TECHNICAL POINT OF CONTACT (TPOC)
Jonathan Sides
Nicole Adcock
John Colbert
PROJECTED CMMC LEVEL REQUIREMENT
Level 2 (Self)
TECHNOLOGY AREAS
None
MODERNIZATION PRIORITIES
Trusted AI and Autonomy
KEYWORDS
FOD; Facilities; Pavement; Digital Airfield; Artificial Intelligence/Machine Learning; AI/ML; Infrastructure
OBJECTIVE
Develop a continuous, sensor-based inspection solution that provides real-time data on airfield surface conditions and Foreign Object Debris (FOD) risks, with outputs that support established airfield assessment practices (e.g., Pavement Condition Index (PCI) and alignment with applicable ASTM/FAA standards, without prescribing specific report formats or alerting implementations.
DESCRIPTION
Develop a sensor-based system to inspect and analyze airfield surfaces. The system will be evaluated on its ability to reproduce the Pavement Condition Index (PCI) consistent assessments, aligned with ASTM D 5340 and applicable FAA Advisory Circular guidance, as currently used by airfields and funding sponsors to prioritize airfield maintenance and repair activities related to FOD generation. The system will also be evaluated on its ability to detect, identify, and distinguish airfield surface features, including pavement markings, vegetation, and debris (FOD).
Any system developed must be capable of operating persistently without interfering with airfield operations. For the purposes of the topic, without interfering is defined as operating in a manner that does not require additional runway, taxiway, or apron closures; does not introduce operational delays; and does not increase operator burden. Any platform utilized must also be capable of transitioning to an autonomously operated system that can be integrated into a larger airfield management digital architecture, beginning the FOD Operational Decision Network.
PHASE I
For a Direct to Phase II topic, the Government expects that the small business will have accomplished the following in a Phase I-type effort and developed a concept for a workable prototype or design to address, at a minimum, the basic requirements of the stated objective above. The following actions would be required to satisfy the requirements of Phase I:
This portion of the work will focus on sensor development and qualification. The system must be able to quantify probability of detection to identify, distinguish, and quantify PCI features within a 95% confidence interval.
- Identify PCI elements and current measurement techniques
- Develop sensors capable of measuring PCI features
- May utilize existing and available data and/or Artificial Intelligence (AI)/Machine Learning (ML) to categorize features
- Define a method for measuring performance of sensors (e.g., did you detect all flaws/features? Are you able to accurately quantify the magnitude of each feature?)
- Distinguish PCI features from markings, vegetation, FOD, etc.
FEASIBILITY DOCUMENTATION: Offerors interested in participating in Direct to Phase II must include in their response to this topic Phase I feasibility documentation that substantiates the scientific and technical merit and Phase I feasibility described in Phase I above has been met (i.e., the small business must have performed Phase I-type research and development related to the topic NOT solely based on work performed under prior or ongoing federally funded SBIR/STTR work) and describe the potential commercialization applications. The documentation provided must validate that the proposer has completed development of technology as stated in Phase I above.
PHASE II
Integrate sensors that were developed in a Phase I-type effort into a system capable of operating on an active airfield. Ensure that the system is capable of evaluating defined airfield pavement sections and identifying all Pavement Condition Index (PCI) distress features across 100% of the accessible inspected area. Inspection boundaries should be defined by the airfield pavement section limits provided for demonstration. Inspection frequency should be sufficient to support repeatable PCI evaluation and maintenance prioritization. For areas that are inaccessible due to operational, safety, or physical constraints, the system should document coverage gaps and demonstrate an acceptable method for accounting for these areas in the resulting PCI assessment. Demonstrate that the dataset can be evaluated to reproduce a PCI report for a pavement section for both asphalt and concrete (as defined by the American Society for Testing and Materials (ASTM) standard in the references).
Include in the dataset examples of all features defined in the PCI. (Note: If a single section does not contain examples of all features, multiple sections can be used.)
Include the following key elements:
- Integration into a platform capable of operating on an airfield
- Creation of a new pavement evaluation method that contains sufficient data to also produce a legacy PCI report
- Production of near real-time pavement condition updates based on scan periodicity
- Integration with FOD data systems and digital twins
Prepare a Phase III commercialization/transition plan.
PHASE III DUAL USE APPLICATIONS
Integrate the technology into the larger FOD System-of-Systems managed and funded within Naval Air Warfare Center Aircraft Division (NAWCAD). The Department of Navy (DON) Zero FOD program is the primary transition partner, but this system will produce information that will inform facilities requirements (e.g., Naval Facilities Engineering Systems Command (NAVFAC), Marine Corps Installations Command (MCICOM), Commander, Navy Installations Command (CNIC)).
Airfield recapitalization is an aviation industry problem, with the civil aviation community facing the same challenges as the Department of War (DoW). A comprehensive, automated evaluation of pavement surfaces coupled with a risk-based approach addresses the Federal Aviation Administration's (FAA) mandate to produce 40-year pavement surfaces. These tools will also facilitate prioritization of FAA Airport Improvement Program (AIP) funds that are used to recapitalize civil aviation airfields. The Zero FOD program is in direct coordination with the FAA and DOW facilities commands to develop an operational condition index that is based on the data this project will develop.
REFERENCES
AC 150/5380-6C - Guidelines and Procedures for Maintenance of Airport Pavements. Federal Aviation Administration, 2014. https://www.faa.gov/documentLibrary/media/Advisory_Circular/150-5380-6C.pdf
AC 150/5380-7B Airport Pavement Management Program (PMP). Federal Aviation Administration, 2014. https://www.faa.gov/documentLibrary/media/Advisory_Circular/150-5380-7B.pdf
AC 150/5370-10H Standards for Specifying Construction of Airports. Federal Aviation Administration, 2018. https://www.faa.gov/documentLibrary/media/Advisory_Circular/150-5370-10H.pdf
ASTM D - 5340 Standard Test Method for Airport Pavement Condition Index Surveys. Advancing Standards Transforming Markets International. https://store.astm.org/d5340-20.html
Shahin, Mohamed Y. Pavement Management for Airports, Roads, and Parking Lots. Springer, 2006. https://www.amazon.com/Pavement-Management-Airports-Roads-Parking/dp/0387234640
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