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At least 1,729 records · Page 96

Open Data Integration (ODIN): A Concurrent, Distributed Message-Based Architecture and Framework for Disaster Response

The Runtime for Airspace Concept Evaluation (RACE) is an open-source software architecture and framework to build configurable, highly concurrent and distributed message-based systems that offer scalable, low-latency performance on commodity hardware. RACE was used in commercial aviation applications to rapidly build systems that span several machines (including synchronized displays), interface existing hardware simulators and other live data feeds, and incorporate sophisticated visualization components such as NASA WorldWind. These RACE applications validated elements of the FAA’s System Wide Information Management (SWIM) Program, handling up to 1000 messages/sec from diverse sources (SFDPS, TFM-DATA, TAIS, ASDE-X, ITWS and local ADS) for 4,500 simultaneous flights tracked in the next-generation air transportation system’s digital backbone. We have since generalized RACE to support Open Data Integration (ODIN) applications outside aviation. Systems built with RACE/ODIN can be deployed in the field, on commodity hardware, and operate with limited or intermittent connectivity to the outside world. Our primary use case is a web-server with local/persistent data storage that runs within and only serves the stakeholder network (e.g. an incident command post). We are tailoring the RACE/ODIN system to support wildland fire management for the upcoming NASA Wildland Fire Safety Demonstration Series. RACE-ODIN is under consideration for application in the Scalable Traffic Management for Emergency Response Operations project, or STEReO, which aims to create a system that can be deployed during emergencies, to coordinate multiple elements of disaster response. Such data sources predominantly come from existing services on the internet (e.g. weather and satellite data, imported from so called "edge servers") but can also include dynamic (real-time) data from computer simulations and within the stakeholder network (such as aircraft and personnel tracking information). We will present the architecture and ODIN system demonstration incorporating local data from instrumented power-line towers, interpolated weather data and geospatial data from space-based platforms.

Guillaume P Brat↗

Control Architecture for a Concept Aircraft with a Series/Parallel Partial Hybrid Powertrain and Distributed Electric Propulsion

Traditional aircraft propulsion control approaches are insufficient for electrified aircraft powertrains due to their increased complexity compared to current systems. New control approaches are required to manage the increased interdependency and complexity of these electrified powertrains. Additionally, electrification enables aircraft to have multiple distributed thrust producing fans that the flight control system can leverage for enhanced maneuverability, further increasing the control complexity. This paper describes the control architecture for a concept vehicle with these characteristics, the SUbsonic Single Aft eNgine (SUSAN) Electrofan. SUSAN is a series/parallel partial hybrid electric single-aisle transport aircraft that leverages its electrified powertrain to provide fuel burn and emissions benefits when compared to the state-of-the-art. Achieving these benefits requires an appropriately designed control architecture that coordinates the various powertrain and flight control subsystems. As such, the SUSAN aircraft is designed with a high level of automation, allowing it to properly manage coupled subsystems and react rapidly to failures and anomalies. This paper presents a summary of the SUSAN powertrain design and discusses several of the novel control approaches used to manage the complex electrified powertrain.

Control↗

C2-Communications Concept Architecture Presentation

Presentation Outline 1. Introduction 2. Document Objectives and Concept development assumptions 3. UAS C2-Communication Operations, Functions and Challenges 4. C2 Link Technologies overview 5. New Function introduction 6. C2-Communications Architecture Concept Description 7. UAS Communications Architecture Subsystems 8. Summary and Questions

Command and Control↗

Trades, Architecture, and Design of the Joint Augmented Reality Visual Informatics System (Joint AR) Product

Future expeditions will enable exploration and study of the planetary surfaces of the Moon and Mars by performing extravehicular activity (EVA) operations. Present-day International Space Station (ISS) EVA operations require an intricate choreography of crew, space suits, tools, systems, and flight teams to plan, train, and execute with limited advanced informatics. In this paper, the Joint Augmented Reality Visual Informatics System (Joint AR) project team at NASA Johnson Space Center (JSC) characterizes the design space for developing a modular augmented reality (AR) device for a spacesuit form factor that can support crew decision-making for EVA. The Joint AR product was defined via trade studies and market analysis of previous EVA display efforts, various AR components such as optics, commercial AR systems, light engines, data interfaces, and graphics engine software. This paper outlines the defining architectural design decisions, including safety criticality considerations, interfaces, and computer architectures. The outcomes of these studies result in a prototype design which is defined here as the Joint AR product. This work aims to enable a community-wide discussion toward realizing necessary suit-compatible AR features and capabilities for future missions.

Paromita Mitra↗

Modeling of Gateway Environmental Control and Life Support Systems as A Means to Investigate the Subsystem and Integrated Architecture Performance

As Human spaceflight evolves and develops, the technology the crew relies on for life support must become more advanced than at any point in NASA’s history. Nowhere is this more apparent than the Gateway, where lessons learned from Mercury to ISS are being applied in the design and production of the life support systems. Some of these technological improvements are proven in flight configuration, or have a heritage of proven flight hardware, but many are of a lower technology readiness level. Due to the unpredictable nature of the metabolic byproducts (CO 2 , H 2 O, and heat), even the proven technologies can fail to meet requirements for crew safety. Detailed modeling of individual components excels in proving component level requirements are met, but fails to verify system or architecture level requirements. This paper expounds upon an effort to take a number of detailed component level models of the Gateway ECLSS and integrate them into a larger architecture model known as the Gateway Integrated ECLSS Model (GIEM). The GIEM is then used to study how the subsystems work synergistically to meet environmental requirements as well as investigate how changes at the component level effect the Gateway stack as a whole.

Modeling↗

Trades, Architecture, and Design of the Joint Augmented Reality Visual Informatics System (Joint AR) Product

Future expeditions will enable exploration and study of the planetary surfaces of the Moon and Mars by performing extravehicular activity (EVA) operations. Present-day International Space Station (ISS) EVA operations require an intricate choreography of crew, space suits, tools, systems, and flight teams to plan, train, and execute with limited advanced informatics. In this paper, the Joint Augmented Reality Visual Informatics System (Joint AR) project team at NASA Johnson Space Center (JSC) characterizes the design space for developing a modular augmented reality (AR) device for a spacesuit form factor that can support crew decision-making for EVA. The Joint AR product was defined via trade studies and market analysis of previous EVA display efforts, various AR components such as optics, commercial AR systems, light engines, data interfaces, and graphics engine software. This paper outlines the defining architectural design decisions, including safety criticality considerations, interfaces, and computer architectures. The outcomes of these studies result in a prototype design which is defined here as the Joint AR product. This work aims to enable a community-wide discussion toward realizing necessary suit-compatible AR features and capabilities for future missions.

Paromita Mitra↗

1D-Convolutional Neural Network Architecture for Generalized Time-series Segmentation

Time segmentation of experimental data is a common and often difficult task. Consequently, it is of interest to automate this type of segmentation to reduce manual inputs, which are labor intensive and less consistent. However, simple thresholding algorithms are often insufficiently robust due either to noise or inconsistent data. This paper proposes a simple 1D convolutional neural net (CNN) architecture as a generalized solution for typical time segmentation tasks. The layer architecture, training methods, and methods for simple customization will be described as well as the results of application to three separate data streams: facility condition segmentation, video highlight segmentation, and calorimeter time-series segmentation. In all three test cases the 1D-CNN performs better than tailored integral/derivative/thresholding algorithms across a range of signal-to-noise levels.

CNN↗

Crew Health and Performance Integrated Data Architecture Project Updates

Future Human Exploration missions will face new constraints as crews move further from terrestrial communication, resupply, and the real-time support enjoyed by Low Earth Orbit missions today. Exploration crews will need to be more self-reliant and able to respond to emergencies without immediate support from ground-based personnel. A new generation of technologies, employing advanced analytical and predictive modeling techniques, is needed to assist the crew’s work, help maintain their health, and inform the decisions they make on these future Exploration missions. The Crew Health and Performance Integrated Data Architecture (CHP-IDA) project is laying a foundation for these future technologies by integrating sources of data generated by and around the crew and then providing them though common data models and Application Programming Interfaces to external systems. The combined data model makes comprehensive Crew Health and Performance data accessible and more meaningful to the decision-making process. This presentation will describe the currently ongoing effort to develop and evaluate a path-to-flight concept of the CHP-IDA software, current integrations, updates to the architecture, and examples of exploration scenarios in which CHP-IDA would be used.

B Schmitt↗

1D-Convolutional Neural Network Architecture for Generalized Time-series Segmentation

Time segmentation of experimental data is a common and often difficult task. Consequently, it is of interest to automate this type of segmentation to reduce manual inputs, which are labor intensive and less consistent. However, simple thresholding algorithms are often insufficiently robust due either to noise or inconsistent data. This paper proposes a simple 1D convolutional neural net (CNN) architecture as a generalized solution for typical time segmentation tasks. The layer architecture, training methods, and methods for simple customization will be described as well as the results of application to three separate data streams: facility condition segmentation, video highlight segmentation, and calorimeter time-series segmentation. In all three test cases the 1D-CNN performs better than tailored integral/derivative/thresholding algorithms across a range of signal-to-noise levels.

CNN↗

SUbsonic Single Aft eNgine (SUSAN) Power/Propulsion System Control Architecture Updates

The development of hybrid-electric propulsion technology for commercial transport aircraft presents opportunities for new designs that can reduce fuel consumption and greenhouse gas emissions and improve safety and reliability compared to modern aircraft. The SUbsonic Single Aft eNgine (SUSAN) Electrofan is a conceptual design for a transport aircraft with a series/parallel partial hybrid-electric propulsion system being developed by NASA as a reference design for a regional transport aircraft with a high degree of electrification. The SUSAN concept incorporates multiple tightly coupled power, propulsion, and flight control systems that introduce new challenges to the control design process, requiring a hierarchical and more coordinated control approach. This report summarizes updates to the SUSAN power/propulsion system (PPS) model and control architecture made in preparation for planned flight simulator and hardware-in-the-loop testing at the NASA Glenn Research Center. These updates include a new electrical power system model developed using the NASA-developed Electrical Modeling and Thermal Analysis Toolbox (EMTAT) and a new PPS control architecture that improves the operational flexibility and responsiveness of the propulsion system. The performance of the updated controller is demonstrated and discussed.

SUSAN↗

Mission and Vehicle-Level Updates for the Parallel Electric-Gas Architecture with Synergistic Utilization Scheme (PEGASUS) Concept Aircraft

NASA created the PEGASUS concept with the goal of lowering mission energy (a surrogate for operating cost) compared to other regional aircraft by leveraging electrified aircraft propulsion (EAP). Since its inception, researchers have explored multiple facets of PEGASUS in varying fidelity but have not completed a rigorous, integrated design. The goal of this memorandum is to provide an updated design using recent studies and improved methods. This memorandum explores the initial vehicle concept and concept of operations, while considering ways to improve both the mission concept of operations and the integrated vehicle-level performance. Additionally, the design and analysis methodologies for EAP-enabled aircraft concepts are improved in several areas. This research incorporates new propulsion-airframe integration and wing weight surrogates to model the impacts of wingtip propulsors on the configuration. Detailed weight and balance calculations enable calculating dynamic stability and flight qualities within the conceptual design environment. Ultimately, the vehicle is optimized to reduce "well-to-wake" equivalent CO2, CO2e, rather than minimizing either fuel (or total energy) consumption or maximum takeoff weight. Using fuel/energy or takeoff weight leads to conflicting optima for hybrid-electric aircraft. Two aircraft are developed to provide points of comparison for PEGASUS: an advanced conventional turboprop vehicle and a hybrid-electric variant. The results show that the PEGASUS concept can reduce CO2e relative to the advanced turboprop or a hybrid-electric propulsion architecture, albeit with an increase in maximum takeoff weight. PEGASUS's maximum takeoff weight is 55% heavier than the advanced conventional turboprop but releases 18% less CO2e for a 400 nmi mission. Over the same mission, PEGASUS's maximum takeoff weight is 47% heavier than the comparator hybrid-electric vehicle but releases 12% less CO2e. This study shows that the PEGASUS configuration reduces CO2e through its use of wingtip propulsors and that its benefit is not solely a result of switching to a hybrid-electric propulsion architecture. PEGASUS achieves this reduction in CO2e while maintaining satisfactory Level 1 or 2 flight qualities for all of its longitudinal- and lateral-directional modes.

Hybrid-electric↗

System Engineering & Integration (SE&I) In-Situ Resource Utilization (ISRU) Modeling and Analysis (SIMA) Tool for Subsystem Integration into Full-Scale Architectures

In situ resource utilization (ISRU) is the practice of producing mission consumables from local lunar/planetary resources, thereby minimizing system launch mass requirements, mainly through the production of propellant fuel components and life support resources. Modeling full ISRU technology architectures significantly impacts the design and optimization of individual unit processes and facilitates their introduction into service with the Science Technology Mission Directorate (STMD) logistical planning and operation space. The Mission Analysis and Integration Tool (MAIT) is a modeling framework that connects individual ISRU subsystem models for the purposes of technology down select, scaling & optimization, and end-to-end process planning. The development project team seeks to address specific STMD capability gaps by simulating ISRU systems in MAIT. The goal is to produce system architectures for the Moon and Mars that are linked to Key Performance Parameters (KPP) and environmental requirements. To that end, the framework is adaptive, flexible, and suitable for collaboration among government, private sector, and international entities. Our approach currently provides conventional outputs, such as mass, power, and volume, to analyze whole system trade spaces. However, the framework was designed to validate current breadboard subsystems, simulate future process design capacity, and allow flexibility to any external developer-driven subsystem model that is in a state of evolution.

SE&I↗

An Integrated Architecture Study for Autonomous Lunar Construction

Lunar construction is an expanding field within NASA’s Moon to Mars objectives that presents many challenges and requires innovative and reliable forms of autonomous operations on the surface of the Moon to further the technologies needed for human space exploration. Marshal Space Flight Center’s (MSFC) Advanced Concepts Office (ACO) addressed Lunar Infrastructure Objective LI-4 l by developing a Pre-Phase A, integrated architecture to inform a demonstration for lunar construction operations. The ACO study traded three architectures that would survey and prepare a construction area to build a landing pad out of lunar regolith using MMPACT (Moon-to-Mars Planetary Autonomous Construction Technology) platforms, rovers, and navigation outposts. The main trades examined navigation for the system/architecture, options for rover navigation, battery vs continuous tether power for the MMPACT robotic arm, and assigning site prep functionality to the rovers vs the platforms. Results of the study determined that the best options for the scenario provided would be local navigation (more accurate and continuous), a combination of Light Detection and Ranging (LiDAR) for initial site mapping with subsequent Smart Video Guidance Sensors (SVGS) to save power for construction, and using tethered power to decrease mission duration. The team also concluded that assigning site prep functionality to either the rovers or the platforms has benefits and challenges; future studies could explore having that functionality on both the rovers and platforms. Lastly, the team provided a Concept of Operations (ConOps) timeline that can be used in real-time ground demonstrations to explore the mission timeline, construction processes, autonomous operations, and communication systems that can be tested using MSFC’s lunar regolith field and Lunar Utilization Control Area (LUCA).

Sarah Triana↗

Crew Health and Performance Integrated Data Architecture (CHP-IDA) TechPort May 2024

Future exploration missions to Mars will have increased need for crew autonomy. Crew Health & Performance (CHP) related data on the ISS is currently, manually downlinked and in disparate locations, which limits crew autonomy for future missions. The CHP-IDA project is developing a backend data system platform that grants the ability to seamlessly collect, store, process, and display CHP-related data for exploration missions. This platform allows for integration of data and advanced analytics that offer crew and ground teams better insight into the crew’s health and performance. It also enables applications that can improve the crew’s ability to provide more autonomous medical care during exploration missions. Data will be collected automatically to reduce crew and ground team time and effort and will synchronize across all in-mission vehicles, habitats, and ground as communication delay permits. The Human Research Program’s (HRP) Medical Data Architecture (MDA) project focused on this backend data architecture but for medical data only. The CHP-IDA project, a joint effort between HRP’s Exploration Medical Capability (ExMC) element and the Exploration Medical Integrated Product Team (XMIPT), expands this capability to all relevant CHP-related data. The additional inputs from nutrition, environment, exercise, radiation, and any other relevant sources will give more insight into crew’s health and performance. Currently, the Human Systems Engineering and Integration Division at Johnson Space Center (JSC) is designing the system. The team completed a system requirements review (SRR) in FY22 and now the focus is on core software development, testbed buildup, and use case scenario demonstration. An end-to-end demonstration with multiple data sources across CHP domains is schedule for the end of FY24 where all three focus areas will be displayed. Following this ground demo, the software will be completed, tested, and validated for flight.

Courtney M Schkurko↗

Overview of NASA's Ocean Color Instrument Solar Calibration Architecture, Pre-Launch Tests and Preliminary On-Orbit Results

Launched in February 2024, the PACE mission represents NASA’s next investment in ocean biology, clouds, and aerosol data records. A key feature of PACE is the inclusion of an advanced satellite radiometer known as the Ocean Color Instrument (OCI), a global mapping radiometer that combines multispectral and hyperspectral remote sensing. Like its predecessors, OCI will provide two day global coverage of TOA radiances. Unlike its predecessors, OCI will cover a spectral range from 340nm to 2260nm. Below 900nm, OCI will include two spectrometers that continuously span the ultraviolet to 600nm and 600nm to near-infrared spectral regions to provide hyperspectral radiances sampled every 2.5 nm, with a bandwidth of 5 nm for each channel. Wavelengths above 900nm are measured in seven discrete multispectral bands of varying bandwidths, six of which are at similar wavelengths to those on heritage missions to support both atmospheric and ocean color applications. Nominal spatial resolution is similar to the SeaWiFS instrument with 1050 m at nadir. As for SeaWiFS, the pixel size increases due to a ~20 degree tilt and as a function of scan angle. Variations in the radiometric sensitivity of each OCI channel over time will be monitored by solar diffuser measurements for short term instrument gain adjustments and independent lunar measurements for trend adjustments of long time periods, similar to the approach employed for the VIIRS instrument [4]. The OCI flight-unit was built at NASA’s Goddard Space Flight Center. At the time of this writing, OCI has completed on-orbit commissioning activities and normal science operations have begun. A key aspect of the OCI architecture is the capability to trend absolute and relative calibration changes over the course of mission life with solar calibration. Every 24 hours, the PACE spacecraft performs an inertial hold as the ground track nears the North Pole which orients a Quasi-Volume Diffuser (QVD) mounted on OCI towards the sun. By knowing the irradiance of the sun and the reflectivity of the target, the absolute radiance at the input to the OCI aperture can be computed as OCI scans the target. The allowable absolute uncertainty budget for each solar calibration measurement is 1.6% 1-sigma below 900nm at beginning of life (BOL) and the allowable relative uncertainty budget is ~0.26% 1-sigma. The Solar Calibration Assembly (SCA) consists of three targets selectable via a single mechanism which also opens a door. The targets consist of a Daily Bright Target (DBT), Monthly Bright Target (MBT), and Daily Dim Target (DDT). The bright targets are quartz QVDs with the monthly target being used to track the degradation of the daily target. The dim target is used to track CCD linearity using Progressive Time-Delay Integration (PTDI). A composite baffle is attached to the SCA housing aperture to block Earth shine and stray light from the spacecraft. The SCA assembly is mounted to a view port ~90° from OCI nadir. This paper provides an overview of driving solar calibration requirements, error-budgets and early trade studies which drove the solar calibration assembly (SCA) architecture and on-orbit maneuver. Measurements of the diffuser Bidirectional Reflectance Distribution Function (BRDF) at TNO, Netherlands and GSFC are briefly described. Optical modelling and test results at the sub-system and instrument level are included. Finally, preliminary measurements on-orbit are compared to pre-launch predictions.

Joseph J Knuble↗

Overview of NASA's Ocean Color Instrument Solar Calibration Architecture, Pre-Launch Tests and Preliminary On-Orbit Results

Launched in February 2024, the PACE mission represents NASA’s next investment in ocean biology, clouds, and aerosol data records. A key feature of PACE is the inclusion of an advanced satellite radiometer known as the Ocean Color Instrument (OCI), a global mapping radiometer that combines multispectral and hyperspectral remote sensing. Like its predecessors, OCI will provide two day global coverage of TOA radiances. Unlike its predecessors, OCI will cover a spectral range from 340nm to 2260nm. Below 900nm, OCI will include two spectrometers that continuously span the ultraviolet to 600nm and 600nm to near-infrared spectral regions to provide hyperspectral radiances sampled every 2.5 nm, with a bandwidth of 5 nm for each channel. Wavelengths above 900nm are measured in seven discrete multispectral bands of varying bandwidths, six of which are at similar wavelengths to those on heritage missions to support both atmospheric and ocean color applications. Nominal spatial resolution is similar to the SeaWiFS instrument with 1050 m at nadir. As for SeaWiFS, the pixel size increases due to a ~20 degree tilt and as a function of scan angle. Variations in the radiometric sensitivity of each OCI channel over time will be monitored by solar diffuser measurements for short term instrument gain adjustments and independent lunar measurements for trend adjustments of long time periods, similar to the approach employed for the VIIRS instrument [4]. The OCI flight-unit was built at NASA’s Goddard Space Flight Center. At the time of this writing, OCI has completed on-orbit commissioning activities and normal science operations have begun. A key aspect of the OCI architecture is the capability to trend absolute and relative calibration changes over the course of mission life with solar calibration. Every 24 hours, the PACE spacecraft performs an inertial hold as the ground track nears the North Pole which orients a Quasi-Volume Diffuser (QVD) mounted on OCI towards the sun. By knowing the irradiance of the sun and the reflectivity of the target, the absolute radiance at the input to the OCI aperture can be computed as OCI scans the target. The allowable absolute uncertainty budget for each solar calibration measurement is 1.6% 1-sigma below 900nm at beginning of life (BOL) and the allowable relative uncertainty budget is ~0.26% 1-sigma. The Solar Calibration Assembly (SCA) consists of three targets selectable via a single mechanism which also opens a door. The targets consist of a Daily Bright Target (DBT), Monthly Bright Target (MBT), and Daily Dim Target (DDT). The bright targets are quartz QVDs with the monthly target being used to track the degradation of the daily target. The dim target is used to track CCD linearity using Progressive Time-Delay Integration (PTDI). A composite baffle is attached to the SCA housing aperture to block Earth shine and stray light from the spacecraft. The SCA assembly is mounted to a view port ~90° from OCI nadir. This paper provides an overview of driving solar calibration requirements, error-budgets and early trade studies which drove the solar calibration assembly (SCA) architecture and on-orbit maneuver. Measurements of the diffuser Bidirectional Reflectance Distribution Function (BRDF) at TNO, Netherlands and GSFC are briefly described. Optical modelling and test results at the sub-system and instrument level are included. Finally, preliminary measurements on-orbit are compared to pre-launch predictions.

ocean color↗

Developing a Cybersecurity Architecture for Extensible Traffic Management (xTM)

This paper explores the development of a cybersecurity architecture tailored for Extensible Traffic Management (xTM) to address emerging challenges in managing diverse aerial vehicles within the National Airspace System (NAS). Driven by technological advances and the rise of uncrewed aerial systems (UAS), urban air mobility (UAM), and high-altitude traffic (ETM), the NAS is undergoing a paradigm shift. Traditional air traffic management, reliant on traditional Federal Aviation Administration (FAA) control, will give way to decentralized coordination among autonomous and semi-autonomous systems. The proposed xTM Security Architecture, designed as a high-level framework, focuses on ensuring the confidentiality, integrity, and availability of data and operations in this evolving ecosystem. Utilizing threat modeling, the research identifies potential risks across key flight phases, operations and use cases to offer security control recommendations. Key objectives include analyzing interactions between novel airspace entrants and existing NAS traffic, cataloging vulnerabilities, and developing mitigative strategies to ensure safety, operational stability, and secure data exchanges. This research lays the groundwork for regulatory and industry adaptation, providing critical insights into managing cybersecurity risks in this complex, multi-domain environment.

UAM↗

Architecture of High-Altitude Operations (HAO) Discovery and Synchronization Service (DSS)

The aviation industry is evolving at an unprecedented pace, necessitating the development of efficient, secure, and interoperable systems to manage increasingly complex air traffic. Moreover, the demand for High-Altitude Operations (HAO) is increasing. Furthermore, air traffic control services are limited in HAO environments. HAO industry participants will need airspace access and flexibility to perform their missions in this airspace that provides provisions for scalability. The Discovery and Synchronization Service (DSS) will be a cornerstone of the HAO ecosystem, enabling the effective sharing of critical airspace data, including operational intent, aircraft trajectories, and airspace usage among various stakeholders and operators. The DSS architecture addresses these challenges with a distributed, decentralized, and interoperable system that facilitates seamless integration across diverse airspaces. It prioritizes secure data exchange while safeguarding data ownership. This white paper presents the vision, architecture, and benefits of the DSS for HAO, underscoring its potential to streamline operations, reduce redundancies, and establish a foundation for safe and efficient airspace management.

HAO↗