- Program Areas
- Installation Energy and Water
- Environmental Restoration
- Munitions Response
- Resource Conservation and Resiliency
- Weapons Systems and Platforms
- Energetic Materials and Munitions
- Noise and Emissions
- Surface Engineering and Structural Materials
- Fuels and Greenhouse Gases
- Lead-Free Electronics
- Waste Reduction and Treatment in DoD Operations
Multi-modal Corrosion Solutions for Aircraft Structures
Dr. Christine Sanders | Naval Research Laboratory
The environmental and mechanical loading conditions govern the overall lifetime survivability and maintenance cycles of protective coatings. A model that can better predict maintenance based on accumulated damage will enable maintenance cycles to be performed only when necessary as opposed to overly conservative periodic time-based maintenance intervals based on worst case scenarios. Using a Condition Based Maintenance Plus (CBM+) approach reduces the exposure of both personnel and the environment to hazardous paint strippers and hexavalent chromium used in many primers. By evaluating each asset based on service history and expected future exposure, maintenance will be done when required based on usage/exposure history. To achieve the desired state, there is a need to develop better modeling of coating and material lifetime performance. Furthermore, a combined model real-world fatigue and corrosion damage for Department of Defense (DoD) assets does not exist. By generating data which simulates a real-world environment and inputting this information into a predictive model, better decisions can be made as to the service intervals and reducing the amount of man-hours spent on systems with potentially hazardous materials to refurbish the asset. Additionally, the overall approach is generalizable and can be extended to other coating systems based on additional characterization data.
The objective of this project is to generate a Bayesian network model to predict coating performance and lifetime based on a CBM+ approach.
Physics-based models will be used to supplement the Bayesian model and will provide more thorough examinations of the key contributors to atmospheric corrosion and coating degradation. Data input into the model will begin with known degraders of system life performance and then will be refined by datasets generated by combined mechanical and environmental exposure tests. The model will incorporate cumulative damage from aged specimens from both the Air Force and Naval Air community.