Enabling Digital Twin Life Prediction for Combined Effects of Atmos. Corrosion and Corrosion Fatigue
Abstract
Approved for Public ReleaseThe objective is to combine experimental and modeling approaches to 1) understand and predict the combined effects of atmospheric environmental exposure variables and fatigue damage on the evolution of failure from corrosion and corrosion fatigue (CF), 2) develop a capability to predict the dominant corrosion related failure mechanism, be it corrosion alone or initiation and growth of a CF crack, and 3) predict the environmental parameter(s) that are the strongest contributors to failure. This will be done through 1) experimental quantification of the effects of environmental variables (relative humidity (RH), temperature (T), ultraviolet light (UV), ozone, and salt load density) on CF of AA7075-T6, 2) utilization of the literature available on CF and atmospheric corrosion of AA7075-T6, and 3) leveraging all data with science-guided modeling approaches to develop a digital twin for combined effect failure where atmospheric corrosion and fatigue are the focus. The long-term/overarching aims of this work are to a) understand differences between conventional environment assisted cracking testing environments and atmospheric environments more typical for aerospace service, b) inform understanding of complex atmospheric environmental component interactions in complex natural environments, and c) develop a digital twin that can predict corrosion and CF in aerospace relevant environments to advance structural integrity modeling. To accomplish the above goals and objective, four specific task areas will be pursued. Task 1 will control each variable individually and systematically to allow quantitative assessment of the impact of each individual variable on corrosion and CF crack growth. Task 2 will combine environmental variables in similar mechanical testing environments to Task 1 to determine the effect of interactions between environmental inputs on crack propagation. Both Tasks 1 and 2 will work with NRL and NRL Key Westoutdoor EAC testingfacility (C-Coast) to obtain CF data during outdoor coastal testing for model validation. Task 1 and 2 data, along with data from NRL Key West, will be collected and used in Tasks 3 and 4 to construct a probabilistic model for the cause-consequence relationships that exist between environmental variables and fatigue degradation. In Tasks 3 and 4, the probability distributions and cross-probability tables will be integrated into a holistic predictive model using the Bayesian network approach, which linkscause and consequence nodes defining the relations between environmental parameters and localized corrosion and/or CF.The proposed research will provide positive impact to the Navy by 1) advancing current structural integrity life prediction methods through creation of a digital twin that can predict corrosion and the onset of cracking for the combined effects of fatigue loading and atmospheric environmental exposure experienced in aerospace service, 2) provide critical knowledge on the appropriateness of currently utilized environment assisted cracking environments, and 3) generate knowledge on the atmospheric variables (surface salt(s), RH, T, UV, ozone, etc) that are most critical in failure. This research will help with aircraft and other sea-based asset sustainment as there will be improved understanding regarding how various service environments will exacerbate corrosion and CF damage allowing for adjustments in mitigation activities. Likewise, the ability to tailor these variables to service conditions will allow for improved damageassessment.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Jun 13, 2024
- Source ID
- N000142412396
Entities
People
- Jenifer Locke
Organizations
- Office of Naval Research
- Ohio State University
- United States Navy