Post on 23-Apr-2020
CORROSION MODELING FOR LIFE PREDICTION
April 2010, Rome
Validation of a Galvanic Corrosion Computer Model for AA2024 and CFRP
with localised damaged coatings
Andres PERATTA1, Theo HACK2, Robert ADEY3, Siva PALANI4, John BAYNHAM5, Hubertus LOHNER6
(1) CM BEASY, UK, aperatta@beasy.com
(2) EADS, Germany, theo.hack@eads.net
(3) CM BEASY, UK, r.adey@beasy.com
(4) EADS, Germany, siva.palani@eads.net
(5) CM BEASY, UK, j.baynham@beasy.com
(6) AIRBUS, Germany, hubertus.lohner@airbus.com
CORROSION MODELING FOR LIFE PREDICTION - ROME 2010
OUTLINE
• Objectives
• Conceptual model and methodology
• Governing equations
• Computational model
• Case Studies– Bare Samples
– Local damage in protective layer
• Conclusions
CORROSION MODELING FOR LIFE PREDICTION - ROME 2010
OBJECTIVES
• The aim of this work is to develop and validate a
computational model for galvanic corrosion (GC) in
macroscopic scale for typical case scenarios appearing in an aircraft environment
• The present work is based on the study of a planar bi-
material GC model composed of AA2024 and CFRP
CORROSION MODELING FOR LIFE PREDICTION - ROME 2010
VALIDATION APPROACH
Validation experiment� Measurement of polarisation
curves of the electrodes involved
� Measurement of potential field in the
electrolyte by scanning reference
electrode
� Measurement of total current
between anode and cathode
Numerical modelling� Geometry definition (3D CAD)
� Definition of physical/electrochemical
properties
� Mesh generation
� Numerical calculation (BEM, bottom-up
approach)
� Post-processing & results interpretation
• Results comparison
• Predictive and sensitivity analysis
Co-planar
Bi-material
GC model
CORROSION MODELING FOR LIFE PREDICTION - ROME 2010
ADVANTAGES OF BEM FOR GC MODELLING
• BEM is based on the solution of the leading PDE, i.e. the exact solution of the Laplacian operator is used.
• The mesh discretisation is required on surfaces only (i.e. volumetric meshes are avoided), thus allowing the method to dealmore efficiently with complicated geometrical situations in the pre-processing stage.
• Potential and gradients are treated as independent DOF and are both involved in the formulation. In this way, the current density and electric field vectors are not numerically differentiated from a potential field, but directly introduced in the modelling as new DOF. This feature introduces an additional bonus in terms of numerical accuracy.
• DOF are associated with physical quantities on surfaces where most of the interesting physical processes occur, rather than in the bulk of the electrolyte, where the numerical solution is usually known.
BEM = Boundary Element Method; PDE = Partial Differential Equation; DOF = Degree of freedom;
CORROSION MODELING FOR LIFE PREDICTION - ROME 2010
COMPUTATIONAL MODEL
Electrolyte: 30 x 14 x He cm
Mesh
~2000 elements
~5000 Nodes
AA2024GAP
CFRP
Variable
Electrolyte Height Paint
CORROSION MODELING FOR LIFE PREDICTION - ROME 2010
COMPUTATIONAL MODELLING
• Polarisation curves
• Electrolyte
conductivity
• Model geometry
• Electrical circuit
defined between
electrodes
• Electric currents and
potential on the sample
and in the electrolyte
• Metal voltages
• Electrode potentials
• Total currents flowing
through the wires
INPUT DATA OUTPUT DATA
CORROSION MODELING FOR LIFE PREDICTION - ROME 2010
EXPERIMENTAL WORK
• Measurement of polarisation curves (input data)
• Measurement of electric potential in the electrolyte and total current in the
bi-material coplanar galvanic corrosion cell (validation)
Increasing chloride content
Increasing chloride content
CORROSION MODELING FOR LIFE PREDICTION - ROME 2010
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0 10 20 30 40 50 60 70 80
Time [h]
Cu
rren
t d
en
sit
y [
A/m
²]
SCANNING ELECTRODE
ANODE CATHODE
V
ELECTROLYTE
SCANNING ELECTRODE
CFRP ground AA2024 milled
It
Typical measurement of total current
Experimental setup
Bare material
CORROSION MODELING FOR LIFE PREDICTION - ROME 2010
SIMULATION RESULTS
Electrolyte Potential
z
CORROSION MODELING FOR LIFE PREDICTION - ROME 2010
CASE STUDY 1 – BARE SAMPLES
• Anode: AA2024 Unclad + milled• Cathode: CFRP ground• Electrolyte (NaCl)
Jn
CFRP AA2024GAP
CORROSION MODELING FOR LIFE PREDICTION - ROME 2010
SIMULATION RESULTS
CFRP AA2024
CORROSION MODELING FOR LIFE PREDICTION - ROME 2010
MODEL vs EXPERIMENT
TOTAL CURRENT
7.01 mA6.94 mA
EXPERIMENTMODEL
t1 – t0 = 1h
CORROSION MODELING FOR LIFE PREDICTION - ROME 2010
CASE STUDY 2: COATING LOCALLY DAMAGED
ANODE (AA2024)
Coated area (blue)
Pinhole
0.5 cm
variation of cathode area
Exposed cathode(CFRP)
Masking
LaquerTape
CORROSION MODELING FOR LIFE PREDICTION - ROME 2010
COMPUTATIONAL MODEL
CFRP
INSULATING
SURFACE
COATING DAMAGE
(EXPOSED AA2024)
CORROSION MODELING FOR LIFE PREDICTION - ROME 2010
OBSERVATIONS
Varying C/A ratio
CA=100 CA=150 CA=200
CORROSION MODELING FOR LIFE PREDICTION - ROME 2010
CASE 01
CASE 02
EXPERIMENTAL & SIMULATION RESULTS
Cathodic region Anodic region
Cathodic region Anodic region
Variation
of
distance
CORROSION MODELING FOR LIFE PREDICTION - ROME 2010
COMPARISON OF TOTAL CURRENT
0.0E+00
5.0E-02
1.0E-01
1.5E-01
2.0E-01
2.5E-01
3.0E-01
3.5E-01
1 2 3 4 5 6 7 8 9 10
SAMPLE
TO
TA
L C
UR
RE
NT
[m
A]
EXPERIMENTAL
MODELLING
C/A = const
σ1 = const
Xt = const
σ2 = const
C/A
Xt = const
σ1 = const
Xt
C/A
CORROSION MODELING FOR LIFE PREDICTION - ROME 2010
SUMMARY
• Computer models have been developed, tested and compared against experimental results based on a co-planar bi-metallic arrangement
• The tests involved bare and partially coated samples of CFRP and AA2024
• The observables used for the comparison between experimental and numerical results were:– Total electric current flowing between electrodes
– Electric potential in a number of different points in the electrolyte
CORROSION MODELING FOR LIFE PREDICTION - ROME 2010
CONCLUSIONS
• Good agreement of simulation results with the experimental measurements
• For the cases considered (medium conductivity, cm scale)– Variations of the distance between pinhole and
cathode within a length scale of few centimetres did not produce a substantial change of total current.
– The cathode to anode surface ratio is a dominating parameter in the GC process
• The model forms the basis of a tool for materials testing and corrosion modelling in aerospace structures