The process of developing a virtual replica of a physical asset usually involves using the best available values of the material and environment-related parameters essential to run the predictive simulation.The parameter values are further updated as necessary over time in response to the behaviour/conditions of physical assets and/or environment.This parametric calibration of the simulation models is usually made manually with trial-and-error using data obtained from sensors/manual survey readings of designated parts of the physical asset.Digital twining (DT) has provided a means by which validating data from the physical asset can be obtained in near real time.However, the process of calibration is time-consuming as it is manual, and as with each parameter guess during the trial, a simulation run is required.This is even more so when the running time of a single simulation is high enough, like hours or even days, and the model involves a significantly high number of parameters.To address these shortcomings, an experimental platform implemented with the integration of a simulator and scientific software is proposed.The scientific software within the platform also offers surrogate building support, where surrogates assist in the estimation/update of design parameters as an alternative to time-consuming predictive models.The proposed platform is demonstrated using BEASY, a simulator designed to predict protection provided by a cathodic protection (CP) system to an asset, with MATLAB as the scientific software.The developed setup facilitates the task of model validation and adaptation of the CP model by automating the process within a DT ecosystem and also offers surrogate-assisted optimisation for parameter estimation/updating.

The process of developing a virtual replica of a physical asset usually involves using standardized parameter values to provide simulation of the physical asset.The parameters of the virtual replica are also continuously validated and updated over time in response to the physical asset's degradation and changing environmental conditions.The parametric calibration of the simulation models is usually made with trial-and-error using data obtained from manual survey readings of designated parts of the physical asset.Digital Twining (DT) has provided a means by which validating data from the physical asset can be obtained in near real time.However, the time-consuming process of calibrating the parameters so the simulation output of the virtual replica matches the data from physical asset persists.This is even more so when the calibration of the simulator is performed manually by analysing the data received from the physical system using expert knowledge.The manual process of applying domain knowledge to update the parameters is error prone due to incompleteness of the knowledge and inconsistency of the validation/calibration data.To address these shortcomings, an experimental platform implemented by integrating a simulator and a scientific software is proposed.The scientific software provides for the reading and visualisation of the simulation data, automation of the simulation running process and provide interface of the relevant validation and adaptive algorithmics.This comprehensive integrated platform provides an automated online model validation and adaptation environment.The proposed platform is demonstrated using BEASY -a simulator designed to predict protection provided by a cathodic protection (CP) system to an asset, with MATLAB as the scientific software.The developed setup facilitates the task of model validation and adaptation of the CP model by automating the process within a DT ecosystem.

The validation of the operationality of models is considered a crucial step in the model development process.Recent developments in Digital Twinning (DT) enable the online availability of operational data from the physical asset required for operational validation.The benefits of DT in situations where operational validation has formed a basis for model adaptation has also been demonstrated.However, these benefits within DT have not been fully utilized due to the lack of an approach for benchmarking the required quantity, quality and diversity of validation data and performance metrics for online model validation and adaptation.Therefore, there is a need for a framework for benchmarking validation data and metrics requirements during model validation in different domains.An approach for benchmarking the required quantity, quality and variability of validation data and performance metric(s) for online model adaptation within DT is proposed.The approach is focused on addressing the problem of parameter(s) uncertainty of a predictive model within its uncertainty boundary.It involves generating virtual test models, a primary and another reference model for the performance evaluation of one compared to the another with the benchmarked validating data and metrics within DT.This process is repeated until the dataset and/or metric(s) are promising enough to validate primary model against the reference model.The proposed approach is demonstrated using BEASY -a simulator designed to predict protection provided by a cathodic protection system to an asset.In this case, a marine structure is the focus of the study, where the protection potentials to prevent corrosion are predicted over the life of the structure.The algorithm(s) for the approach are provided within a Scientific Software (MATLAB) and integrated to the simulator-based cathodic-protection model.

Integrating inspection data with a CP simulation model enables the creation of a “digital twin” of the structure which can be used to predict the present and future protection provided to all parts of the structure. The design of marine structures is typically based on design guidelines that specify the protection potentials on the structure to be achieved by the CP system and the rate at which elements of the protection system such as coatings are to be assumed to degrade over the life of the structure. As part of the design study, the performance of the CP system can be evaluated and optimised using a CP simulation model which predicts year by year the protection potentials, the depletion of the anodes, and in the case of ICCP the current to be required by the system. While this type of simulation provides valuable information to the design engineer by confirming that the required protection will be achieved. In reality, the actual performance of the CP system will be often different as coatings for example often degrade at different rates to that described in the design rules, environmental conditions may vary, the “as-built” structure may be different and changes and retrofits are made over time. Integrating the CP data collected during the routine inspection surveys with a CP simulation model enables a “digital twin” of the structure to be created by adjusting the model to match the inspection data. In this way, the simulation digital twin represents the behaviour of the structure and the CP system at the time the inspection survey was performed. This then provides the ability to predict the present and future protection for all parts of the structure. By repeating the process with each new inspection report the engineer can easily monitor the differences between the model predictions and survey data systematically to assess current “health” of the structure, identify anomalies, predict and plan for future risks, optimise the inspection strategy and provide early identification of problems which will require actions. In this paper, a case study is presented where the approach is used as part of the integrity management of an FPSO. The paper will describe the system developed and applications of both the 3D corrosion data visualisation and the simulation-based digital twin.

Although computational methods have been separately developed to predict corrosion and fatigue crack growth rates for metallic structures, challenges remain in implementing a methodology that considers the combined effects. In this work the output from a galvanic model is used to determine the spatial distribution of corrosion damage; providing a guide for the location of discrete corrosion damage features that can be analyzed using stress fields from structural models. In order to build confidence in this approach the galvanic models are validated by comparing predicted results to surface damage measurements from test specimens subject to ambient atmospheric exposure. There was good comparison between the predicted spatial distribution of corrosion damage and the measured surface damage profiles obtained from the galvanic test specimens. Following this exercise novel computational corrosion damage features were developed to represent simplified cracks shapes emanating from corrosion pits. Stress intensity factors (SIF) for these newly developed hybrid pit-crack features were determined and these solutions compared to cases where the pit is assumed to be an equivalent crack. The impact of the local, cavity induced stress field, on the SIF solutions is discussed. Building on these findings a fatigue crack growth simulation was performed using an initial flaw emanating from a hemispherical cavity (corrosion pit) located at the edge of hole in a plate. A reasonable comparison, of the predicted number of crack growth cycles, to available experimental test results was achieved.

There is a gap between the Integrity management systems used by companies to manage their assets and the needs of the CP engineer. Integrity management systems do not fully meet the needs of the engineer responsible for corrosion as they do not provide access and visualizations of all the data the engineer needs to make fast and informed decisions. There is also often no easy way to see the trends in the data, or easily access the relevant video and photographic data also recorded during the survey. Data from surveys is normally contained in reports and EXCEL spreadsheets often with different measurement locations and inconsistent naming of the locations between reports. In this paper a system is introduced which enables engineers to manage and visualise in 3D CP survey data and provide access to all the relevant information through a 3D visual interface to any member of the teams. The software gives the engineer the ability to visualize in 3D the historical and predicted CP protection on the structure and the status of the anodes in the CP system. It also provides information on long term trends in the survey data. By integrating the corrosion data with a simulation model a “digital twin” of the structure can be created to make predictions of the present and future protection of all parts of the structure. For example the engineer can easily use the software to systematically monitor the differences between the model predictions and survey data to identify anomalies and give early identification of problems which will require action. The paper will describe the system developed and present applications of both the 3D corrosion data visualisation and the simulation based digital twin

Material degradation mechanisms such as galvanic, pitting, crevice, and intergranular corrosion limit the operational lifetime of aircraft and result in unsustainable long term maintenance costs. Recent studies of naval aircraft suggest that galvanic corrosion is the primary corrosion mechanism, in nearly 80% of the cases, when corrosion damage is observed on the aircraft. Corrosion maintenance is often very labor intensive so more effective scheduling can reduce costs; there is an economical need to move from a “Find and Fix” approach to a more efficient and cost-effective “Predict and Prevent” approach. A new approach to predicting corrosion damage using computer simulation models is presented where not only the corrosion rate can be predicted for complex multi material structures but also the cumulative corrosion damage to structure experiences during its service life. A demonstration of this new methodology (corrosion Service Life Model) is presented using actual environmental exposure data collected onboard a naval vessel. The effects of crevice and pitting corrosion can also be included in this predictive model. The approach is applicable not only to aircraft but to a wide range of structures subject to atmospheric corrosion 1.0 Introduction The annual cost of corrosion for Navy and Marine Corps aviation is estimated at $3.4 B, accounting for 27.9% of the total maintenance budget, with annual non-availability due to corrosion at 228,471 days [1]. Corrosion maintenance is often very labor intensive so more effective scheduling can reduce costs; there is an economical need to move from a “Find and Fix” approach to a more efficient and cost-effective “Predict and Prevent” approach. Aircraft are exposed to a wide range of environmental conditions over their operational life and this influences the type and severity of corrosion damage they experience. For example, sea based aircraft experience a much more aggressive, salt-laden, environment than land based aircraft. In order to make meaningful predictions of cumulative corrosion damage it is critical to know the environmental exposure of an aircraft over the course of Predicting Cumulative Galvanic Corrosion Damage in Aircraft Structures PAPER NBR 2 STO-MP-AVT-303 NATO UNCLASSIFIED+ EOP APPROVED FOR PUBLIC RELEASE its lifetime. Corrosion damage often drives other failure mechanisms including cracks that initiate from the corroded surface morphology. This is a complicated mechanism where both environmental and mechanical loading contribute to the nature and aggressiveness of the structural damage. Structural integrity decision making is intimately connected to a better understanding of how galvanic corrosion influences the formation of corrosion pits and the initiation of cracks. Use of better design principles will reduce the impact of galvanic corrosion and yield more durable structures. Recent advancements in computational corrosion modeling tools have the potential to dramatically improve the durability of aircraft by providing engineers with predictive tools to improve material selection and develop more corrosion resistant designs. Corrosion modeling also provides engineers with forecasting tools that can be used to gain insight into the effect of long term corrosion damage; ultimately helping to improve maintenance scheduling and reduce fleet maintenance costs. 2.0 Predictive Corrosion Modeling Tools Computational modeling is now widely used in many industries to predict corrosion risk, and to design and help better understand the performance of mitigation measures, including cathodic protection. [4, 5]. The Finite Element Method (FEM) has been widely applied as the modeling method in this regard. In this work a modified version of the Nernst-Planck mass transport equation is used to model galvanic behavior. Electroneutrality in the corrosion system (i.e. no charge separation in electrolyte) is assumed along with no bulk motion of the fluid (i.e. fluid velocity = 0). The concentration gradient contribution is also assumed to be much smaller relative to the migration component of the current density. By ignoring these changes in solution chemistry and ion species diffusion the Laplace Equation can be used to model the steady-state current and potential distributions under both bulk and thin film electrolyte conditions. Driven primarily by needs in the aerospace industry, the BEASY Corrosion Manager Software package has recently been improved to include an extended electrochemical database and new analytical tools (i.e. kinetics reaction fitting, curve crossing), support for cumulative corrosion damage predictions, and a connection to an empirically based corrosion pitting model (Figure 1). This suite of software tools supports a range of sophistication in the prediction of corrosion rates for both bulk (deep electrolyte) and thin-film (atmospheric) electrolytes. The most significant development however, is the ability to make estimates of metal loss for dynamically changing exposure conditions, while also including the geometric effects of the galvanic assembly. In order to validate the approach an experimental program was developed with the objective of quantitatively understanding the effects of important external variables on the potential and current distributions in the galvanic coupling between SS316 and AA7075-T6 under both immersion and thin-film electrolyte conditions. Of particular interest was the polarization data required to accurately simulate the anodic and cathodic current density under thin film conditions. The successful validation of the computational modeling approach using galvanic sensor measurements will facilitate the development of better corrosion prediction tools. This work also establishes the bases for creating corrosion prediction models that use real time sensor input. Predicting Cumulative Galvanic Corrosion Damage in Aircraft Structures STO-MP-AVT-303 PAPER NBR 3 APPROVED FOR PUBLIC RELEASE APPROVED FOR PUBLIC RELEASE CAD Model Of The Structure Polarization Database & Curve Crossing Tools Summary of the corrosion risk of all the materials in the structure Corrosion Rate Predictions Pitting Predictions Figure 1-1: Predictive tools in the BEASY Corrosion Manager software 3.0 Corrosion Rate and Distribution Experimental Validation In order to validate the approach an experimental program was developed with the objective of quantitatively understanding the effects of important external variables on the potential and current distributions in the galvanic Predicting Cumulative Galvanic Corrosion Damage in Aircraft Structures PAPER NBR 4 STO-MP-AVT-303 NATO UNCLASSIFIED+ EOP APPROVED FOR PUBLIC RELEASE coupling between SS316 and AA7075-T6 under both immersion and thin-film electrolyte conditions. Of particular interest was the polarization data required to accurately simulate the anodic and cathodic current density under thin film conditions. 3.1 Segmented Electrode Galvanic Sensor A segmented electrode galvanic sensor was designed and fabricated by Luna Innovations Inc [3] to investigate the spatial and temporal variations of galvanic currents during static conditions. The sensor was fabricated from 50.8 mm (2 in) wide plates and sheets of aluminum (AA7075-T6) and stainless steel (SS316) of varying thickness in a simple butt-joint configuration. Thinner segments were included closer to the butt-joint interface where anodic and cathodic current density gradients are expected to be the highest and thus require finer spatial resolution. Three SS316 and five AA7075-T6 segments were included. The thicknesses of the SS316 segments, in order from the furthest to the closest to the butt-joint interface were 12.7 mm (0.5 in), 3.2 mm (0.13 in), and 1.2 mm (0.06 in). The thicknesses of the five AA7075-T6 segments, in order from the furthest to the closest to the butt-joint interface were 12.7 mm (0.5 in), 6.4 mm (0.25 in), 2.3 mm (0.13 in), 1.2 mm ( 0.06 in), and 1.2 mm (0.06 in). All segments were electrically isolated by a 50 μm thick prepreg layer. The segmented galvanic sensor was subject to two different tests to measure the anodic and cathodic current density distributions under varying electrolyte layer thicknesses under static relative humidity (RH) conditions. The static holds were conducted with 2.6M NaCl applied to the sensor surface under 90% RH and 25 °C (in a programmable humidity and temperature cabinet) to ensure minimal evaporation. The electrolyte thicknesses were 1000 μm, and 80 μm. The 1000 μm film was created by placing a silicone gasket around the edge of the sensor to create a reservoir that would also break up the fluid surface tension at the edges. 3.2 Model Description A computational model of the segmented galvanic sensor was created to predict galvanic currents under both immersion and thin film atmospheric conditions. These results were then compared to the experimental measurements in order to validate the modeling approach and the suitability of the polarization data inputs. The model configuration of interest is shown in Figure 3.2. Figure 3-1 Image of segmented electrode sensor, top segments are SS316 and bottom segments are AA7075-T6. Red material is a silicone gasket to create an electrolyte reservoir. Figure 3-2 Model of Segmented Electrode Predicting Cumulative Galvanic Corrosion Damage in Aircraft Structures STO-MP-AVT-303 PAPER NBR 5 APPROVED FOR PUBLIC RELEASE APPROVED FOR PUBLIC RELEASE The model geometry is first discretized using an appropriate meshing scheme, boundary conditions based on the electrochemical kinetics (i.e. polarization curves) are then applied to represent the SS316 and AA7075 electrodes, and finally the characteristics of the electrolyte film (e.g. conductivity, film thickness) are assigned. The polarization curves, describing the electrochemical kinetics, for both immersion (bulk) and thin-film conditions are shown below in Figure 3-3. In this particular model each electrode

Atmospheric corrosion represents an annual multi-billion dollar cost burden for the aerospace and defense sectors. For many aircraft, particularly those operating in marine environments, up to ninety percent of corrosion is due to galvanic interactions at dissimilar metal couples. As new materials are introduced with the acquisition of more advanced aircraft, galvanic corrosion is likely to remain a concern. The ability to model galvanic corrosion accurately holds the promise of being able to both predict the performance of new material combinations to guide material selection and predict corrosion damage for maintenance planning. Such models often utilize data collected under immersion test conditions that are not representative of the thin-film electrolytes that are relevant to atmospheric corrosion and may diminish model accuracy and utility. In this work, an atmospheric cell is presented that allows for measurements of corrosion kinetics using thin-film electrolytes. It is observed that the limiting oxygen reduction current density on various alloys is increased several orders of magnitude over immersion results. A segmented, galvanic sensor is presented that enables the experimental quantification of spatial distributions of galvanic current under thin film conditions that is compared to model predictions for verification of the suitability of immersion and thin-film electrolyte polarization data inputs.

Multibarrier isolation of hazardous waste is proposed by organizations and companies responsible for underground disposal of such waste. The host rock of repositories is of majorimportance and cons ...

The design rules used to design CP systems in the main do not take into account the interference between the anodes provided to protect a structure or interactions between the structures themselves. CP systems will always interact with each other to some extent when they are in the same electrolyte even when there is no metallic electrical connection and this can radically affect the protection provided to the structure and the life of the CP system. A case study is presented involving the design of the CP system of an FPSO (Floating production storage and offloading vessel). The aim of the study was to verify the performance of the CP system to ensure that the structure was protected for the design life and the anodes had sufficient capacity. Computer modelling was used to simulate the performance of the CP system which comprised of an ICCP system and sacrificial anodes. The study identified some interesting and unexpected interactions which required the design of the CP system to be modified.

Deep geological disposal of dangerous waste like mercury, solidified organic pesticides and radioactive rest products, requires suitable engineered barriers. Use of deep abandoned mines is a ration ...

In the product development process, to assess the risk of corrosion designs are often exposed to an outdoor environment for a long time, or corrosion acceleration tests are conducted to simulate the actual condition the vehicle or structure will be exposed to during its life. These methods however require several months to years of test time to complete. As an alternative approach computational modeling has the potential to significantly shorten and reduce the cost of testing. The paper gives an overview of the development and experimental validation of a computational model for simulating galvanic corrosion in an aircraft environment. The numerical approach is based on a three dimensional Boundary/Finite Element Method model. Amongst the inputs of the problem are: geometrical description and physical properties of the electrolyte, as well as macroscopic polarization curves of the active electrodes. The main outcomes of the model are corrosion rates, electric current density and potential distribution. An experimental set-up has been established for validation of the computational results consisting of a co-planar bi-material combination composed of aluminum UNS A92024 and carbon fiber reinforced polymer (CFRP). The validation approach is explained and the results are shown. Very good agreement has been obtained between observed and simulated data. This basic model has been applied to different multi-material combinations relevant for aircraft structures. In particular, different cases of application of protective coatings and other corrosion protection measures are also considered. Finally how the modeling approach will be further developed to be used for simulating galvanic corrosion in more complex structural components of an aircraft will be discussed.

Marine structures are frequently monitored or surveyed as part of an ongoing integrity management program to obtain data on corrosion potentials, anode consumption and in some cases field gradients. One objective is to determine how effective the CP system is at providing protection to the structure and another is to verify that sacrificial anodes are being consumed at a rate consistent with design assumptions. However it is not economic or in many cases even feasible to measure potentials on a complete structure or to collect data from all anodes, so the CP engineer is required to infer the condition of the overall structure from the available data. In particular for structures with complex geometry, the accuracy of data collected may not be reliable, as for example potential readings obtained with a measurement probe can be affected by nearby metal surfaces, leading to significant error in the data collected particularly for field gradients. Similarly access problems can result in error if the probe cannot be oriented or placed on the structure or anode in the required location. These issues require the CP engineer to use his judgment to determine which data to use and which to discard. Computer modeling has been used in the design of CP systems firstly to optimize the design, and secondly to provide assurance to the operator that requirements for anode life are met, and that the system will sustain the potentials required to protect the structure. In such a case the structure geometry and the anode design are supplied as data to the model and the model predicts the potentials and the anode consumption rates over the life of the structure. However another application of modeling is to use it to convert information we can measure into the information we want to know. In particular modeling can be used to expand limited survey data into a prediction of potentials on all structural surfaces, and to provide data on the performance of all anodes. A case study is presented in which computer modeling is used to evaluate data from a single survey, then to enhance the data to provide a view of potentials over the complete structure and to provide a view of consumption of all anodes.

Above ground tanks are frequently used for the storage of Oil & Gas products and they can present a challenge to design an optimum corrosion control system. The base of the tank lies on or near the surface of the ground and is in contact with the material used to support the tank and therefore presents a corrosion challenge.One method of protecting the bottom of a tank is by use of an impressed current cathodic protection (ICCP) system. There are a number of types of Cathodic Protection systems which are designed to protect the tank base in these circumstances. The details of the design of such a system are very important for optimal performance and also the cost, if a number of such systems are to be installed The consequence of a poor design can be uneven distribution of protection potential on the tank base or in the worst cases regions where corrosion of the tank base can take place. An over designed system on the other hand can have significant economic consequences both in terms of installation cost and running costs.Computer modeling is now widely used to optimize CP Designs and verify that the design of the cathodic protection (CP) system meets the design requirements. In this paper a modeling tool is presented which enables corrosion engineers to evaluate the performance of tank base CP systems by predicting the protection provided to the tank for a given CP design. The paper describes and discusses all aspects of the modeling methodology, which it then applies to several different design concepts.

Design of sacrificial anode cathodic protection (SACP) systems to achieve uniform anode mass loss rates is desirable, since it helps avoid early installation of costly retrofit systems which may be needed if some anodes are consumed more quickly than others. Such optimized design is only practically possible through the use of mathematical modeling performed using numerical techniques. A range of numerical methodologies can be applied to simulation of galvanic effects and cathodic protection, and of these it is the boundary element method that is applied in this work. The simulation requires an accurate model of the structure which is to be protected, as well as the anodes, and any other metallic structures which may act as current drains (even though they may not need to be cathodically protected). The optimization process first involves design and simulation of an initial SACP system design. Performance of the design is assessed against criteria which may include anode mass loss rate, most positive allowed potential and remaining anode mass, not only at start of life, but also throughout the design life of the structure. The results of previous assessments are used to guide the selection of the next trial SACP system design, which usually involves changing the number, position or size of anodes, while adhering to user-defined rules (e.g. “keep-out areas”). The process is repeated until satisfactory results are obtained. The objective of this paper is to explore such simulation techniques, and show how they can be combined to provide a practical toolset for SACP system design optimization. This provides the user with new and significantly more powerful design capabilities which are based on real physics rather than standardized design rules. The use of these tools both reduces the risk of the CP design not meeting its required life and ensures an economical design The paper illustrates performance of the design and optimization processes using a jacket structure for which long-term “sigmoidal” polarization curves provide an appropriate representation of calcareous deposits.

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Prestressed Concrete Cylinder Pipe (PCCP) is a rigid pipe designed to take optimum advantage of the tensile strength of steel and of the compressive strength and corrosion inhibiting properties of concrete and is frequently used for water transmission. PCCP consists of a steel cylinder embedded in a concrete core, which is helically wrapped with high-strength, hard-drawn wire after curing. The wire is embedded in thick cement slurry and coated with a dense cement mortar. While the cement mortar and additional coatings usually protect the prestressing wires from corrosion, in certain circumstances chlorides can diffuse into the mortar and reach the wires. Therefore PCCP transmission pipelines can also be protected by CP systems to mitigate the risk of corrosion damage when chlorides are high in the soil. This paper describes a computer modeling study which was designed to determine the protection provided by a CP system, to evaluate different design options, and to optimize the design. Results will be presented showing the model predictions for the different cases considered.

The paper gives an overview of the development and experimental validation of a computational model for simulating galvanic corrosion in specific application case scenarios appearing in an aircraft environment. The numerical approach is based on solving the electro-neutrality equation with a three dimensional Boundary/Finite Element Method. Amongst the inputs of the problem are: geometrical description and physical properties of the electrolyte, as well as macroscopic polarization curves of the active electrodes. The main outcomes of the model are electric current density and potential distribution on the surface. The focus of the study is thin electrolyte conditions that could occur in the upper part of A/C structure. A model considering a co-planar unpainted bi-material combination composed exemplarily of Aluminum AA2024 and carbon fibre reinforced polymer (CFRP) has been developed. An experimental set-up has been established for validation of the computational results. The validation approach is explained and the results obtained are presented. Good agreement has been obtained between observed and simulated data. This conceptual model can be applied to different multi-material combinations relevant for aircraft structures. In particular variations in the environmental condition are considered, including for example different thicknesses of electrolyte film, and different aggressiveness of electrolytes. Further parameter studies are discussed to show the effect of different physical properties of the electrolyte on corrosion rates and total current changes in the materials involved.

Sacrificial anode retrofitting to aging structures is routinely performed for life extension of offshore assets in matured fields. Sometimes earlier retrofit systems are now being replaced or supplemented. Understanding when remnant CP systems can no longer prevent depolarization is important as timely intervention can reduce overall retrofit cost, which is a significant factor. Life must be extended a required number of years, and design should take into account performance of remaining anodes and state of calcareous deposits. Data for this is generally available from past surveys. During design, computational modeling can be used firstly to gain quantitative understanding of the state of the structure, remaining life of existing anodes and estimated date at which serious loss of calcareous deposits will occur. Secondly, modeling can determine the short term effect of a new CP system on structural potentials. This information can be used to modify the numbers, positions and mass of new anodes. This optimizes distribution of potential and anode mass loss rates. Moreover, benefits of fewer large versus several smaller anodes can be weighed-up. Finally, modeling can determine the long-term effects of new, old, and combined CP systems, eg to identify when individual anodes reach their utilization factor and consequent effect on remainder of structure. The aim of this paper is to present a case where modeling has been applied to a jacket structure, using “long-term” polarization curves to represent accumulation of calcareous deposits. Hence, the key benefits achieved are: retrofit requirement reduction, significant cost savings, better CP current distribution despite reduction in number of anodes, maximized life. Other future benefits are possibility to predict future CP survey frequency and improved planning of retrofits requirements; hence saving further cost on needless future surveys.