Digital Twin Simulator of the National Airspace System (NAS)

Aerospace
Digital Twin Simulator of the National Airspace System (NAS) (TOP2-325)
An environment for building and running realistic simulations of current or future airspace operations
Overview
The National Airspace System (NAS) is a challenging system of systems to study and monitor due to the volume of data passing through at any given time, including all information, services, rules, regulations, policies, procedures, personnel, and equipment required to manage flight operations within the United States. Developing and running simulations of the NAS relies on the cumulative experience of engineering teams. Variances in the simulations due to differences in assumptions, software, hardware, and models make results difficult to control and reproduce. New features to be added to the NAS require testing in a time-consuming and iterative process that can delay implementation of new technologies, management protocols, and safety measures. NASA Ames has developed a novel approach for simulating the NAS by using a digital twin simulator. This novel technology can simulate a duplication of the live NAS system, and can test and simulate integration of new elements. The digital twin NAS system can also be used to test high-fidelity models of autonomous systems to validate the operation of such autonomous systems safely interacting with the NAS system.

The Technology
The digital twin NAS simulator provides a complete digital copy of the individual systems that comprise the NAS to allow for the creation of offline simulations to test proposed changes to one or more individual systems based on actual historical data from the NAS or on real-time data from the NAS. The NAS is composed of a collection of systems, including source systems such as weather stations from various locations or airports, which are used by other systems such as individual aircraft flight data and airline operators. Other systems may include management systems such as the FAA, air traffic control centers, and flight traffic monitors. Operational data from each of these systems may be archived by a central information sharing platform such as the System Wide Information Management (SWIM) Program operated by the FAA. The digital twin NAS simulator can access archived SWIM data to create a digital twin NAS system to provide a virtual environment that may operate in real-time alongside the actual NAS, with the digital twin receiving live data updates from the actual NAS. A dedicated application programming interface (API) is used to facilitate communication between various distributed external components and the testbed. The testbed receives NAS data during a test and feeds the data to the simulation manager for use with a digital twin of the NAS system. The result is a virtual environment that is an exact twin of the actual operational system and is able to function identically to the actual NAS system because it is based on and uses the same data archived from the actual NAS system. A primary function of the virtual twin NAS is that it will allow for changes to one or more systems to be simulated against the archived NAS data and subsequently allow for a comparison between the simulated results and the actual results from the operational system. The digital twin simulator may also function in a distributed network environment, allowing for simulations of different elements to run simultaneously, which speeds up and improves the testing and evaluation of proposed changes.
NAS Digital Twin NAS Digital Twin
Benefits
  • Enhances air traffic fuel efficiency, reduces airline costs and lowers greenhouse gas emission
  • Enables seamless communication between distributed external components and the testbed through a dedicated API
  • Offers a live, virtual environment to assess and validate proposed changes, new technologies, and easy integration of new algorithms
  • Easily integrates new elements (e.g., aircraft types, flight routes) for generating common metrics and assessing various scenarios
  • Models autonomous systems in a realistic environment using digital twin, ensuring validation without affecting live operations
  • Accelerates test data generation for a through exploration of costs and benefits of proposed system changes to the NAS
  • Operates in parallel with the live NAS, continuously receiving real-world data to support multiple “what-if” scenarios and enhance decision-making based on potential future events
  • Enables evaluation of proposed flight operation changes with historical data and simulated aircraft, avoiding use of actual aircraft
  • Provides a cloud-based distributed test platform for accessing core functionality and easily swapping test scenarios without affecting the core system

Applications
  • NAS stakeholders - including vehicle manufacturers, decision support tool developers, data providers, surveillance system Original Equipment Manufacturers (OEMs)
  • Aviation industry
  • Major airlines
  • Developers of new types of aircraft
  • Air cargo industry
  • Government agencies
Technology Details

Aerospace
TOP2-325
ARC-18867-1
https://ntrs.nasa.gov/citations/20240009035 https://arc.aiaa.org/doi/abs/10.2514/6.2022-3828 https://arc.aiaa.org/doi/abs/10.2514/6.2024-4011
Similar Results
FACET: Future Air Traffic Management Concepts Evaluation Tool
FACET: Future Air Traffic Management Concepts Evaluation Tool
Actual air traffic data and weather information are utilized to evaluate an aircrafts flight-plan route and predict its trajectories for the climb, cruise, and descent phases. The dynamics for heading (the direction the aircraft nose is pointing) and airspeed are also modeled by the FACET software, while performance parameters, such as climb/descent rates and speeds and cruise speeds, can also be obtained from data tables. The resulting trajectories and traffic flow data are presented in a 3-D graphical user interface. The FACET software is modular and is written in the Java and C programming languages. Notable FACET applications include reroute conformance monitoring algorithms that have been implemented in one of the Federal Aviation Administrations nationally deployed, real-time operational systems.
Mitigating Risk in Commercial Aviation Operations
NASA’s newly developed software leverages flight operations data (e.g., SWIM Terminal Data Distribution System (STDDS) information), and with it, can predict aviation related risks, such as unstable approaches of flights. To do this, the software inputs the complex, multi-source STDDS data, and outputs novel prediction and outcome information. The software converts the relatively inaccessible SWIM data from its native format that is not data science friendly into a format easily readable by most programs. The converted, model friendly data are then input into machine learning algorithms to enable risk prediction capabilities. The backend software sends the machine learning algorithm results to the front end software to display the results in appropriate user interfaces. These user interfaces can be deployed on different platforms including mobile phones and desktop computers and efficiently update models based on changes in the data. To allow for visualization, the software uses a commercially available mapping API. The data are visualized in several different ways, including a heat map layer that shows the risk score, with higher risk in areas of higher flight density, a polyline layer, which shows flight paths, and markers that can indicate a flight’s location in real time, among other things. The related patent is now available to license. Please note that NASA does not manufacturer products itself for commercial sale.
Flying drone
Unmanned Aerial Systems (UAS) Traffic Management
NASA Ames has developed an Autonomous Situational Awareness Platform system for a UAS (ASAP-U), a traffic management system to incorporate Unmanned Aerial Systems (UASs) into the National Airspace System. The Autonomous Situational Awareness Platform (ASAP) is a system that combines existing navigation technology (both aviation and maritime) with new procedures to safely integrate Unmanned Aerial Systems (UASs) with other airspace vehicles. It uses a module called ASAP-U, which includes a transmitter, receivers, and various links to other UAS systems. The module collects global positioning system GPS coordinates and time from a satellite antenna, and this data is fed to the UAS's flight management system for navigation. The ASAP-U module autonomously and continuously sends UAS information via a radio frequency (RF) antenna using Self-Organized Time Division Multiple Access (SOTDMA) to prevent signal overlap. It also receives ASAP data from other aircraft. In case of transmission overload, priority is given to closer aircraft. Additionally, the module can receive weather data, navigational aid data, terrain data, and updates to the UAS flight plan. The collected data is relayed to the flight management system, which includes various databases and a navigation computer to calculate necessary flight plan modifications based on regulations, right-of-way rules, terrain, and geofencing. Conflicts are checked against databases, and if none are found, the flight plan is implemented. If conflicts arise, modifications can be made. The ASAP-U module continuously receives and transmits data, including UAS data and data from other aircraft, to detect conflicts with other aircraft, terrain, weather, and geofencing. Based on this information, the flight management system determines the need for course adjustments and the flight control system executes them for a safe flight route.
Dynamic Weather Routes Tool
Dynamic Weather Routes Tool
Every 12 seconds, the Dynamic Weather Route (DWR) automation system computes and analyzes trajectories for en-route flights. DWR first identifies flights that could save 5 or more flying minutes (wind-corrected) by flying direct to a downstream return fix on their current flight plan. Eligible return fixes are limited so as not to take flights too far off their current route or interfere with arrival routings near the destination airport. Using the direct route as a reference route, DWR inserts up to two auxiliary waypoints as needed to find a minimum-delay reroute that avoids the weather and returns the flight to its planned route at the downstream fix. If a reroute is found that can save 5 minutes or more relative to the current flight plan, the flight is posted to a list displayed to the airline or FAA user. Auxiliary waypoints are defined using fix-radial-distance format, and a snap to nearby named fix option is available for todays voice-based communications. Users may also adjust the alert criteria, nominally set to 5 minutes, based on their workload and desired potential savings for their flights. A graphical user interface enables visualization of proposed routes on a traffic display and modification, if necessary, using point, click, and drag inputs. If needed, users can adjust the reroute parameters including the downstream return fix, any inserted auxiliary waypoints, and the maneuver start point. Reroute metrics, including flying time savings (or delay) relative to the current flight plan, proximity to current and forecast weather, downstream sector congestion, traffic conflicts, and conflicts with special use airspace are all updated dynamically as the user modifies a proposed route.
Tower
Method and System for Air Traffic Rerouting for Air-space Constraint Resolution
National Airspace System (NAS) Constraint Evaluation and Notification Tool (NASCENT) employs a NAS-wide simulation and analysis infrastructure that implements airspace constraint avoidance algorithms for efficient routing. NASCENT uses NASA-developed aircraft performance tables for computing climb, cruise, and descent trajectories. Reference routes are created that save more than a user-specified number (e.g., five) minutes of flying-time savings. The return capture fix for the reference route is the last fix on the current flight plan within a limit region (derived using this patented technology). A Maneuver Start Point is selected to allow time for coordination of the reroute with the Federal Aviation Administration (FAA). These routes are checked against the weather polygons, FAA denoted Special Use Airspaces (e.g., Military Operations Areas) and Temporary Flight Restrictions (TFRs); and additional waypoints are added to avoid these airspace constraints. The wind-corrected flying-time savings are reported for each flight. The polygons are first converted into convex hulls and inflated by a user-specified number of nautical miles (e.g., 20, for weather) to account for the FAA requirements. Lateral and/or vertical advisories are created using a binary tree search along the left-side and right-side, up to the return capture fix, to find a minimum-deviation delay solution. The NASCENT system provides notification for congested sectors along the current flight plan and the proposed avoidance route, along with flights impacted by FAA imposed required Traffic Management Initiatives (TMIs, reroutes, Ground Delay Programs, etc.). The reroutes can be implemented with no changes required to the current FAA operational infrastructure.
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