Sensing to Measure and Validate Corrosion in Naval Systems - STTR Topic DON26TZ01-NV012

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This topic was temporarily posted by the Department of War SBIR Program on March 2nd 2026 and removed the following day.
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Funding Amount:

Est. $240,000

Deadline to Apply:

Est. April 29th, 2026.

Objective:

Develop and deliver a sensory tool that can be used to monitor and assess several modes of corrosion activity as a function of time within Navy ship systems and subsystems. The sensory tool will incorporate artificial intelligence (AI) identify and estimate component life in a given platform/system for a given material selection, CAD geometry, and environment during the ship operations. AI can incorporate a set of mathematical models that will detect when the error happens and when to do maintenance. The main objectives of AI are to reduce maintenance time, production downtime, and the cost of component supplies.

Description:

It is increasingly important for corrosion rate analysis to be performed on steel structures such as ships, offshore platforms and bridges to determine their safe operating life and for the development of effective and efficient maintenance practices. Optimal timeframes for asset availability and for planned redundancy also demand information about corrosion rates. Corrosion loss affects the effective load capacity of steel plating through causing plating thickness loss. The design of steel ships typically incorporates a corrosion allowance, i.e., an amount of corrosion loss that can be tolerated before the structural system is considered compromised. Corrosion protection measures include paint coatings and sacrificial anode systems for immersed areas. However, these methods are not always wholly effective, and continual maintenance usually is required but not always applied. In extreme cases, repair and replacement of structural details may be necessary, incurring very considerable cost penalties due to direct repair costs. It follows that the estimates of the expected rate of deterioration are important inputs for optimal maintenance and repair decisions for ships.

Naval ships are exposed to a range of corrosive environments and as a result the patterns of corrosion vary widely. The structural details and the orientation and position within the space within a given environment also will cause different corrosion patterns and rates. For immersion environments, influences on corrosion include chemical factors such as salinity, oxygen content, pH, and presence of pollutants; physical factors such as temperature and pressure; and biological factors such as bacteria and biomass. For ballast tanks the immersion environment usually is considered the most critical but in modelling the corrosion process attention might also need to be given to the occurrence of repeated wet/dry cycles as a result of the tanks being filled and emptied to adjust the freeboard trim of the ship. In addition, the presence of sacrificial anodes may have some influence, although they are effective only under immersed conditions and for uncoated areas. Thus, a de-ballasted tank will not be protected. It follows that the amount of corrosion in a ballast tank is a function of the environment, the type of corrosion protection, and the tank status. Apart from corrosion protection and operational practices, the main influence on the environmental parameters is the result of the conditions encountered during operations – what might be called the trading route, including geographical influences.

The number of hours a ship is generally in an operating or training status have decreased. Navy corrosion maintenance costs continue to escalate, reaching upwards to nearly $10B/year. Roughly 40% of those costs are caused by corrective maintenance that can be attributed to the improper selection of materials, usually from design process decisions that addressed system requirements without considering materials corrosion behavior in environments for which they are planned.

The application of a resistant coating on ships, offshore structures, and pipelines is the primary prevention method of corrosion wastage in the marine industries. To guarantee coating integrity and to be able to thoroughly survey for corrosion wastage on marine structures, new advanced nondestructive methods are being sought. The requirements of convenient and rapid determination of corrosion wastage on coated structures, even in the difficult spatial positions of the structure, will require advanced technologies which are being developed for other industries that also require very high structural integrity. Corrosion detection and monitoring are essential diagnostic and prognostic means for preserving material “health” and reducing life-cycle cost of industrial infrastructures, weapon systems, ships, aircraft, ground vehicles, pipelines, etc.

Sensor system attributes of small size, low weight, open plug-and-play interface architecture, self-diagnostics and validation make this a valuable interface and controller platform for other industrial and military monitoring applications. The system simplicity and low cost allows for wide area coverage by monitoring multiple sites on an individual structure and for fleet-wide vehicle condition monitoring. Other than Military vehicles, the smart sensor system has market potential in stationary structures, industrial processes, and civil and commercial transportation. By collecting and consolidating datasets into a fleet management system, DOW can better allocate maintenance resources and increase availability and service life objectives for these platforms. The collected data drive sustainment analytics and fleet management by increasing the accuracy of predictive maintenance schedules and decreasing inspection intervals and unnecessary preventative maintenance.

Artificial Intelligence (AI) plays a pivotal role in interpreting the vast amounts of data collected by drones. Machine learning (ML) algorithms analyze the images to identify patterns of corrosion, thereby enabling more accurate and timely maintenance decisions. This level of automation reduces human error and ensures that Navy vessels remain in optimal condition. AI is a machine’s capability to impersonate human behavior, respond perceptively, solve problems, and make decisions automatically without human interference or with less human interference. The main objective of AI research involves general intelligence, automated planning, perception, natural language processing, knowledge representation, and robotics.

Who will win?

If you can achieve the objective above better than any other company on the market, you have a very high-likelihood of success and should apply.

Who is eligible to apply?

Any company that meets the following criteria:

• For-profit company

• U.S.-owned and controlled.

• 500 or fewer employees (including affiliates)

How Can BW&CO Help?

1) End-to-end support including, strategy, writing of the full proposal, and administrative & compliance support.

2) Proposal strategy and review.

3) Administrative & compliance support.

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