Validation of a Galvanic Corrosion Model for AA2024 and CFRP with Localised Coating Damage

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1 Validation of a Galvanic Corrosion Model for AA2024 and CFRP with Localised Coating Damage Siva PALANI 1, Theo HACK 2, Andres PERATTA 3, Robert ADEY 4, John BAYNHAM 5, Hubertus LOHNER 6 1 EADS, Germany, siva.palani@eads.net 2 EADS, Germany, theo.hack@eads.net 3 CM BEASY, UK, aperatta@beasy.com 4 CM BEASY, UK, r.adey@beasy.com 5 CM BEASY, UK, jbaynham@beasy.com 6 AIRBUS, Germany, hubertus.lohner@airbus.com Abstract: The paper presents the development and experimental validation of a computational model for simulating galvanic corrosion in typical case scenarios appearing in an aircraft environment. The numerical approach is based on the three dimensional Boundary Element Method. Amongst the inputs of the problem are: geometrical description and physical properties of the electrolyte, as well as macroscopic polarisation curves of the active electrodes. The main outcomes of the model are corrosion rates, electric current density and potential distribution. The case study used for the validation consists of a co-planar pair of Aluminium AA2024 and carbon fibre reinforced polymer (CFRP) immersed in saline solution with variable coating conditions. In particular, the situation of a circular damage ( pinhole defect ) of a coating of very high insulating properties on the anodic side of the sample is considered. A comparison between experimental measurements, including potential and total current flowing between anode and cathode, and the corresponding simulation results is presented for different variations of the modelling scenario. Very good agreement has been obtained between observed and simulated results for systematic variations of the case study which consider different locations of the damage in the sample, different surface area ratios between anodic and cathodic regions, and different electrolyte conductivities. The successful validation of the modelling approach has enabled its use for simulating galvanic corrosion in more complex structural components of an aircraft as illustrated in this paper. Keywords: Galvanic corrosion, AA2024, CFRP, Boundary Element Method, Aircraft 1. Introduction Corrosion protection plays a very important role in the design and maintenance of the aircraft. The alloys currently used are the compromise of high specific strength and corrosion resistance. The extreme long aircraft design life requires durable protection systems to ensure acceptable operational cost during in-service. Current maintenance concepts are based on either damage tolerance or safe life concepts. In both cases it is assumed that the structures are free of corrosion. Therefore, any corrosion flaw that is found during inspection has to be repaired. This philosophy causes high repair and maintenance costs for the airliner. Reduction in 1

2 maintenance costs of new aircraft structures can be achieved by extension of the inspection intervals. New maintenance requirements have to be defined and the protection against corrosion has to be very effective. In addition, at the same time the corrosion protection should also be adequately optimized in order to reduce design and manufacturing cost of the aircraft. Therefore, a tailored corrosion protection system is required. In the aircraft industry, because of the recent demand for better fuel-efficiency, more lightweight materials such as aluminium, magnesium, titanium and CFRP (Carbon Fibre Reinforced Plastics) are utilized and particularly combinations thererof. The application of this increasing mixed materials enhances the risk for galvanic corrosion. Galvanic corrosion (GC) is one type of corrosion and can occur when two different materials with different electrochemical properties are coupled in the presence of a corrosive electrolyte. Therefore, galvanic corrosion is the undesirable result of this mixed materials usage. New aircraft designs contain a high degree of CFRP materials which are in contact with Aluminium in specific areas. Galvanic corrosion can be induced, since the carbon fibres behave electrochemically like a noble metal where cathodic corrosion reaction will take place and the aluminium alloy is preferentially corroded. The basic principles of GC are quite well established and generally understood, but the general understanding gained has so far not yet been exploited enough to narrow down the difference between scientific research and reality. On the other hand, the progressive advance of computational resources in the last few decades has today made possible to model a variety of complex corroding systems, thus representing a leading edge technology not only for research in the subject, but also for direct application in engineering design [1]. At present, a computational modelling approach is one of the most effective tools for design and optimization purposes, as well as for failure detection, monitoring, and quality performance assessment. In addition, recent advances in numerical methods have allowed the solution of increasingly larger and more complicated structures [2]. One of the general objectives of modelling GC is to tailor the corrosion protection measures in order to avoid GC for hybrid structures without performing a huge amount of laboratory testing. A crucial aspect of computational modelling for GC is its connection with reality, and its reliability as a predictive tool, and for this reason the validation step of any model is as important as any other aspect of the model. This work generally describes the status of the development of a basic galvanic corrosion model based on BEM (Boundary Element Method) and how protective coatings are integrated in this model concept in order to optimize the protection of the mixed structures against galvanic corrosion in aircraft environments. The validation approach consists of comparing experimental measurements of electrolyte potential and corrosion rates obtained from a corroding sample with the predictions coming from the equivalent computational model. The materials involved in the experiment are coated aluminium alloy AA2024 with circular pinhole defect damage and Carbon Fibre Reinforced Plastics (CFRP) acting as anode and cathode, respectively. 2

3 2. Bi-Electrode Model The basic bi-electrode galvanic corrosion model which was validated in previous work for bare substrates is adapted in order to contemplate the study of coatings. Generally, this new model with coating damage considers the case of having an isolated small damage (pinhole) on the coating of the anodic part (AA2024 unclad) of the model with varying exposed cathode (CFRP) area. In this case the cathodic surface area is much bigger than the pinhole surface area. This is an extreme condition for localized corrosion in the pinhole. The objective of this work is to verify the modelling capabilities for solving high current densities in the pinhole in the range of that can be validated experimentally. The main geometrical parameters of the model are shown in Figure 1. The model considers the critical situation of a small circular defect (pinhole) of diameter d p on the coating of the anodic side located at a distance Xt apart from anode and big cathode electrodes. The model main design conditions are as follows: CATHODE CFRP uncoated and ground Surface area = mm 2 depending on C/A ratio (refer Table 1) ANODE AA2024 (unclad) Perfectly coated except at pinhole Surface area = 130 mm x 107 mm (a x b) COATING Perfect insulator (high barrier properties) ELECTROLYTE Thickness=5 cm PINHOLE Without coating Surface area = 20 mm 2 CATHODE COATING d p ANODE b Xt a PINHOLE Figure 1: Sketch of a top view of the co-planar galvanic corrosion model indicating the main parameter notations 3

4 The size of the defect (pinhole) is set to 20 mm 2 which means d p is ~ 5 mm. The justifications for the size of the defect are because it s easy to be manufactured and in order to expect a quantifiable experimental result, which later can confidently be used for the simulation results validation. Based on the rough sketch in Figure 1, the actual design with geometries, dimensions, and testing scenarios for different cases were constructed as shown in Figure 2. However, the model differs for different variations in modelling scenario. Exposed Cathode (CFRP) Pinhole (AA2024) h e Coated Area (Lacquer) Electrolyte: 28 x 12.5 x h e cm Figure 2: Geometrical description of the finalized model in CAD interface [3] The integration domain consists of the electrolyte with two planar surfaces i.e. exposed CFRP and pinhole acting as anode and cathode respectively, as shown in Figure Problem Formulation The problem formulation for the electrolyte is based on the charge conservation equation in the bulk of the electrolyte under steady state conditions. The mathematical description of the problem is based on the 3D Poisson equation for the electrolyte potential with non-linear boundary conditions imposed by the prescribed polarisation curves on the active electrodes. The physical and mathematical background for the modelling can be followed from references [1,4,5]. In the steady state case, the governing equation for the electrolyte becomes 1 : j 0 (1) where j is the current density given by: j V (x e ), represents the electrolyte conductivity, and V (x) is the electric potential in the electrolyte at point e x, x x represents the 3D gradient operator , 3 3 x R. The 4

5 integration domain of this problem is the electrolyte, and the boundaries are defined by all the surfaces surrounding it, including the anode, cathode and the insulating walls. The boundary conditions applied to the active electrodes are of the generic form: Ve jn f ( V ) (2) nˆ where j n is the current density flowing throughout the surface in normal direction (nˆ ), and V is the polarisation potential across the interface metal/electrolyte given by V V e V m where V m is the potential in the metal. This boundary condition is actually given by the corresponding polarisation curves which result from the representative polarisation curves characterisation of the material. The function f, usually containing exponential factors of V as prescribed by Butler-Volmer type equations, is in general non-linear and considered as an assembly of linear functions. This relationship must be known prior to solving the model. The software BEASY [6] used for the simulation needs to know the representative polarisation data as an input in order to assign this type of non-linear boundary condition to the corresponding electrode. In this particular model, all other surfaces in contact with electrolyte apart from the interfaces with the AA2024 (pinhole) and CFRP samples are considered as insulating, i.e. j 0. n This numerical approach is based on the Direct Boundary Element Method (BEM) combined with collocation technique [7,8,9] 4. Methodology The modelling and validation experiment is basically to investigate the effect on galvanic current and potential by 3 main scenarios, which are: Distance variation (Xt) between exposed cathode and anode (pinhole) Cathode to anode area ratio (C/A) Electrolyte conductivity variation The validation work in general context consists of experimental determination of electrochemical data which can be compared with the results of the computational modelling as shown in Figure 3. These electrochemical data are: Results of potential field measurements in the electrolyte on anode and cathode areas Total current flowing between anode and cathode In general, there are total of 10 cases under consideration in this work as listed in Table 1. The case number matches the notation adopted for the experimental part. C/A ratio is the cathode to anode surface area ratio. Xt is the distance between gap and pinhole centre, as defined in the experiment. The σ refers to the electrolyte conductivity. 5

6 Table 1: List of case scenarios considered for modelling and experimental work [3] Case Case Pinhole C/A Ratio Xt Conductivity, Area σ Type at Anode [cm] [µs/cm] [cm 2 ] 1 Xt Variation Xt Variation Xt Variation σ Variation σ Variation σ Variation C/A Ratio Variation C/A Ratio Variation C/A Ratio Variation C/A Ratio Variation

7 Galvanic Corrosion Mathematical Approximation Validation o Measurement of polarization curves of electrodes involved o Measurement of potential fields in the electrolyte o Measurement of total current between anode and cathode Simulation Outcomes MATHEMATICAL MODEL o Partial differential equations (PDEs) o Constitutive equations o Initial conditions (ICs) o Boundary conditions (BCs) NUMERICAL MODELLING o Geometry definition (3D CAD) o Physical/electrochemical properties definition o Discretization o Numerical calculation o Post-processing and results interpretation Software Implementation Modelling and Simulation Activities Assessment Activities Figure 3: Validation approach 5. Modelling Approach The integral formulation is done following Green s identity and the boundary discretisation to represent potential and normal current densities using collocation technique which leads to an algebraic system of equations. These can followed in detail from references [1,7,8,9]. 7

8 The Boundary Element Method has important advantages [8,9] over the more widely used Finite Element Method (FEM) approach for galvanic corrosion modelling in industrial applications. Firstly, the BEM formulation is based on the solution of the leading partial differential operator, thus improving the numerical accuracy in comparison to artificial polynomial approximations. Secondly, the mesh discretisation of the BEM model is required on surfaces only, thus avoiding volume mesh discretisation. This feature helps to decrease the computational burden, especially in complicated geometries. In addition, complex mesh generators for volumes are avoided. Thirdly, in the standard BEM potential field and potential gradient are treated as independent degrees of freedom and are both involved in the formulation, hence the outcome of the calculation is both potential fields and current densities. In contrast, the outcome of calculations based on standard FEM is the potential field so that gradients have to be calculated by differentiation of the potentials an inherently inaccurate process. Finally, the degrees of freedom are associated with potentials and current densities on the surfaces surrounding the electrolyte, rather than in the bulk of the electrolyte. This is quite appealing for electrochemical corrosion modelling where the electrolyte problem is driven by surface effects in the thin layers developed on the active electrodes while the bulk of the electrolyte satisfies the potential equation. The corresponding boundary element mesh of the model is shown in Figure 4. The discretisation mesh in the anode is more refined towards the pinhole area since the variation of potential and normal current density are both expected to be steeper in that region. 3D View Plan view Pinhole area = 20 mm 2 Figure 4: Mesh discretization of the bi-electrode GC model, viewed from below the electrodes [3] 6. Experimental Throughout this investigation for the anode, aluminium sheet alloy AA2024 unclad with milled surface was used. As for the cathode, a ground CFRP plate where the outer resin layer was removed by grinding down into the first carbon ply (~100 µm) to 8

9 achieve an almost pure carbon surface. All carbon fibres were eclectically connected by silver glue at the cut edges. The electrochemical properties for the CFRP have been found to be comparable to the behaviour of pure carbon plates, which indicates that the share of carbon on the surface is very high and almost % and comparable to a cutting edge situation. The experimental work consists of two stages. The first stage one involves obtaining the electrochemical properties of the AA2024 and CFRP, by means of an electrochemical cell which is a standard three electrode cell. The outcomes of this process are the polarisation curves which are used as input by the modelling tool. Figure 5 shows polarization curves obtained through experiment for AA2024 immersed in air purged electrolytes with different Chloride concentrations and conductivities. The different conductivities are corresponding with varying of the Chloride (Cl-) content: Conductivity Chloride concentration 5000 µs/cm ~ 0.05 M µs/cm ~ 0.10 M µs/cm ~ 0.60 M A representative polarisation curve measurement of CFRP (cathode) is shown (exemplarily 0.05 mol/l) in Figure 5 since here the curve is not sensitive to the electrolyte composition in the investigated range. UNCLAD AA2024 & CFRP - POLARIZATION CURVES CFRP-0.05M_5000µS/cm AA M_5000µS/cm AA M_10000µS/cm AA M_49500µS/cm 1,00E+00-1,2-1 -0,8-0,6-0,4-0,2 0 1,00E-01 Current density [A/cm 2 ] 1,00E-02 1,00E-03 1,00E-04 1,00E-05 1,00E-06 Potential [V calomel ] 1,00E-07 Figure 5: Polarisation curves of the CFRP and AA2024 samples used for the validation test. The potential is referred to the standard calomel electrode (SCE) [3] The second stage consists of experimental determination of electrochemical data which can be compared with the results of the simulation. These electrochemical data are the total current flowing between anode and cathode, and the potential field 9

10 measurements in the electrolyte close to anode and cathode. A schematic drawing of the validation device is shown in Figure 6. A switching device is used for monitoring of the potential in the electrolyte which is a voltmeter in this case. The AA2024 (anode) is insulated from the CFRP (cathode) sample. The short cut is established through the current measurement device. The total current flowing between anode and cathode is determined in the external circuit. The value of the potential in relation to the sample is determined. V O L T M E T E R V x Anode ELECTROLYTE REF. ELECTRODE + CAPILLARY I T Cathode h e COMPUTER (Switching Device, Data Analysis, Documentation & Storage) POTENTIOSTAT x z y x Figure 6: Schematics of the experimental validation setup [3] Basically, from this experimental setup the following experimental parameters can be varied: Height of the electrolyte (h e ) Composition of the electrolyte (conductivity, Chloride (Cl - ) concentration) Agitation of the electrolyte (here air purged, stirred) with a porous rubber tube. However, in this work the height of electrolyte, h e is kept constant at 5 cm. In both two stages the electrolyte was constantly air purged and stirred in order establish homogeneous flow condition and oxygen aeration. 7. Results 7.1 Total Current In general, comparisons for electrolyte potential and total current are made between experimental and modelling results for all the ten case scenarios shown in Table 1. The variation of total current with respect to pinhole distance from cathode, (Xt) is shown in Figure 7. Basically, this curve represents the cases 1 to 3. The figure shows a comparison between the experimental measurements and the modelling results 10

11 employing the polarisation curves shown in Figure 7. It can be observed that when the conductivity is medium i.e µs/cm, the total current is practically almost unaffected by the location of the pinhole for the short distance within the experimental scale. Total Current vs Distance (Xt) -C/A Ratio=100; σ=5000µs/cm 4,00E-04 Total Current [A] 3,50E-04 3,00E-04 2,50E-04 2,00E-04 1,50E-04 1,00E-04 EXPERIMENTAL MODELLING 5,00E-05 0,00E Xt [cm] Figure 7: Comparison of modelling results against experiment for the variation of total current in function of the distance (Xt) [3] Total Current [A] 5,00E-04 4,50E-04 4,00E-04 3,50E-04 3,00E-04 2,50E-04 2,00E-04 1,50E-04 Total Current vs C/A Ratio - Xt=13cm EXPERIMENTAL (σ=10000µs/cm) EXPERIMENTAL (σ=5000µs/cm) MODELLING (σ=10000µs/cm) MODELLING (σ=5000µs/cm) 1,00E-04 5,00E-05 0,00E C/A Ratio Figure 8: Comparison of modelling results against experiment for the variation of total current in function of the C/A ratio [3] Figure 8 shows cases 4 to 10 where the variation in total current against C/A ratio for the conductivities 5000 µs/cm and µs/cm can be seen. In general, the 11

12 modelling results show an increasing trend as the C/A ratio increases which is also the case with experimental results and also the theory. This is because as the cathodic area increases compared to anodic area, more electrons are consumed at the bigger cathode through the oxygen reduction reaction. Also as expected, an increase of electrolyte conductivity translates into an increase of total current. Figure 9 shows the galvanic corrosion area from the validation experiment and modelling (current density distribution) for case 4. Jnormal (+ == OXIDIZING) a) b) Figure 9: Comparison of the galvanic corrosion area for the a) validation experiment for Case 4 and the b) BEM model (current density distribution) [3] 7.2 Potential Distribution This potential difference between cathode and anode is the actual driving force of the galvanic effect. Figure 10 is from the modelling where it shows the potential distribution on the sample and also in the electrolyte for case 4. The dotted line along the electrodes indicates the points or path considered for measuring potential distribution during validation experiment and also in modelling for comparison purposes. These comparison results for all the considered cases are reflected in Figure 11 respectively. 12

13 VOLTAGE IN ELECTROLYTE Figure 10: Contour plot of potential distribution on the electrode surfaces and in electrolyte obtained by the simulation particularly for Case 4 [3] Figure 11 shows the variation of electrolyte-to-sample potential along the x coordinate for each case scenario. The blue curves indicating error with a cross symbol on the graphs (ELECTROLYTE POTENTIAL [V] vs. X [cm]) correspond to the experimental measurements at 3 mm or 1.5 mm from the surface, red continuous lines corresponds to simulation results also at 3 mm or 1.5 mm from the electrodes and green dots indicate the surface potential from the simulation. The reference electrode considered is saturated calomel electrode (SCE). pinhole cathode C/A=100 Xt=7cm σ= 5000µS/cm C/A=100 Xt=13cm σ= 5000µS/cm 13

14 C/A=100 Xt=18cm σ= 5000µS/cm C/A=100 Xt=13cm σ= 10000µS/cm C/A=150 Xt=13cm σ= 10000µS/cm C/A=200 Xt=13cm σ= 10000µS/cm C/A=50 Xt=13cm σ= 5000µS/cm C/A=100 Xt=13cm σ= 5000µS/cm 14

15 C/A=150 Xt=13cm σ= 5000µS/cm C/A=200 Xt=13cm σ= 5000µS/cm Figure 11: Potential measurement against distance in x-direction for case 1-10 (see Figure 10) The main point of interest here in the potential distribution comparison between experimental and modelling values is the relative potential values or in other words, the maximum potential difference. Besides, another point to note here is that the software BEASY successfully captures the effect of solution resistance or IR drop in the electrolyte which happens when the potential is calculated at any discrete positions within the electrolyte i.e. Z=1.5 mm or 1.3 mm from the surface in this case. This actually gives good agreement to the actual potential drop which is detected during the validation experiment since potentials were measured at the distance of Z=1.5 mm or 1.3 mm as well from the surface. 8. Summary An effective galvanic corrosion model was successfully setup to study corrosion rate under different scenarios of protective coatings. The BEM based simulation results based on the BEASY program can reasonably predict the galvanic current and potential distribution for AA2024/CFRP combination with surface protections in NaCl solution. The simulation results for a number of sets of experimental measurements corresponding to three different case scenarios i.e. effect of distance, Xt, effect of conductivity variation and effect of area ratio of cathode/anode have been successfully corroborated with experimental measurements. The comparison involved total current flowing between anode and cathode, and electrolyte potential at different points in the electrolyte along the specimen. 9. Conclusion In conclusion, the accuracy of the computational modelling is critically dependent on the accurate characterizations of the polarization response. The agreement between simulated results and experimental data from total current measurements is good in all cases. On the other hand the matching of results for total current improves with decrease of C/A ratio at higher conductivity. Besides, it can be observed that for electrolyte thickness of 5 cm and for medium conductivity i.e µs/cm, the total current is practically almost unaffected by the 15

16 location of the pinhole for the short distance within the considered experimental scale. 10. Acknowledgement This work is supported by the Six Framework Programme for Research and Development of the European Commission in the Specific Targeted Project SICOM, Priority 4, Aeronautic and Space ; Project No.: AST5-CT SICOM. 11. References [1] A.Peratta, T.Hack, R.Adey, J. Baynham, H.Lohner, Eurocorr (2009). [2] T. Grytsenko, A. Peratta. Adaptive cross approximation based solver for boundary element method with single domain in 3D. Boundary Elements and Other Mesh Reduction Methods XXX. WIT Transactions on Modelling and Simulation, (2008). pp [3] S.Palani: Modelling and Simulation of Impact of Surface Protection on Galvanic Corrosion of Al/CFC Combinations, MSc. Thesis, Munich, (2009). [4] Robert A. Adey and Seyyed Niku. Computer Modelling of Galvanic Corrosion, in Galvanic Corrosion. Harvey P. Hack, editor. ASTM Committee G-1 on Corrosion of Metals. ASTM International, 1988 [5] Pierre R. Roberge. Corrosion Engineering. Principles and Practice. McGraw-Hill (2008) [6] BEASY software user guide, Computational Mechanics BEASY. Version 10. Southampton, UK, (2009). Available at: [7] Adey, R. A., and Niku, S. M.: Computer Modelling of Corrosion using the Boundary Element Method, Computer Modelling in Corrosion. ASTM STP 1154 pp (1992) American Society of Testing and Materials, Philadelphia, 1992 [8] C.A. Brebbia, J.C.F. Telles and L.C. Wrobel. Boundary Element Techniques Theory and Application in Engineering. Springer Verlag Berlin, Heidelberg NY, Tokyo. (1984). [9] C. Brebbia and J. Dominguez. Boundary Elements, An Introductory Course 2 nd ed. Computational Mechanics Publications, McGraw-Hill. NY, Colorado, San Francisco, Springs Mexico, Montreal, Oklahoma City, San Juan, Toronto (1992) 16