Galvanic Corrosion Prediction for Aircraft Structures

Period of Performance: 06/17/2014 - 03/04/2015

$150K

Phase 1 SBIR

Recipient Firm

Corrdesa
11 Jefferson Place Array
Newnan, GA 30263
Principal Investigator

Research Topics

Abstract

ABSTRACT: Corrdesa is validating a finite element analysis method of predicting galvanic corrosion locations and relative severity between dissimilar metals using commercially available GalvanicMaster software. This project will demonstrate that this same approach can be modified and extended to quantitatively predict corrosion rates between dissimilar materials, including metals, composites, and in Phase II anodized layers and metal-filled polymers. The methodology will be defined to acquire electrochemical data (polarization and impedance) from these materials as a function of time under well-defined conditions. This methodology will be added to our Best Practices document, and the data to our galvanic corrosion database, which together with the software constitute a galvanic prediction trade tool. Using this data we will predict the galvanic corrosion pattern ( hot spots ) and rate over time for bare 7050-T7451 aluminum against the exposed fibers of a carbon fiber/epoxy composite cross-section in a simple, well-defined, galvanic assembly. The predictions will be validated against quantitative corrosion measurements made for the assembly in a B117 test chamber, overlaying the predictions onto the assembly s CAD model, compared directly with measured material loss across its surface. In Phase II the methodology will be validated against additional materials and more complex systems. BENEFIT: The Phase I program will demonstrate that the methodology we are developing can be used for quantitative prediction, and hence for lifing. The Phase II program will develop the methodology into a quantitative galvanic prediction trade tool comprising predictive software, well-defined data acquisition methods, and the beginning of a database of reliable electrochemical data for quantitative prediction. This tool will provide OEMs with the capability of analyzing systems for corrosion in the design phase, just as they currently analyze for stress, heat flow, etc. The tool will also give DoD engineers a way to predict corrosion rates for weapons systems and define overhaul schedules to minimize corrosion risk and service failure, while maximizing on-wing time. The overall benefit to DoD of adopting these tools in both the design and sustainment phases will be a significant reduction in the $20 billion/year cost of corrosion.