Small Business Innovation Research/Small Business Tech Transfer
Self-Aware Aerospace Vehicle Contingency Management
Project Description
Aurora Flight Sciences, with Agent Oriented Software, proposes to develop a contingency management system that dynamically performs decision-making based on both sensed and predictive information to carry out adaptive missions and maintenance. This system will mirror the human nervous system, having sensing capabilities distributed throughout systems and subsystems measuring characteristics that predict the conditional response of the aerospace vehicle. The vehicle 'nervous system' of embedded distributed sensors and reasoning agents will generate real-time information on vehicle condition. Like a nervous system, each subsystem will communicate with a higher-level system-reasoning agent. The central reasoning agent will manage mission control systems to perform adaptive maneuvers informed by this network of sensors. This program will concentrate on the composite airframe structure as the system of interest and will encompass the following areas: 1. Assignment of airframe capability figures to maneuvering limits (i.e. various maneuvers that load the airframe, coupled with the capability of the airframe to take that loading). 2. Analysis of available inputs including the environment (temperature, altitude, humidity), the structural state (damage type, size and location), and the loading (inertia, pressure profiles). 3. Creation of an algorithm to determine the capability of the airframe, and potentially return the viability of performing different maneuvers. A safety factor may also be returned, which could be used to determine alternate safe maneuvers. 4. Mission decisions based on whether the airframe can safely perform the required maneuvers, and if not, what maneuvers can be performed that would still enable it to satisfy the mission.
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Anticipated Benefits
Prognosis of failures and faults and contingency management methods on composite airframe structures allow for the extension of vehicle health management onto the structure, which typically represents the majority weight and a large cost of both maintenance and replacement. Prognostics would allow for condition-based maintenance of airframe structures which reduces maintenance costs associated with an air vehicle. Reducing maintenance overheads and enhancing safety will be driving factors for all new aircraft concepts, including the NASA Environmentally Responsive Aviation (ERA) project, the Subsonic Fixed Wing (SFW) project, and airframes for hypersonic and supersonic flight. Additionally, current research aircraft such as NASA's WB-57F would benefit from the prognostics developed here to extend the life of the airframe or improve mission capability based on RUL and airframe condition assessment. Finally, space applications such as launch vehicles and payload and pressurized modules, including the ISS laboratories, would benefit from prognostic applications of composite structures in order to assess the structural capability and any damage or degradation that might endanger crew or payload. The overall commercial fitness of this prognostic algorithm is very high due to the large field of structures for which it enables condition-based maintenance and enhances design life and safety.
This program will provide a contingency management system that dynamically performs decision-making based on both sensed and predictive information to carry out adaptive missions and maintenance. Targeted at composite airframes, the market opportunity for such a system is very significant for the UAV industry, as it is clear that UAVs cannot be made in the same manner as conventional, manned aircraft. Their cost of construction must be much lower, i.e., cheaper materials, less labor and fewer parts. In addition, the ability to make small, custom runs will be commercially very attractive – the lead times for conventional aircraft are many years. These commercial imperatives will drive the adoption of low-cost, composite airframes constructed largely automatically. Rotorcraft such as the Sikorsky CH-53E and the upcoming CH-53K, as well as commercial aircraft such as the Boeing 777 and 787 all incorporate various levels of vehicle health management to monitor subsystems for faults and failures. Prognosis of failures and faults and contingency management on composite airframe structures allow for the extension of vehicle health management onto the structure, which typically represents the majority weight and a large cost of both maintenance and replacement. Aircraft such as Aurora's Orion long endurance aircraft would benefit from airframe prognostics, and we would push for its application both on our own platforms as well as other OEM air vehicle providers. More »
This program will provide a contingency management system that dynamically performs decision-making based on both sensed and predictive information to carry out adaptive missions and maintenance. Targeted at composite airframes, the market opportunity for such a system is very significant for the UAV industry, as it is clear that UAVs cannot be made in the same manner as conventional, manned aircraft. Their cost of construction must be much lower, i.e., cheaper materials, less labor and fewer parts. In addition, the ability to make small, custom runs will be commercially very attractive – the lead times for conventional aircraft are many years. These commercial imperatives will drive the adoption of low-cost, composite airframes constructed largely automatically. Rotorcraft such as the Sikorsky CH-53E and the upcoming CH-53K, as well as commercial aircraft such as the Boeing 777 and 787 all incorporate various levels of vehicle health management to monitor subsystems for faults and failures. Prognosis of failures and faults and contingency management on composite airframe structures allow for the extension of vehicle health management onto the structure, which typically represents the majority weight and a large cost of both maintenance and replacement. Aircraft such as Aurora's Orion long endurance aircraft would benefit from airframe prognostics, and we would push for its application both on our own platforms as well as other OEM air vehicle providers. More »
Primary U.S. Work Locations and Key Partners
| Organizations Performing Work | Role | Type | Location |
|---|---|---|---|
| Aurora Flight Sciences Corporation | Lead Organization | Industry | Cambridge, Massachusetts |
Ames Research Center
(ARC)
|
Supporting Organization | NASA Center | Moffett Field, California |
Primary U.S. Work Locations
-
California
-
Massachusetts
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This is a historic project that was completed before the creation of TechPort on October 1, 2012. Available data has been included. This record may contain less data than currently active projects.