CORROSION MODELING FOR LIFE PREDICTION April 2010, Rome Validation of a Galvanic Corrosion Computer Model for AA2024 and CFRP with localised damaged coatings Andres PERATTA 1 , Theo HACK 2 , Robert ADEY 3 , Siva PALANI 4 , John BAYNHAM 5 , Hubertus LOHNER 6 (1) CM BEASY, UK, [email protected](2) EADS, Germany, [email protected](3) CM BEASY, UK, [email protected](4) EADS, Germany, [email protected](5) CM BEASY, UK, [email protected](6) AIRBUS, Germany, [email protected]
20
Embed
Validation of a Galvanic Corrosion Computer Model …...CORROSION MODELING FOR LIFE PREDICTION April 2010, Rome Validation of a Galvanic Corrosion Computer Model for AA2024 and CFRP
This document is posted to help you gain knowledge. Please leave a comment to let me know what you think about it! Share it to your friends and learn new things together.
Transcript
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
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