BAA Topics of Interest-Amend 013 R14.pdf

BAA FAA Aviation Research 2020 Solicitation Number: 692M15-20-R-00004 R14

Federal Aviation Administration William J. Hughes Technical Center Atlantic City International Airport

Atlantic City, NJ

BROAD AGENCY ANNOUNCEMENT

AVIATION RESEARCH 2020

TOPICS OF INTEREST

May 3, 2023

The following is a list of BAA Topics of Interest of Aviation Research required by the FAA Technical Center. This BAA is an open request for white paper submittals at any time until the expiration of the BAA or until the Topic is removed. White papers and proposals will be assessed according to the instructions and criteria contained in the BAA. Offerors are invited to submit brief descriptive white papers relevant to a Topic or Topics described within the BAA. Each Topic identifies a Technical POC to whom questions relating to a particular Topic must be directed.

AVIATION RESEARCH AIRPORT PAVEMENTS (ARAP)

Topic Number: ARAP0001:

Develop Measurements, Specifications, and Guidance for Multiple Bump Events of Airport Pavement Roughness to Supplement the Existing Pavement Surface Boeing Bump Index (BBI)

Technical POCs: Richard Ji; Richard.Ji@faa.gov Matthew Brynick; Matthew.T.Brynick@faa.gov Copy: 9-ACT-AAQ-600-BAA@faa.gov

Background:

Pavement smoothness is an important consideration for airport pavement. It provides the comfort and safety of aircraft ground operations. Therefore, when pavements are put into service, the FAA recommends that airports periodically check in service roughness because the surface characteristics of a pavement affect aircraft operation cost and the riding quality.

It is because of these considerations, that technical procedures and evaluation for pavement roughness is provided in Advisory Circular (AC) 150/5380-9 Guidelines and procedures for measuring airfield pavement roughness, which references the Boeing Bump Index (BBI) for evaluation. The BBI was developed solely to identify and quantify single event in-service runway pavement roughness from acceptable, excessive to unacceptable conditions.

However the BBI does not show roughness issues caused by continuous events, which reflects the interaction between the pavement and the aircraft. Without considering it, the single bump cannot reflect the real ride quality felt by the user when the aircraft, such as when it is passing by multiple bumps caused by surface distresses, the frost heave, and runway wavelengths. The consideration of a coupled system with the runway and the aircraft in a multiple vertical bump events can reflect the real responses of the aircraft and make the airport operators correctly protect the aircraft safety and aircraft structural fatigue.

The outcome from this research effort will provide airport operators with multiple bump event surface evaluation procedures for in-service pavement roughness, as well as technical specifications to consistently conduct safe, reliable, and effective airport surface roughness inspections.

Purpose:

Develop methodologies and procedures for conducting multiple bump event based airport pavement surface roughness inspections, as well as technical criteria for acceptable, excessive, and unacceptable pavement roughness.

Requirements:

The FAA would like proposals to address the specific areas listed below; however, proposals are not limited to these requirements.

mailto:Richard.Ji@faa.gov mailto:Matthew.T.Brynick@faa.gov mailto:9-ACT-AAQ-600-BAA@faa.gov

Determine if an alternative method or index for the calculation of the roughness of in-service airport pavement is possible or necessary considering both single and multiple event bumps.

• Develop processes and procedures for analyzing multiple event bumps and develop recommended technical specifications (i.e. acceptable, excessive, and unacceptable surface roughness criteria).

• Develop a software package that considers multiple event bumps and make it available for public use.

Period of Performance/ Rough Order of Magnitude: The Period of Performance (PoP)/Rough Order of Magnitude (ROM) will be determined based on the projects proposed.

There are currently no set parameters for these elements.

Topic Number: ARAP0002: This topic has been deleted.

Topic Number: ARAP0003: This topic has been deleted.

Topic Number: ARAP0004: This topic has been deleted.

Topic Number: ARAP0005: This topic has been deleted.

Topic Number: ARAP0006: This topic has been deleted.

AVIATION RESEARCH AIRPORT SAFETY (ARAS)

Topic Number: ARAS0001: This topic has been deleted.

Topic Number: ARAS0002:

Aqueous Film-Forming Foams (AFFF) Replacement

Technical POC: Keith Bagot; Keith.Bagot@faa.gov

Title 14 CFR Part 139 (Part 139) provides regulations to airports that have scheduled operations with aircraft of 9 to 31 seats or scheduled and unscheduled operations with air carrier aircraft holding more than 30 seats. Per Part 139, certificated airports must have a certain amount of extinguishing agents on hand dependent on the aircraft activity at the airport. The main agent that Part 139 calls for airport to have is aqueous film-forming foams (AFFF). Guidance for the types of foams used at airports can be found in Federal Aviation Administration (FAA) Advisory Circular (AC) 150/5210-6D, “Aircraft Fire Extinguishing Agents”.

Over the years, there has been a growing concern about the potential health and environmental impacts of AFFF used by Aircraft Rescue and Fire Fighting (ARFF) Departments at airports and surrounding communities. Perfluoroalkyl and polyfluoroalkyl substances, commonly referred to as PFAS, are a toxic group of chemicals that are found in AFFF concentrates used at airports.

Specifically of concern are perfluorooctane sulfonate (PFOS) and perfluorooctanoic acid (PFOA). Both PFOS and PFOA are considered persistent, bio-accumulative and toxic by United States (US) Environmental Protection Agency (EPA) standards. Though foam manufactures have worked diligently to reduce presence of PFAS in their AFFF concentrates, the environmental concerns still linger. There are also several other PFAS compounds in the current AFFF formulas whose environmental and health hazards are not yet known. Recently new AFFF formulas known as Fluorine-Free Foams (FFFs) have shown potential to replace current AFFFs however; they have not been shown to have equivalent fire extinguishing capabilities.

Additionally, the FAA Reauthorization Act of 2018 enacted in October 12, 2018 stated:

Not later than 3 years after the date of enactment of this Act, the Administrator, using the latest version of National Fire Protection Association 403, ‘‘Standard for Aircraft Rescue and Fire-Fighting Services at Airports’’, and in coordination with the Administrator of the Environmental Protection Agency, aircraft manufacturers and airports, shall not require the use of fluorinated chemicals to meet the performance standards referenced in chapter 6 of AC No: 150/5210–6D and acceptable under 139.319(l) of title 14, Code of Federal Regulations.

For these reasons, the FAA’s Airport Technology Research and Development Branch (ATRD) was tasked by the FAA Office of Airport Safety and Standards with evaluating FFFs and aide in determining performance standards for FFFs to be used at airport. The FAA Technical Center broke ground on a new research facility in November 2018 with the primary focus on AFFF alternatives research testing and other ARFF technologies. Construction of this facility was completed in October 2019. One of the primary function of this facility is to find alternative firefighting agents that are environmentally friendly, while providing the same level of safety currently offered by MIL-PRF-24385 AFFF.

Purpose:

To identify potential fluorine-free firefighting agent candidates that could replace current AFFF used at airports.

The FAA would like white papers to address the specific areas listed below; however, Offerors are not limited to these requirements.

• Foams should meet standards found in MIL-PFR-24385

• Foams must have no trace of PFOS, PFOA, or any other Fluorine content

• Foams must not contain any chemicals found in the EPA’s List of Emergent

Contaminants

The FAA’s fire test facility can be used to evaluate the fire extinguishment capabilities of the foams and can be part of the proposal.

All proposed efforts should be properly documented in a detailed project plan.

Period of Performance/Rough Order of Magnitude:

The PoP/ROM will be determined based on the projects proposed. There are currently no set parameters for these elements.

Topic Number: ARAS0003: This topic has been deleted.

Topic Number: ARAS0004: This topic has been deleted.

Topic Number: ARAS0005: This topic has been deleted.

Topic Number: ARAS0006: This topic has been deleted.

Topic Number: ARAS0007: This topic has been deleted.

Topic Number: ARAS0008: This topic has been deleted.

Topic Number: ARAS0009:

Airport Unmanned Aircraft System(s) (UAS) Detection and Mitigation Research Program

Technical POC: Jim Patterson; Jim.Patterson@faa.gov

Consistent with Section 383 of the Federal Aviation Administration (FAA) Reauthorization Act of 2018 (Public Law 115-254, Oct. 5, 2018), Airport safety and airspace hazard mitigation and enforcement, the FAA is launching an effort to test and evaluate technologies and systems that detect and/or mitigate potential aviation safety risks posed by unmanned aircraft systems (UAS)1 operations in the airport environment.

Section 383(a) of the FAA Reauthorization Act of 2018 created a new § 44810 in Title 49 U.S.C.

Section 44810(a) requires the FAA Administrator to work with the Secretaries of Defense, Homeland Security, and the heads of other relevant federal departments and agencies to ensure that technologies or systems that are developed, tested, or deployed by federal departments and agencies to detect and mitigate potential risks posed by errant or hostile UAS operations do not adversely impact or interfere with safe airport operations, navigation, air traffic services, or the safe and efficient operation of the National Airspace System (NAS).

In addition, § 44810(b) requires the FAA to develop a plan for the certification, permitting, authorizing or allowing of UAS detection and mitigation systems in the NAS. Section 44810(b) requires the FAA to take certain actions as part of or potentially informing the plan, including convening an Aviation Rulemaking Committee. Further, § 44810(c) requires the FAA to test and evaluate technologies/systems that detect and/or mitigate risks posed by UAS at five airports and § 44810(d) directs the FAA to use detection and mitigation systems to detect and mitigate the unauthorized operation of an unmanned aircraft that poses a risk to aviation safety in the course of the required testing and evaluation.2

As part of this program, the FAA has issued Broad Agency Announcement (BAA) Topic Number ARAS0009 to solicit interest from manufacturers, vendors, and integrators of UAS detection and/or mitigation technologies/systems.

Purpose:

The purpose of this Topic is to identify eligible manufacturers, vendors, and integrators of UAS detection and/or mitigation technologies and/or systems in support of the FAA’s Airport UAS Detection and Mitigation Research Program, which is being carried out pursuant to 49 U.S.C. § 44810(c)-(d). For purposes of this research program:

1 See 49 U.S.C. § 44801(12) for definition of UAS.

2 The FAA was expressly exempted from various federal laws that would otherwise present legal implications associated with UAS detection and mitigation activities. See 49 U.S.C. § 44810(g). The authority conferred in § 44810(g) is limited to the testing and evaluation of UAS detection and/or mitigation technologies/systems by the FAA at five airports. This authority cannot be delegated.

1) UAS detection system refers to a system or device capable of lawfully and safely detecting, identifying, monitoring, or tracking an unmanned aircraft or unmanned aircraft system. UAS detection systems may be integrated into or be linked to counter-UAS3 systems, but, themselves, do not provide the capability to disable, disrupt, seize control, or otherwise directly interfere with UAS operations.

2) Mitigation refers to actions taken to deter, prevent, respond to, and minimize the immediate consequences of safety and security threats posed by certain UAS operations.

Mitigation may be conducted using counter-UAS and UAS detection systems, or by using other means, including efforts not reliant on these technical systems.

The FAA has a requirement to test and evaluate technologies/systems that have the ability to detect and/or mitigate UAS in the airport environment. It is important to note that the FAA will not be comparing or ranking vendors, nor is it developing a list of approved vendors as part of this research program. The FAA will be collecting data on UAS detection and mitigation capabilities and the associated impacts of these systems/technologies on the safe and efficient operation of the NAS in order to inform the additional activities required under 49 U.S.C.

§ 44810.

The FAA is seeking the submission of white papers to address the specific areas listed below;

however, submittals are not limited to these requirements:

1) UAS Detection Testing - Conduct testing and evaluation of technologies/systems to protect the air operations area (AOA)4 of an airport and as much surrounding area as possible with a general goal of reaching approximately 5 miles out from the center point of the AOA.

2) UAS Mitigation Testing - Conduct testing and evaluation of technologies/systems that offer mitigation capabilities, either as a stand-alone system or in conjunction with a detection capability, to protect the AOA of an airport.

The FAA reserves the right to pre-test mitigation technologies/systems in a controlled setting before introducing any system/technology into any airport environment for operational testing.

The selection of any offered system/technology for FAA’s research program may be denied, and testing of any selected mitigation systems/technologies may be discontinued at any stage, due to the identification of unacceptable adverse impacts or interference caused by the system/technology to safe airport operations, navigation, air traffic services, or the safe and efficient operation of the NAS.

Period of Performance (PoP)/ Rough Order of Magnitude (ROM):

The PoP/ ROM will be determined based on the projects proposed. There are currently no set parameters for these elements.

3 See 49 U.S.C. § 44801(5) for definition of counter-UAS.

4 See 14 C.F.R. § 153.3 for definition of air operations area.

Topic Number: ARAS0010: This topic has been deleted.

Topic Number: ARAS0011: This topic has been deleted.

AVIATION RESEARCH SOFTWARE & SYSTEMS

(ARSS)

Topic Number: ARSS0001:

Complex Digital Systems

Technical POC: Srini Mandalapu, Srini.Mandalapu@faa.gov Copy: 9-ACT-AAQ-600-BAA@faa.gov

Background:

Aircraft manufactures and modifiers are developing highly integrated and distributed system architectures with multiple aircraft functions. In addition, new methodologies, tools, and Artificial Intelligence/Machine Learning (AI/ML) applications are planned to be used in airborne systems. Aircraft system element development continue to evolve due to technology innovations and the desire to reduce system element development cost and time to market. Safe use of these methodologies, tools, and commercial off-the-shelf (COTS) components may not have been demonstrated in embedded aircraft equipment; which may introduce a safety risk for undetected errors with failure manifestation at the aircraft level; and may only be suitable to meet safety regulations when new, revised or additional assurance activities are also included. For example, industry is proposing to use Artificial Intelligence (AI) where little is known about the validation and verification of AI in a safety critical environment. In addition, use of autonomous (non-piloted) aircraft are also being proposed under conditions where, currently, regulations and guidance do not exist. These methodologies, individually or in combination, could introduce unknown risk if not properly addressed early in the development process.

In addition, the traditional lines of identifying issues, gaps, and assurance process approaches for aircraft systems and system element implementation continue to blur. Issues may affect both aircraft systems and system element development such that identifying and mitigating them may need to be addressed in both areas, rather than individually.

The Federal Aviation Administration (FAA) plans to conduct research to proactively address certification issues that may arise due to the introduction of new methodologies, tools, and techniques with a particular focus on Artificial Intelligence/Machine Learning (AI/ML) applications and autonomy that can potentially cause new failure conditions posed by the rapid or new and novel development processes on highly integrated and distributed systems. The research results will be used in improving the assurance standards, guidance, and training material for certification engineers and/or develop position papers for assurance needs.

Purpose:

The purpose of this Topic is to address the use of new methodologies and techniques with a focus on AI/ML in safety critical airborne systems by identifying assurance concerns, validation and verification issues/criteria, and potential mitigation techniques including run-time monitors to address risks early in the development process. Also, the FAA is studying new assurance processes that can address the safety risk that may have been introduced while mailto:Srini.Mandalapu@faa.gov implementing newer architectures, tool, and technologies. The Topic also further explores the validity of the currently-recognized development assurance standards for highly integrated and distributed systems and determine if newer development assurance approaches are needed to demonstrate compliance with the regulations in light of the rapid advances in design and development of highly integrated and distributed aircraft systems.

The goal is to develop recommendations and assurance criteria and verification methodologies that assist in the certification and assurance of new technologies (e.g. AI/ML implementations), highly integrated, distributed, and complex digital aircraft systems, including systems development processes and architectures, requirements validation and integration; use of COTS devices, new and novel electronic hardware and software implementation techniques, tools, methods, and processes; continued operational safety; and streamlining approaches for safety assurance and aircraft certification.

Requirements:

The FAA would like white papers to address the specific areas listed below; however, submittals are not limited to these requirements. Innovative ideas are welcome and encouraged.

The research should consider aircraft and system safety and assurance issues in the following specific areas or combination of areas, but no be limited to:

• Identify risks, mitigation of the risks and improving confidence in software-based systems by developing a closer relationship between safety and certification along a safety continuum

• Develop concepts to improve lower critically AI/ML models to move them for higher criticality levels and develop approach(es) to scale upwards from low-criticality advisory systems to safety critical systems

• Develop improvements of software safety through the use of architectural means

• Study the AI/ML techniques for anomalies in the models that are not visible during the verification process and understand the risk associated

• Study the impact of using higher computing platforms to train AI/ML models in the certification point-of-view and its impact during real-time operations

• Study the explainability of AI/ML models and develop criteria to adapt these models for different risk scenarios, assurance levels, or safety levels

• Implementation and verification Methodologies for Automation using Artificial

Intelligence and Machine Learning in safety critical airborne systems

• Implementation of run-time assurance and the safety implications

• Pilot studies to evaluate the use of new assurance approaches, e.g., Overarching

Properties (OPs) as Alternative Means of Compliance

• Use of Formal Methods and Assurance Cases, and their use in aircraft certification

• Assurance Challenges with new and novel Avionics Architectures, Tools and

Technologies

For the research areas listed above, the FAA would like to:

• Assess alternative assurance approaches to currently recognized standards and their effectiveness in addressing safe implementation of new technologies such as AI/ML and addressing the safe implementation of autonomy.

• Identify the issues, challenges, and gaps in the current standards/guidance in assuring new complex airborne systems and components

• Develop criteria, mitigation approaches, recommendations, training material, or position papers.

The results of the research will be used by FAA to develop/modify standards, guidance, or training material to support the FAA’s certification workforce.

Period of Performance/Rough Order of Magnitude:

The Period of Performance (PoP)/Rough Order of Magnitude (ROM) will be generally determined based on the projects proposed. However, the tasks lasting for more than 3 years will NOT be considered. Although the FAA encourages separate proposals for each item listed under requirements, proposals combining multiple items will be considered.

Continued efforts at the completion of each milestone or deliverable are at the discretion of the FAA, based on performance and results. These efforts are anticipated to be funded annually, subject to availability of funds. ROM for this research is expected not to exceed $400,000.00 per project, per fiscal year for any awards made under this announcement.

Topic Number: ARSS0002:

Flight Controls and Mechanical Systems

Technical POC: Robert McGuire; Robert.J.McGuire@faa.gov Copy: 9-ACT-AAQ-600-BAA@faa.gov

Background:

The FAA’s Small Airplane Directorate has been working for a number of years to address General Aviation (GA) safety and to create a regulatory environment that uses advances in technology to enhance GA safety. In that time, the certification process study and Part 23 rewrite have indicated a need for the FAA to keep pace with technology and specifically apply it to prevent fatal GA accidents. Using a data driven approach, the FAA, along with the General Aviation Joint Steering Committee (GA-JSC), have identified the top three causes of fatal GA accidents to be: loss of control (LOC), controlled flight into terrain (CFIT), and system or component failure - power plant. Advanced Flight Controls, including augmented flight path control can help address many of these root causes of fatal GA accidents.

Purpose:

The purpose of this Topic is to solicit white papers from the aviation community to develop proposed methods of compliance for certification of advanced flight control systems and address the root causes of fatal GA accidents. The white papers can focus on any one part of these causes, multiple parts of these causes, or all the causes. Offerors are welcome to submit multiple white papers if desired.

The FAA wants to identify barriers to certification and find ways to affordably certify systems and safety enhancements. Results will be used by the FAA and/or industry to capture best design practices, create industry standards, field new designs, and develop methods of compliance for certification of advanced flight control systems. Ultimately, the expected outcome will be a significant reduction of Loss of Control, CFIT, and power plant related GA accidents.

Requirements:

The FAA would like to address the specific areas listed below, however, white papers are not limited to these requirements. Innovative ideas are welcome and encouraged.

• Aviation Safety Research focusing on new and innovative Cockpit Displays, Heads-up Displays, and/or Inceptors for General Aviation, VTOL, VSTOL, or Hybrid aircraft.

• Aviation Safety Research focusing on new and innovative Autopilot technologies, Flight Path Control Systems, Automation, and/or Collision Avoidance Systems for General Aviation, VTOL, VSTOL, or Hybrid aircraft.

• Aviation Safety Research focusing on developing Mission Task Elements, Means of Compliance/Methods of Compliance, or other research to assist in the certification of General Aviation, VTOL, VSTOL, or Hybrid aircraft.

mailto:Robert.J.McGuire@faa.gov

• Aviation Safety Research focusing on how sensors, avionics, processors, actuators, etc.

could be used to enhance GA safety by safely retrofit into existing General Aviation aircraft.

• Aviation Safety Research focusing on automation in the context of safe flight path augmentation, automation for safety risk controls, aiding pilot decision making, reducing pilot workload, performing dynamic consistency checks, and providing run time assurance for complex systems.

• Aviation Safety Research focusing on ways to enhance the safety of commercial Urban Air Mobility.

• Aviation Safety Research focusing on ways to reduce the General Aviation accident rate.

• Aviation Safety Research to address design best-practices, architectures, and methods of compliance to affordably implement basic envelope protection, augmented flight path control systems, and energy management concepts.

• Aviation Safety Research to propose ways to address pilot distraction, confusion or pilot errors that have resulted in GA accidents and incidents.

• Aviation Safety Research to propose design best-practices, architectures, and methods of compliance to certify “refuse to crash” hazard avoidance systems. These systems have awareness of threats such as terrain, obstacles, weather, and other aircraft.

The Period of Performance (PoP)/Rough Order of Magnitude (ROM) will be generally determined based on the projects proposed. However, tasks lasting for more than 3 years will NOT be considered.

Continued efforts at the completion of each milestone or deliverable are at the discretion of the FAA, based on performance and results. These efforts are anticipated to be funded annually, subject to availability of funds. There are currently no set parameters for the ROM.

Topic Number: ARSS0003:

Integrated Flight and Propulsion Control for Rotorcraft

Technical POC: Dan Dellmyer; Dan.Dellmyer@faa.gov Alternate POC: Traci Stadtmueller; Traci.Stadtmueller@faa.gov

New and novel ways of integrating propulsion and flight controls to simultaneously produce lift, thrust and control of vertical landing aircraft are being introduced. Some of the existing system requirements, airworthiness standards and associated means of compliance are not applicable, need modification or need to be drafted. Flight characteristics and thrust/control coupling of multiple propulsion and control effector vehicles (multi-rotor copters of 3 or more blades) need to be understood.

Purpose:

This Topic is part of a proactive effort by the FAA to engage with industry and collaborate on emerging technologies. Furthermore, the FAA wants to identify barriers to certification and find ways to affordably certify systems and safety enhancements on powered-lift and distributed lift rotorcraft.

The purpose of this Topic is to solicit white papers from the rotorcraft and non-rotorcraft community that offer potential solutions for multi-rotor powered-lift and rotorcraft/vehicles that will provide needed data/information to help the FAA develop guidance and airworthiness criteria and means of compliance for this type of vehicle.

Requirements:

The FAA would like white papers to address one or more of the specific areas listed below, however, proposals are not limited to these requirements. Innovative ideas are welcome and encouraged.

• Stability: Height-speed envelope, main rotor speed and pitch limits, general flight characteristics.

• Control bandwidth requirements and external disturbance rejection capability and evaluation.

• Performance: General, landing, autorotation (emergency landing), controllability and maneuverability.

mailto:Dan.Dellmyer@faa.gov mailto:Traci.Stadtmueller@faa.gov

• Failure modes and acceptable system degradation capabilities.

• System Integration/Flight Management: eVTOL simulation or actual test demonstration to cover takeoff, en route, and landing phase for normal and emergency procedures.

• Since certifying Emergency Auto-Land, the FAA has been looking at a new paradigm in automation integration. In some cases now, the automation is there to back up the pilot (correcting for pilot incapacitation or pilot errors) instead of the pilot stepping in when the automation fails. What types of training and aircraft certification standards should apply in this new paradigm? With new and novel automation integration (especially with fly-by-wire eVTOL aircraft and integrated envelope protections) how do the assumptions of pilot interaction with the aircraft and system change? How do these assumptions change the way aircraft are certified and the way airmen are trained and tested?

Submitted white papers should focus on solutions to one or more of the above challenges. The goal of this program is to have a system that can demonstrate a multi-rotor or powered-lift vehicle that will be tested to provide/generate data in one of the areas listed above. (Simulation and/or computer models or actual vehicle testing).

Period of Performance/Rough Order of Magnitude: The Period of Performance (PoP)/Rough Order of Magnitude (ROM) will be generally determined based on the projects proposed.

However, tasks lasting for more than 3 years will NOT be considered. There are currently no set parameters for the ROM.

Topic Number: ARSS0004:

Helicopter Fuel System Drop Test

Technical POC: Dan Dellmyer; Dan.Dellmyer@faa.gov Alternate POC: Traci Stadtmueller; Traci.Stadtmueller@faa.gov

When applicants seek certification of a rotorcraft, they must show that the fuel system is crash resistant per §27/29.952. This rule requires demonstrating that the fuel tank system will not leak after impacting a non-deformable surface when dropped from a height of 50 feet. The tank must be filled to 80% of its normal, full capacity with water, and the tank must be enclosed in a surrounding structure representative of the installation unless it can be established that the surrounding structure is not likely to contribute to rupture of the tank. However, there are currently no standardized methods to evaluate the surrounding structure of the fuel system for the drop test. Additionally, there are concerns that the use of wood in the test article platform may affect the requirement for the test article to impact a non-deformable surface.

Purpose:

The purpose of this Topic is to solicit white papers from the rotorcraft community that determine the relevance and effects of dropping the test article with and without surrounding structure, and standardize the use of different platform materials used in helicopter fuel cell drop tests as prescribed in Fuel Cell Crash Resistance §27/29.952. The goal is standardization of the certification process when applicants are seeking approval of a crash resistant fuel system.

This research will determine the significance of drop-testing with or without surrounding structure, and whether the use of certain platform materials violate the non-deformable impact surface requirement. The findings in this research will help ensure that post-crash fires will be significantly reduced in the models that comply with the rule through standardized testing methods.

Requirements:

The FAA would like white papers to address the specific areas listed below:

• Review existing approved fuel system designs to determine what platform materials and surrounding structures applicants have used during certification. Review existing helicopters with crash resistant fuels systems, to determine the effectiveness of these systems.

• Perform instrumented helicopter fuel system drop tests on representative articles with and without surrounding structure and with and without deformable platforms. The test articles should include internal components typical of fuel system installations (fuel gauging probes, fuel pumps, etc.) Perform instrumented helicopter fuel system drop tests with different platform materials, to investigate the effect of deformable materials between the test article and the impact surface. Quantitatively evaluate the results.

mailto:Dan.Dellmyer@faa.gov mailto:Traci.Stadtmueller@faa.gov

• Correlate drop test results with previous applicant data.

• Compare the loads and fuel tank damage from all articles, with and without surrounding structure and the various drop test platform configurations, to determine if there are any configurations that reduce the loads or damage that the fuel tank should have experienced.

The goal of this Topic is to support guidance material for applicants to better understand how to develop and perform a fuel tank drop test.

Period of Performance/Rough Order of Magnitude: The Period of Performance (PoP)/Rough Order of Magnitude (ROM) will be generally determined based on the projects proposed.

However, tasks lasting for more than 2 years will NOT be considered. There are currently no set parameters for the ROM.

Topic Number: ARSS0005:

Technology Exploration Study for Context-Aware Behavioral Artificial Intelligence (CAB

AI)

Technical POC: John Peace; John.Peace@faa.gov Copy: 9-ACT-AAQ-600-BAA@faa.gov

Background:

Context-aware behavioral Artificial Intelligence (CAB-AI) is an emerging area of research within the Artificial Intelligence and Machine Learning (AI/ML) domain that aims to improve existing AI/ML models through the injection of context into the design, training, and testing of those models. Current AI/ML models (particularly deep learning models) require large data sets to infer latent features that define trends in the data, but they often fall short in terms of overfitting to the specific data they are trained upon and fail to capture all inputs that a human would process in order to make decisions. Through the application of CAB-AI, additional data sources outside of the primary training dataset can be utilized to enhance the classification capabilities of these ML models. Knowledge from subject matter experts of the dataset and domain under evaluation can be injected into these ML models in various ways to provide context to the data. By providing this context, CAB-AI can allow for greater accuracy in modelling real-world environments and more explainable results for the human end-user.

Furthermore, the broad aviation cybersecurity domain contains both an abundance of data and human-motivated attacker/defender actions which provide a solid foundation for application of CAB-AI. For example, knowledge from human analysts on network-layout, patching procedures, critical network assets and levels of defensive measures could enhance the efficacy of anomaly detection systems deployed on networks by providing the ML model insight into the structure and operation of their organization. Additionally, data fusion techniques could be utilized with operational data to provide enhanced context of the patterns within the network data set since they are often intimately related with different representations of events.

Purpose:

The purpose of this BAA research topic is to support ongoing FAA research in the area of Cybersecurity Data Science (CSDS) with emphasis on AI/ML. The FAA is researching the potential benefits from the application of CSDS with AI/ML to specific elements of the aviation ecosystem, namely airlines, airports and aircraft (integrators and avionics manufacturers).

Specifically excluded from this research is application to the FAA Air Traffic Control (ATC) infrastructure and services. This topic seeks a study to explore and describe current general industry, academic and Government CAB AI techniques (including algorithms and processes).

Researchers also will conduct analysis and recommend which of these techniques are most relevant and applicable to the noted elements of the aviation ecosystem. Rationale supporting potential application of specific general CAB AI techniques to the aviation ecosystem will be provided.

mailto:John.Peace@faa.gov

Requirements:

The FAA seeks White Papers to address the specific areas listed below; however, submittals are not limited to these requirements.

• Provide a detailed list of existing and anticipated CAB-AI techniques (including algorithms and processes) within the AI community, supported with associated descriptions and source references.

• Analyze and recommend which of the identified techniques are most relevant and applicable to the noted elements of the aviation ecosystem, with supporting rationale.

The PoP is anticipated to be 8 months. The ROM for this research is expected to be no more than $125,000.00.

Topic Number: ARSS0006:

Aviation Data Strategy Exploration & Development

Technical POC: John Peace; John.Peace@faa.gov Copy: 9-ACT-AAQ-600-BAA@faa.gov

Background:

The "Aviation Ecosystem" contains six "As" as described in the National Strategy for Aviation Safety (NSAS) of 2018. Of those six, the FAA Cybersecurity Data Science (CSDS) research program is focused on three elements: Airlines, Airports and Aircraft (integrators and avionics manufacturers). These elements are further refined by the FAA's CSDS Aviation Architecture Framework (AAF) into six functional aviation domains: Aircraft OEMs (and supply chains);

Aircraft/Airline Operators; Maintenance, Repair and Overhaul (MRO) Providers;

Data/Communication Providers; Airspace Management; and Airport Operators. Domain stakeholders are defined in DO-391, Aeronautical Information System Security Framework Guidance, published by RTCA in Dec 2021. To provide additional research context, a draft of the current (evolving) AAF will be made available, upon request via email to 9-ACT-AAQ-600- BAA@faa.gov. Section 2.4 of the AAF discusses concepts associated with data relevancy, data lifecycles and data spheres.

These domains within the aviation ecosystem rely upon operation and information technologies (OT & IT), including their systems, network architectures and the large quantity of valuable data that they process for aviation business purposes. By exploring individual stakeholder Use Cases, ongoing FAA collaboration with "3A" industry stakeholders, across five of these six domains (with the exception of Airspace Management), serves to provide a mechanism to unite various independent commercial entities through sharing of data and concepts, as well as to influence emerging cybersecurity standards. This collaboration will better enable industry to leverage lessons learned from this research to strengthen their own proactive and reactive cybersecurity, both individually and collectively, thereby making the broader aviation ecosystem more resilient (available and reliable) and safer for the flying public.

The data used in these aviation domains is large in scale and diverse in format and purpose. To support research and development of CSDS concepts for the aviation domains of concern, it is critical to understand the broad scope of aviation-related data, as well as the underlying architectures that support transmission and use of that data. It is the FAA's long-term research intent to investigate and identify as much of the aviation data as possible and the associated data collection capabilities and "sensors", assess what portion of that data and supporting infrastructure/capability is relevant to CSDS for the aviation ecosystem, and lastly consider alternatives for ecosystem implementation of a CSDS data strategy.

mailto:John.Peace@faa.gov

Purpose:

The purpose of this BAA research topic is to support ongoing FAA research in the area of CSDS with emphasis on AI/ML. The FAA is researching the potential benefits from the application of CSDS with AI/ML to specific elements of the aviation ecosystem, namely airlines, airports and aircraft (integrators and avionics manufacturers). Specifically excluded from this research is application to the FAA Air Traffic Control (ATC) infrastructure and services. This topic addresses the research of identifying the range of aviation data processed in the five domains and the data collection capabilities/sensors employed to collect that data. Understanding the data within different aviation networks will enable and optimize the development of advanced AI/ML algorithms and Security Incident Event Management (SIEM) end applications to improve the human cyber analyst’s abilities to respond and recover from advanced cyber threats through use of numerous diverse data sources.

Requirements:

The FAA seeks White Papers to conduct a study and provide a report that addresses all specific areas listed below; however, submittals are not limited to these requirements.

• Explore each of the domain types identified to identify, categorize and characterize associated aviation data. Characterization includes conveying an understanding of how and why the data fits within the “datasphere” (see AAF), and is used, transmitted, formatted, etc.

• Explore each of the domain types identified to identify, categorize and characterize associated data collection capabilities/sensors. Characterization includes conveying an understanding of how (methods and tools/capabilities) and why the data is collected, used, transmitted, formatted, etc.

• Produce a report that documents the results of the exploration above with enough information to analyze and evaluate which data and sensors are most needed to support application of CSDS with AI/ML to the aviation ecosystem in the five domains.

The anticipated PoP is 6-8 months. ROM for this research is expected not to exceed $400,000.00.

Topic Number: ARSS0007:

Reducing Pilot Error Through Raising Awareness of Cognitive Biases

Technical POCs: Angela Campbell; Angela.Campbell@faa.gov Jeffery Schroeder; Jeffery.Schroeder@faa.gov Copy: 9-ACT-AAQ-600-BAA@faa.gov

Background:

Pilot error remains the leading contributing factor to aviation accidents worldwide. Often, errors arise from typical human failings, such as confirmation bias, attention tunneling, etc. While pilots have varying levels of understanding of these typical human failings, unfortunately the failings still occur operationally, and pilots are often surprised that they succumbed to those failings. This research aims to create a succinct training module to enhance the knowledge, skills, and awareness of the key cognitive biases the most commonly affect commercial transport aviation safety.

Purpose:

The purpose of this BAA research topic is to develop a practical training module that airlines will want to use in order to reduce human errors arising from cognitive biases. The training module will have both an academic and practical component. The academic component needs to provide the necessary knowledge of the relevant biases. This knowledge will be the foundation for crew awareness and the creation of effective prevention strategies to reduce the potentially dangerous consequences of such cognitive biases. The practical component of the training module will reinforce the academics with effective flight simulation scenarios that expose crews to situations that likely induce cognitive biases. In fact, the best scenarios will cause crews to fall for those biases so that the experience helps prevent recurrences. Creating effective training modules, especially those that include high-quality flight simulator scenarios, is time consuming.

Many airlines lack the internal resources to create the academic and practical training for the breadth of safety topics that face commercial aviation, and the purpose of this research is to provide such assistance to airlines on this important topic.

Requirements:

The FAA seeks White Papers to address the specific areas listed below; however, submittals are not limited to these requirements.

• Create a training module containing both academics and specific simulator scenarios where pilots can personally experience cognitive biases. By personally experiencing these biases, the idea is that a pilot will both learn and remember their heuristic nature and effects. Depending on the type of training proposed, Section 508 (Federal Electronic and Information Technology) compliance may apply, as determined by the FAA.

The PoP is anticipated to be 24 months. The ROM for this research is expected to be no more than $450,000.00.

mailto:Angela.Campbell@faa.gov mailto:Jeffery.Schroeder@faa.gov

AVIATION RESEARCH STRUCTURES AND

PROPULSION (ARSP)

Topic Number: ARSP0001: This topic has been deleted.

Topic Number: ARSP0002: This topic has been deleted.

AEROSPACE MEDICAL RESEARCH DIVISION

(AMRD)

Topic Number: AMRD0001: This topic has been deleted.