The objective of this SON is to deliver a predictive methodology for assessing the performance of new, viable corrosion mitigation solutions – materials, metallic and organic coatings, and designs – vs. baseline technologies in complex assemblies.
Proposals should identify technology gaps associated with modeling the effect of organic coatings and potentially metallic coatings or designs. Proposals should fundamentally explain how the proposed methodology will address the gaps. This methodology should be able to predict corrosion in complex assemblies, guide redesign where necessary, and predict corrosion damage in variable severity environments. This should include development and validation of a “Department of War (DoW) standard corrosion coupon and test methodology”, or similar approach, that would allow DoW and Original Equipment Manufacturer (OEM) engineers to quantitatively compare corrosion prediction methods and mitigation solutions. This methodology should be designed in such a way that it can be used by DoW engineers in sustainment and design, but can be extended and enhanced to incorporate more specialist capabilities and data as they become available, ultimately linking corrosion with structural lifetime models to capture the effect of corrosion on lifetime reduction, stress corrosion cracking, etc.
At the present time implementation of technologies for corrosion mitigation is hindered by the cost and time involved in testing novel materials and designs relative to legacy approaches. In the short term the proposed work should provide a reliable, proven and practical methodology for predicting the performance of assemblies containing new sustainable materials and coatings relative to existing baseline materials. This would significantly reduce the cost, time and risk of evaluation and adoption.
In the long term it will provide a structure for extending corrosion modeling methods to bring corrosion prediction to a state where it will become a standard tool for use together with structural design tools.
The long-term purpose of corrosion modeling is to predict corrosion in complex assemblies with variable corrosivity experienced by DoW assets in service around the world, and interface with structural lifetime modeling to accurately capture corrosion effects on lifetime reduction. But such models far exceed current capabilities, and complex computational modeling can be used only by specialists, using data that would be far more extensive than is currently available.
Until recently, predicting corrosion of DoW weapons systems has been based on subjective (or collective) field experience. Determining actual corrosion has always required extensive corrosion testing, usually involving ASTM B117 salt fog testing as well as long-term atmospheric exposure testing, in high-corrosivity coastal locations, followed by final testing on actual assets. This approach is time-consuming and expensive, and does not provide useful predictions of corrosion behavior under the wide range of conditions experienced by weapons systems in service.
The uncertainty inherent in adopting novel technologies is magnified by the lack of a clear standard for evaluating alternative technologies or selecting the best predictive methods for assessing them.
Over the past few years various approaches to modeling corrosion have been developed, based on electrochemical mechanisms. The simplest of these approaches is the electrochemical polarization curve-crossing method introduced in MIL-STD-889D. This method is usable by any engineer, provided the electrochemical data are available, but it is limited to evaluating galvanic corrosion between two materials, and is not suitable for complex assemblies. Far more detailed and complex electrochemical computational methods attempt to take into account the varied materials, geometries, corrosion environments and corrosion mechanisms experienced by weapons systems in service. Yet, these models are typically usable only by experienced computational experts, and often require input data that is not readily available. Additionally, there are still significant gaps in the technology as even the most complex of these models rarely incorporate more than one of the various corrosion mechanisms, they do not include passive and active corrosion mitigation from the organic coating stackups, sealants, etc. used to combat corrosion in actual weapons systems, and they do not link corrosion with structural lifing modeling to capture the effect of corrosion on lifetime reduction. As such, there are significant opportunities to develop these models to be more realistic, easier to use, and enable broader impacts for DoW acquisition and maintenance communities.
The cost and time to meet the requirements of this SON are at the discretion of the proposer. Proposers submitting a Standard or Limited Scope Proposal must provide the rationale for the proposed scale. The two options are as follows:
Standard Proposals: These proposals describe a complete research effort. The proposer should incorporate the appropriate time, schedule, and cost requirements to accomplish the scope of work proposed. SERDP projects normally run from two to five years in length and vary considerably in cost consistent with the scope of the effort. It is expected that most proposals will fall into this category.
Limited Scope Proposals: Proposers with innovative approaches to the SON that entail high technical risk or have minimal supporting data may submit a Limited Scope Proposal for funding up to $350,000 and approximately one year in duration. Such proposals may be eligible for follow-on funding if they result in a successful initial project. The objective of these proposals should be to acquire the data necessary to demonstrate proof-of-concept or reduction of risk that will lead to development of a future Standard Proposal. Proposers should submit Limited Scope Proposals in accordance with the SERDP Core Solicitation instructions and deadlines.
John La Scala, Ph.D.
Program Manager for Weapons Systems and Platforms
Strategic Environmental Research and Development Program (SERDP)
