1. Aircraft Corrosion Maintenance and Sustainment
Luna Innovations Incorporated 
Office
Fritz Friedersdorf
5 October 2017

2. Issue of Corrosion for DoD Aviation
Corrosion increases costs and reduces availability of DoD aviation systems
$2.6 billion cost of corrosion for Navy and Marine Corps aviation (LMI 2011)
25% of maintenance costs / 25 days of corrosion-related non-availability per year
$4.5 billion cost of corrosion for Air Force aircraft and missiles (LMI 2012)
24% of maintenance costs / 15.9 days of corrosion-related non-availability per year
Corrosion management and sustainment for DoD aircraft is schedule based
Wash cycles are set by corrosion severity zones (TO )
Severe (30 days) / Moderate (90 days) / Mild (180 days)
There is a desire within DoD to implement CBM for improved corrosion prevention and control

3. Aircraft Corrosion Health Monitoring
Individual Aircraft Tracking
Measure corrosion severity
Detect upset conditions
Predict time to next inspection
Schedule preventive maintenance
Establish long term trends
Manage inspections and maintenance processes
Perform load leveling among aircraft
Examine fleet wide trends for life cycle sustainment
Validate usage assumptions
Optimize availability and life cycle costs
Fleet Management

4. Aircraft Environment and Corrosivity Measurements
Corrosion prediction requires inputs, models, and actionable outputs that can be used by maintainers
Aircraft corrosion monitoring systems quantify:
Environmental parameters (environmental severity)
Corrosion rate of surrogate materials (corrosivity)
Sensors for use in environment and corrosivity measurements have been standardized
Electrochemical sensors are compliant with ANSI/NACE Standard TM
Currently a new work item within ISO

5. Corrosion Prediction
Historically, environmental severity and corrosivity are measured by average environmental conditions and/or mass loss coupons
ISO Corrosivity of atmospheres - Classification, determination and estimation
Environmental parameters of significance
Relative humidity
Time of wetness
Amounts of corrosive contaminants
Temperature
Location based average conditions have limited utility for individual aircraft tracking and fleet management
Recent efforts have focused on continuous, dynamic measurements and models to predict corrosion rate

6. Aircraft Monitoring Systems
Aircraft sensor nodes include environmental and corrosivity sensors
RH and air temperature sensor
Combined sensing elements with digital output
Surface temperature sensor
RTD embedded within node enclosure material
Conductance (salt contaminants)
Gold IDE
Aluminum free corrosion rate
Aluminum alloy interdigitated electrode (IDE)

7. Monitoring System Correlation to Mass Loss
Corrosion rate sensor output is strongly correlated to mass loss coupon measurements
AA7075-T6 mass loss coupons with / A286 SS fasteners
45-day GMW14872 accelerated test
Both sensor and mass loss coupon response exhibit power law behavior

8. Predictive Modeling ANN
Instantaneous corrosion rate is dependent on environmental conditions
Non-linear / Interaction effects / Hysteresis
Environmental parameters can be used to predict corrosion rate
ANN

9. Corrosion monitoring system data within HH-60, Patrick AFB, FL
Upset Conditions
Deviation of aircraft environment from predicted conditions can be an indication of operational or maintenance issues
Isolated instances where aircraft humidity is much higher than expected humidity based on local NOAA data
Corrosion monitoring system data within HH-60, Patrick AFB, FL

10. Aircraft Operation
High altitude flight cold soaks the structure, and upon landing in a high humidity climate, condensation causes high corrosion

11. Summary
The is a significant need for improved aircraft corrosion maintenance and sustainment
Standardized measurement methods for atmospheric corrosion monitoring are available
Machine leaning techniques may be useful for corrosion prediction
Individual aircraft monitoring can be used to quantify the effect of upset conditions and operations
Successful CBM will depend on the integration of monitoring systems, predictive models, and network systems
Output must be informative to maintainers