The United States Air Force (USAF) dictates policy for foam fire suppression systems in their hangars. In November 2021, the USAF issued a Sundown Policy for Foam Fire Suppression Systems. The National Fire Protection Association’s Standard on Aircraft Hangars, NFPA 409 serves a similar function. This article uses a real-world installation and analysis of the hangar fire protection scheme stipulated in the USAF Sundown Policy as compared to an installation in compliance with NFPA 409. Applying the Poisson process for a zero-inflated probability distribution, the data referenced for the event tree were evaluated and thereafter validated. The analysis shows that the installation of hangar fire protection stipulated in the USAF Sundown Policy achieves a better performance for the fire protection system than an installation in compliance with NFPA 409, insofar as the risk analysis is concerned. Second, the installation of a fire protection system that complies with the requirements of NFPA 409 fails to achieve the basic probabilistic performance promulgated by the International Code Council’s Performance Code (ICCPC). The validation also demonstrated that the scenario involving the accidental discharge of fire foam was significantly more likely to occur compared to that involving only fire occurrences.

In this article, an Advanced Air Mobility (AAM) platform focused on search and rescue applications is discussed and analyzed from a systems thinking perspective. By applying two systems thinking tools, namely Mind Map and TRIZ, the strong interactions within the constituent parts that make up the system’s whole are examined with the aim of providing a comprehensive roadmap for a proposed Advanced Air Mobility Post-Disaster Response (AAMPDR) system. Furthermore, two problems are discussed to demonstrate the application of the TRIZ technique. The first is in regards to a clause in the AGL rule that could present operational risks to the AAM’s airframe, while the second relates to a potential conflict ensuing from the advent of the 5G C-band and its effect on the AAM altimetry. The resulting solutions to resolve these conflicts using this same technique are also discussed, firstly by taking into account the mean sea/water level as a reference for vertical height within the provisions of the Federal Aviation Regulation requirements, and secondly by applying segmentation of the mission profile as well as a multi-stage frequency designation for each segment depending on a threshold vertical distance. Finally, this study demonstrated that Mind Map and TRIZ can be effective techniques in the early stages of conceptual model development for an AAM system applied to post–disaster response. Furthermore, that the contradictions tool of TRIZ can also be utilized in resolving those potential conflicts identified in relation to the system of interest. To this end, this paper proposes the amendment of the current Part 107 rule to include the term Above Mean Sea (or Water) Level (AMS/WL), a critical yet missing piece of the system requirements that engineers should take into account in future AAM system designs.

Here, the interactions between Urban Air Mobility (UAM) and general aviation (GA) as a socio-technical system (STS) are studied. Their characteristics are also outlined as they relate to the complexity usually associated with such kinds of systems, the aviation industry being an enterprise where both are described as subsets. Using agent-based modeling (ABM), the conceptualization of the socio-technical system (STS) model and its incorporation into the development of a NetLogo program are succinctly presented. Key elements within this complex framework were captured using high-level abstraction, including interfaces such as the physical infrastructure consisting of the airport, airspace (or highway), waypoints, runways, and so on; the social components, one of which was represented by the volume of passenger traffic to and from the airport which was further abstracted in terms of the number of outbound and inbound flights; and the electronic/digital components including surface radar as well as calls by air traffic controllers to the pilot which were also abstracted as separate-aircraft and dynamic-separate-aircraft procedures in the NetLogo code developed for the agent-based model (ABM). The results, discussion and conclusion are presented. Finally, after conducting a number of simulations with the developed NetLogo model by varying the number of airplanes and UAMs for each iteration, the setup with four airplanes and two UAMs resulting in 54 and 27 check-ins/outs over a duration of 291 ticks offered the best configuration with the least likelihood of mid-air collision occurring.

Use of measures of effectiveness (MOE) analysis in exploring candidate systems or alternatives has been the subject of much debate in the systems engineering discipline, as some authors have noted. In this work, methods for MOE analysis are revisited as they pertain to an advanced air mobility platform, first by using the traditional approach, which involves the application of the Pugh matrix, and second by proposing an approach that involves a combination of two (2) methods, namely the Monte Carlo method (MCM) and the analytical hierarchy process (AHP), in order to evaluate and rank the preferred alternative from a selection of candidate systems. The latter method is termed the Monte Carlo–analytical hierarchical hybrid process (MC–AHHP). The results obtained from the application of both approaches demonstrate that the MC–AHHP is a less subjective, more objective, data-driven, and quantitative measure for MOE analysis compared to the erstwhile Pugh matrix method. While the Pugh matrix ranked the SAR AAM as first overall among seven (7) alternatives, the MC–AHHP ranked the same second among three (3) alternatives. The subsequent verification and validation process showed that the MC–AHHP approach resulted in a degree of consistency value of $0.083$, where $CI/RI<0.10$ represents an acceptable level of consistency. Thus, the MC–AHHP approach is recommended as a viable decision-making tool for adoption by systems engineering practitioners.