(Invited) Replicating the Corrosion Behavior of Steel and Aluminum Alloys at a Coastal Exposure Site: Using an Accelerated Combined-Effects Chamber Simulation (ACES) for Improved Laboratory Corrosion Testing

Abstract

Listen

Translate article

Although there are numerous test methods for exposing bare and coated metals in a controlled, corrosive environment to determine relative corrosion resistance and coating behavior, the prediction and correlation of corrosion performance of “accelerated exposure tests” in environmental chambers like salt spray (B117) to field environments are not always straightforward. Existing test methods do not address the simultaneous exposure of various atmospheric and environmental conditions that can affect corrosion performance of a bare or coated metal or correlate results of exposure chamber tests with exposure to outdoor atmospheres and with end-user performance. Many investigations have been performed in recent years to clarify the role of environmental and climatic factors in the atmospheric corrosion of commonly used structural metals and coatings as well as simulate their observed corrosion behavior in the laboratory.The first step toward developing better accelerated test methods is to analyze and accurately reproduce these environments in a laboratory setting. To achieve this goal, a new state-of-the-art accelerated combined effects simulation (ACES) exposure chamber has been developed and has undergone testing by the U.S. Air Force Research Laboratory (AFRL) in collaboration with the U.S. Naval Research Laboratory (NRL) to replicate field conditions and corrosion behavior of various alloys, coating systems, and corrosion/environmental sensors. This chamber was built to include more environmental effects than any previous exposure chamber to accurately mimic a field environment that includes temperature and humidity control, ultraviolet (UV), mixed gasses, and actuators to simulate mechanical stresses.The long term objective of this effort was to develop a better method to categorize the environmental severity of field exposure sites in terms of corrosion attack, which will aid in the design of accelerated laboratory test protocols and lifetime prediction for bare metal substrates in coastal environments. Measurements included site specific weather parameters, mass loss of 1018 steel, AA2024-T3 and AA7075-T6, the corrosion characteristics of uncoated aluminum alloys AA2024-T3 and AA7075-T6, and the resulting environmental deposition of salts onto the aluminum alloy exposure coupons.In the present work, the ACES was used to simulate a 90 day exposure environment of bare metal coupons at the NRL-Key West (NRL-KW) outdoor exposure facility (Key West, FL) as well as an “accelerated” version of the environmental exposure period. The resulting corrosion behavior of bare steel and aluminum alloy coupons in the chamber were compared to identical samples exposed at the NRL-KW facility. It was determined that the exposed steel and aluminum alloy coupons in the ACES chamber exhibited statistically similar values in terms of mass loss (Figure 1), and other corrosion parameters such as thickness of material lost, maximum pit depth, pit coverage and pit density to that determined from identical coupons exposed in the field. In addition, scanning electron microscopy and energy dispersive spectroscopy (SEM-EDS) of elemental surface contamination through deposition from salt spray deposits on the field exposed samples were somewhat similar to the ACES chamber exposed samples.The ability to accurately replicate an exposure environment for materials corrosion testing would provide a significant research development and testing platform for bare and coated materials exposed to environments that are variable in nature. The intent of the test protocol is to be specific to a particular exposure environment or dynamically “tunable” to match the particular environment in which the coating or alloy substrate is intended to be used in service. Any test protocol developed using this system could allow a reasonable prediction of performance lifetime based upon an accelerated test in a relatively short timeframe. Figure 1