CRC, 1998.
[3] C.P. Gardiner, R.E. Melchers, Corrosion analysis of bulk carriers – Part I: Operational parameters influencing corrosion rates, Marine Structures 16 (8) (2003) 547–566.
[4] R.E. Melchers, Probabilistic model for marine corrosion of steel for structural reliability assessment, Journal of Structural Engineering (ASCE) 129 (2003) 1484–1493.
[5] R. Loseth, G. Sekkeseater, S. Valsgard, Economics of high tensile steel in ship hulls, Marine Structures 7 (1994) 31–50.
[6] J.K. Paik, A.K. Thayamballi, Y.I. Park, J.S. Hwang, A time-dependent corrosion wastage model for seawater ballast tank structures of ships, Corrosion Science 46 (2) (2004) 471–486.
[7] J.K. Paik, J.M. Lee, J.S. Hwang, Y. Park Ii, A time-dependent corrosion wastage model for the structures of single- and double-hull tankers and FSOs and FPSOs, Marine Technology 40 (3) (2003) 201–217.
[8] P. Morris, Ships of Shame: Inquiry into Ship Safety, Parliament of the Commonwealth of Australia, Australian Government Publishing Service, Canberra, 1992.
[9] R.E. Melchers, Probabilistic models of corrosion for reliability assessment and maintenance planning, in: Proceedings of the International Conference on Offshore Mechanics and Arctic Engineering, vol. 2, 2001, pp. 27–47. [10] K. Okamoto, E. Sugita, Deterioration measurement of ship’s hull and
application to design, IHI Engineering Review 26 (1) (1993).
[11] L.D. Ivanov, Statistical evaluation of the ship’s hull cross section geometrical characteristics as a function of her age, International Shipbuilding Progress 33 (387) (1986) 198–203.
[12] W. Shi, In-service assessment of ship structures: effects of general corrosion on ultimate strength, Transactions – The Royal Institution of Naval Architects 135 (1992) 77–91.
[13] C. Guedes Soares, Y. Garbatov, Reliability of corrosion protected and maintained ship hulls subjected to corrosion and fatigue, Journal of Ship Research 43 (2) (1999) 65–78.
[14] J.K. Paik, S.K. Kim, S.K. Lee, Probabilistic corrosion rate estimation model for longitudinal strength members of bulk carriers, Ocean Engineering 25 (10) (1998) 837–860.
[15] N. Yamamoto, K. Ikegami, A study on the degradation of coating and corrosion of ship’s hull based on the probabilistic approach, Journal of Offshore Mechanics and Artic Engineering 120 (1998) 121–128.
[16] N. Yamamoto, Probabilistic corrosion model of ship structural members, in: Proceedings of IMAS’97, Paper 1, Ships – The Ageing Process, 1997. [17] C. Guedes Soares, Y. Garbatov, Reliability of maintained, corrosion protected
plates subjected to non-linear corrosion and compressive loads, Marine Structures 12 (6) (1999) 425–445.
[18] S. Qin, W. Cui, Effect of corrosion models on the time-dependant reliability of steel plated elements, Marine Structures 16 (2003) 15–34.
[19] J.K. Paik, A.K. Thayamballi, S.K. Kim, S.H. Yang, Ship hull ultimate strength reliability considering corrosion, Journal of Ship Research 42 (2) (1998). [20] R.E. Melchers, Modelling of marine immersion corrosion for mild and
low-alloy steels – Part 1: Phenomenological model, Corrosion (NACE) 59 (4) (2003) 319–334.
[21] R.E. Melchers, Probabilistic models for corrosion in structural reliability assessment – Part 2: Models based on mechanics, Journal of Offshore Mechanics and Artic Engineering 125 (2003) 272–280.
[22] F.M. Reinhart, J.F. Jenkins, Corrosion of Materials in Surface Seawater after 12 and 18 Months of Exposure, Technical Note N-1213, Naval Civil Engineering Laboratory, Port Hueneme, CA, 1972.
[23] C.R. Southwell, J.D. Bultman, C.W. Hummer Jr., Estimating service life of steel in seawater, in: M. Schumacher (Ed.), Seawater Corrosion Handbook, 1979, pp. 374–387.
[24] Y. Kondo, Prediction method of corrosion fatigue crack initiation life based on corrosion pit growth mechanism, Transactions of Japan Society Mechanical Engineers 53 (495) (1987) 1983–1987.
[25] U.R. Evans, The corrosion and oxidation of metals: scientific principles and practical applications, Edward Arnold Ltd., London, UK, 1966.
[26] B.B. Chernov, T.B. Pustovskikh, G.M. Chertskova, Evaluation of the maximum corrosion rate of metals in seawater, Protection of Metals 25 (4) (1989) 507– 509.
[27] N.D. Tomashev, Theory of Corrosion and Protection of Metals, The MacMillan Co., New York, 1996.
[28] R. Melchers, Recent progress in the modeling of corrosion of structural steel immersed in seawaters, Journal of Infrastructure Systems (ASCE) 12 (3) (2006) 154–162.
[29] Hyper-accelerated corrosion, Marine Engineers Review, June 2001. [30] C.P. Gardiner, R.E. Melchers, Enclosed atmospheric corrosion in ship spaces,
British Corrosion Journal 36 (4) (2001) 272–276.
[31] C.P. Gardiner, R.E. Melchers, Corrosion of mild steel by coal and iron ore, Corrosion Science 44 (2002) 2665–2673.
[32] R.E. Melchers, T. Wells, Models for the anaerobic phases of marine immersion corrosion, Corrosion Science 48 (7) (2006) 1791–1811.
[33] R.E. Melchers, Mathematical modelling of the diffusion controlled phase in marine immersion corrosion of mild steel, Corrosion Science 45 (2003) 923–940. [34] R.E. Melchers, Modelling of marine immersion corrosion for mild and low alloy steels – Part 2: Uncertainty estimation, Corrosion (NACE) 59 (4) (2003) 335–344. [35] National Oceanographic Data Centre (NODC), (Levitus) World Ocean Atlas 1998 (WOA98), NOAA-CIRES Climate Diagnostics Data Centre, Boulder, CO, USA, 1998.
[36] N. Hogben, N.M.C. Dacunha, G.F. Olliver, Global Wave Statistics, British Maritime Technology, 1986.
[37] B. Thygesen, Crude oil tanker cargo tank corrosion, Presented at the International Technical Conference and Exhibition UK Corrosion 2002, 22–24 October, Cardiff, Wales, 2002.
[38] HUMMITER 50U/50Y(X) Integrated Humidity and Temperature Transmitter, Vaisala Instruments Catalogue, Ref. 1329en 1998–06, Helsinki, Finland, 1998.
[39] ASTM, ASTM G1-90: Standard Practice for Cleaning and Evaluating Corrosion Test Specimens, Annual Book of ASTM Standards, 1994.
[40] R.E. Melchers, Transition from marine immersion to coastal atmospheric corrosion for structural steels, Corrosion (NACE) 63 (6) (2007) 500–514. [41] Tanker Structure and Co-operative Forum (TSCF), Condition Evaluation and
Maintenance of Tanker Structures, Witherby and Co. Ltd., London, 1992. [42] C.P. Gardiner, Corrosion Analysis of Bulk Carriers, PhD Thesis, Department of
Civil Surveying and Environmental Engineering, University of Newcastle, Australia, 1999.
[43] R.E. Melchers, X. Jiang, Estimation of models for durability of epoxy coatings in water ballast tanks, Ships and Offshore Structures 1 (1) (2006) 61–70.
