16,605 research outputs found

    Prognostic Reasoner based adaptive power management system for a more electric aircraft

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    This research work presents a novel approach that addresses the concept of an adaptive power management system design and development framed in the Prognostics and Health Monitoring(PHM) perspective of an Electrical power Generation and distribution system(EPGS).PHM algorithms were developed to detect the health status of EPGS components which can accurately predict the failures and also able to calculate the Remaining Useful Life(RUL), and in many cases reconfigure for the identified system and subsystem faults. By introducing these approach on Electrical power Management system controller, we are gaining a few minutes lead time to failures with an accurate prediction horizon on critical systems and subsystems components that may introduce catastrophic secondary damages including loss of aircraft. The warning time on critical components and related system reconfiguration must permits safe return to landing as the minimum criteria and would enhance safety. A distributed architecture has been developed for the dynamic power management for electrical distribution system by which all the electrically supplied loads can be effectively controlled.A hybrid mathematical model based on the Direct-Quadrature (d-q) axis transformation of the generator have been formulated for studying various structural and parametric faults. The different failure modes were generated by injecting faults into the electrical power system using a fault injection mechanism. The data captured during these studies have been recorded to form a “Failure Database” for electrical system. A hardware in loop experimental study were carried out to validate the power management algorithm with FPGA-DSP controller. In order to meet the reliability requirements a Tri-redundant electrical power management system based on DSP and FPGA has been develope

    Technology for large space systems: A special bibliography with indexes (supplement 03)

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    A bibliography containing 217 abstracts addressing the technology for large space systems is presented. State of the art and advanced concepts concerning interactive analysis and design, structural concepts, control systems, electronics, advanced materials, assembly concepts, propulsion, solar power satellite systems, and flight experiments are represented

    A machine learning enabled multi-fidelity platform for the integrated design of aircraft systems

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    The push toward reducing the aircraft development cycle timemotivates the development of collaborative frameworks that enable themore integrated design of aircraft and their systems. The ModellIng and Simulation tools for Systems IntegratiONon Aircraft (MISSION) project aims to develop an integratedmodelling and simulation framework. This paper focuses on some recent advancements in theMISSION project and presents a design framework that combines a filtering process to down-select feasible architectures, amodeling platformthat simulates the power system of the aircraft, and a machine learning-based clustering and optimization module. This framework enables the designer to prioritize different designs and offers traceability on the optimal choices. In addition, it enables the integration of models at multiple levels of fidelity depending on the size of the design space and the accuracy required. It is demonstrated for the electrification of the Primary Flight Control System (PFCS) and the landing gear braking system using different electric actuation technologies. The performance of different architectures is analyzed with respect to key performance indicators (fuel burn, weight, power). The optimization process benefits from a data-driven localization step to identify sets of similar architectures. The framework demonstrates the capability of optimizing across multiple, different system architectures in an efficient way that is scalable for larger design spaces and larger dimensionality problems

    Architecture and Information Requirements to Assess and Predict Flight Safety Risks During Highly Autonomous Urban Flight Operations

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    As aviation adopts new and increasingly complex operational paradigms, vehicle types, and technologies to broaden airspace capability and efficiency, maintaining a safe system will require recognition and timely mitigation of new safety issues as they emerge and before significant consequences occur. A shift toward a more predictive risk mitigation capability becomes critical to meet this challenge. In-time safety assurance comprises monitoring, assessment, and mitigation functions that proactively reduce risk in complex operational environments where the interplay of hazards may not be known (and therefore not accounted for) during design. These functions can also help to understand and predict emergent effects caused by the increased use of automation or autonomous functions that may exhibit unexpected non-deterministic behaviors. The envisioned monitoring and assessment functions can look for precursors, anomalies, and trends (PATs) by applying model-based and data-driven methods. Outputs would then drive downstream mitigation(s) if needed to reduce risk. These mitigations may be accomplished using traditional design revision processes or via operational (and sometimes automated) mechanisms. The latter refers to the in-time aspect of the system concept. This report comprises architecture and information requirements and considerations toward enabling such a capability within the domain of low altitude highly autonomous urban flight operations. This domain may span, for example, public-use surveillance missions flown by small unmanned aircraft (e.g., infrastructure inspection, facility management, emergency response, law enforcement, and/or security) to transportation missions flown by larger aircraft that may carry passengers or deliver products. Caveat: Any stated requirements in this report should be considered initial requirements that are intended to drive research and development (R&D). These initial requirements are likely to evolve based on R&D findings, refinement of operational concepts, industry advances, and new industry or regulatory policies or standards related to safety assurance

    Aeronautical Engineering: A special bibliography with indexes, supplement 62

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    This bibliography lists 306 reports, articles, and other documents introduced into the NASA scientific and technical information system in September 1975

    UltraSwarm: A Further Step Towards a Flock of Miniature Helicopters

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    We describe further progress towards the development of a MAV (micro aerial vehicle) designed as an enabling tool to investigate aerial flocking. Our research focuses on the use of low cost off the shelf vehicles and sensors to enable fast prototyping and to reduce development costs. Details on the design of the embedded electronics and the modification of the chosen toy helicopter are presented, and the technique used for state estimation is described. The fusion of inertial data through an unscented Kalman filter is used to estimate the helicopter’s state, and this forms the main input to the control system. Since no detailed dynamic model of the helicopter in use is available, a method is proposed for automated system identification, and for subsequent controller design based on artificial evolution. Preliminary results obtained with a dynamic simulator of a helicopter are reported, along with some encouraging results for tackling the problem of flocking

    Technology for large space systems: A special bibliography with indexes (supplement 04)

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    This bibliography lists 259 reports, articles, and other documents introduced into the NASA scientific and technical information system between July 1, 1980 and December 31, 1980. Its purpose is to provide information to the researcher, manager, and designer in technology development and mission design in the area of the Large Space Systems Technology Program. Subject matter is grouped according to systems, interactive analysis and design. Structural concepts, control systems, electronics, advanced materials, assembly concepts, propulsion, solar power satellite systems, and flight experiments

    A Model-Based Systems Engineering Approach to e-VTOL Aircraft and Airspace Infrastructure Design for Urban Air Mobility

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    This paper serves to contribute to Model-Based Systems Engineering (MBSE) by following the NASA Systems Engineering Handbook framework for a Systems Engineering (SE) design approach to an Electric Vertical Takeoff and Landing (e-VTOL) aircraft and the incorporating airspace infrastructure. The focus of this study is, by using the MBSE model created, to capture the technical requirements definition and design intent of the vehicle and airspace inclusive of community specific knowledge derived from the Federal Aviation Administration (FAA) NextGen Urban Air Mobility (UAM) Concept of Operations (ConOps) version 1.0. The stakeholder requirements derived from the FAA UAM NextGen ConOps will form the bedrock for the aircraft infrastructure requirements from which the flight mission requirements are derived. From these requirements, the profile of a notional flight mission is provided. Additionally, from the flight mission requirements, a design solution can be proposed and examined to ensure it meets the original stakeholder needs. The vehicle and associated airspace environment are modeled using an MBSE dedicated platform, Cameo Systems Modeler, in a language called SysML. The resulting MBSE model created can demonstrate the traceability between top-level system requirements down to the subcomponent-level design. In the conclusive study of the sub-system behavioral relationships, the analysis and validation of the proposed design solution can support model reliability
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