997 resultados para Flight engineering


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Ratites are large, flightless birds and include the ostrich, rheas, kiwi, emu, and cassowaries, along with extinct members, such as moa and elephant birds. Previous phylogenetic analyses of complete mitochondrial genome sequences have reinforced the traditional belief that ratites are monophyletic and tinamous are their sister group. However, in these studies ratite monophyly was enforced in the analyses that modeled rate heterogeneity among variable sites. Relaxing this topological constraint results in strong support for the tinamous (which fly) nesting within ratites. Furthermore, upon reducing base compositional bias and partitioning models of sequence evolution among protein codon positions and RNA structures, the tinamou–moa clade grouped with kiwi, emu, and cassowaries to the exclusion of the successively more divergent rheas and ostrich. These relationships are consistent with recent results from a large nuclear data set, whereas our strongly supported finding of a tinamou–moa grouping further resolves palaeognath phylogeny. We infer flight to have been lost among ratites multiple times in temporally close association with the Cretaceous–Tertiary extinction event. This circumvents requirements for transient microcontinents and island chains to explain discordance between ratite phylogeny and patterns of continental breakup. Ostriches may have dispersed to Africa from Eurasia, putting in question the status of ratites as an iconic Gondwanan relict taxon. [Base composition; flightless; Gondwana; mitochondrial genome; Palaeognathae; phylogeny; ratites.]

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This paper presents the flight trials of an electro-optical (EO) sense-and-avoid system onboard a Cessna host aircraft (camera aircraft). We focus on the autonomous collision avoidance capability of the sense-and-avoid system; that is, closed-loop integration with the onboard aircraft autopilot. We also discuss the system’s approach to target detection and avoidance control, as well as the methodology of the flight trials. The results demonstrate the ability of the sense-and-avoid system to automatically detect potential conflicting aircraft and engage the host Cessna autopilot to perform an avoidance manoeuvre, all without any human intervention

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This paper investigates a mixed centralised-decentralised air traffic separation management system, which combines the best features of the centralised and decentralised systems whilst ensuring the reliability of the air traffic management system during degraded conditions. To overcome communication band limits, we propose a mixed separation manager on the basis of a robust decision (or min-max) problem that is posed on a reduced set of admissible flight avoidance manoeuvres (or a FAM alphabet). We also present a design method for selecting an appropriate FAM alphabet for use in the mixed separation management system. Simulation studies are presented to illustrate the benefits of our proposed FAM alphabet based mixed separation manager.

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This paper presents an approach to derive requirements for an avionics architecture that provides onboard sense-and-avoid and autonomous emergency forced landing capabilities to a UAS. The approach is based on two design paradigms that (1) derive requirements analyzing the common functionality between these two functions to then derive requirements for sensors, computing capability, interfaces, etc. (2) consider the risk and safety mitigation associated with these functions to derive certification requirements for the system design. We propose to use the Aircraft Certification Matrix (ACM) approach to tailor the system Development Assurance Levels (DAL) and architecture requirements in accordance with acceptable risk criteria. This architecture is developed under the name “Flight Guardian”. Flight Guardian is an avionics architecture that integrates common sensory elements that are essential components of any UAS that is required to be dependable. The Flight Guardian concept is also applicable to conventionally piloted aircraft, where it will serve to reduce cockpit workload.

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The future emergence of many types of airborne vehicles and unpiloted aircraft in the national airspace means collision avoidance is of primary concern in an uncooperative airspace environment. The ability to replicate a pilot’s see and avoid capability using cameras coupled with vision based avoidance control is an important part of an overall collision avoidance strategy. But unfortunately without range collision avoidance has no direct way to guarantee a level of safety. Collision scenario flight tests with two aircraft and a monocular camera threat detection and tracking system were used to study the accuracy of image-derived angle measurements. The effect of image-derived angle errors on reactive vision-based avoidance performance was then studied by simulation. The results show that whilst large angle measurement errors can significantly affect minimum ranging characteristics across a variety of initial conditions and closing speeds, the minimum range is always bounded and a collision never occurs.

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The main objective of this paper is to describe the development of a remote sensing airborne air sampling system for Unmanned Aerial Systems (UAS) and provide the capability for the detection of particle and gas concentrations in real time over remote locations. The design of the air sampling methodology started by defining system architecture, and then by selecting and integrating each subsystem. A multifunctional air sampling instrument, with capability for simultaneous measurement of particle and gas concentrations was modified and integrated with ARCAA’s Flamingo UAS platform and communications protocols. As result of the integration process, a system capable of both real time geo-location monitoring and indexed-link sampling was obtained. Wind tunnel tests were conducted in order to evaluate the performance of the air sampling instrument in controlled nonstationary conditions at the typical operational velocities of the UAS platform. Once the remote fully operative air sampling system was obtained, the problem of mission design was analyzed through the simulation of different scenarios. Furthermore, flight tests of the complete air sampling system were then conducted to check the dynamic characteristics of the UAS with the air sampling system and to prove its capability to perform an air sampling mission following a specific flight path.

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This paper outlines an innovative and feasible flight control scheme for a rotary-wing unmanned aerial system (RUAS) with guaranteed safety and reliable flight quality in a gusty environment. The proposed control methodology aims to increase gust-attenuation capability of a RUAS to ensure improved flight performance when strong gusts occur. Based on the design of an effective estimator, an altitude controller is firstly constructed to synchronously compensate for fluctuations of the main rotor thrust which might lead to crashes in a gusty environment. Afterwards, a nonlinear state feedback controller is proposed to stabilize horizontal positions of the RUAS with gust-attenuation property. Performance of the proposed control framework is evaluated using parameters of a Vario XLC helicopter and high-fidelity simulations show that the proposed controllers can effectively reduce side-effect of gusts and demonstrate performance improvement when compared with the proportional-integral-derivative (PID) controllers.

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This paper presents a nonlinear gust-attenuation controller based on constrained neural-network (NN) theory. The controller aims to achieve sufficient stability and handling quality for a fixed-wing unmanned aerial system (UAS) in a gusty environment when control inputs are subjected to constraints. Constraints in inputs emulate situations where aircraft actuators fail requiring the aircraft to be operated with fail-safe capability. The proposed controller enables gust-attenuation property and stabilizes the aircraft dynamics in a gusty environment. The proposed flight controller is obtained by solving the Hamilton-Jacobi-Isaacs (HJI) equations based on an policy iteration (PI) approach. Performance of the controller is evaluated using a high-fidelity six degree-of-freedom Shadow UAS model. Simulations show that our controller demonstrates great performance improvement in a gusty environment, especially in angle-of-attack (AOA), pitch and pitch rate. Comparative studies are conducted with the proportional-integral-derivative (PID) controllers, justifying the efficiency of our controller and verifying its suitability for integration into the design of flight control systems for forced landing of UASs.

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This paper presents a practical scheme to control heave motion for hover and automatic landing of a Rotary-wing Unmanned Aerial Vehicle (RUAV) in the presence of strong horizontal gusts. A heave motion model is constructed for the purpose of capturing dynamic variations of thrust due to horizontal gusts. Through construction of an effective gust estimator, a feedback-feedforward controller is developed which uses available measurements from onboard sensors. The proposed controller dynamically and synchronously compensates for aerodynamic variations of heave motion, enhancing disturbance-attenuation capability of the RUAV. Simulation results justify the reliability and efficiency of the suggested gust estimator. Moreover, flight tests conducted on our Eagle helicopter verify suitability of the proposed control strategy for small RUAVs operating in a gusty environment.

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This paper describes a generic and integrated solar powered remote Unmanned Air Vehicles (UAV) and Wireless Sensor Network (WSN) gas sensing system. The system uses a generic gas sensing system for CH4 and CO2 concentrations using metal oxide (MoX) and non-dispersive infrared sensors, and a new solar cell encapsulation method to power the UASs as well as a data management platform to store, analyse and share the information with operators and external users. The system was successfully field tested at ground and low altitudes, collecting, storing and transmitting data in real time to a central node for analysis and 3D mapping. The system can be used in a wide range of outdoor applications, especially in agriculture, bushfires, mining studies, opening the way to a ubiquitous low cost environmental monitoring. A video of the bench and flight test performed can be seen in the following link https://www.youtube.com/watch?v=Bwas7stYIxQ.

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Stagnation-point total heat transfer was measured on a 1:27.7 model of the Flight Investigation of Reentry Environment II flight vehicle. Experiments were performed in the X1 expansion tube at an equivalent flight velocity and static enthalpy of 11 km/s and 12.7 MJ/kg, respectively. Conditions were chosen to replicate the flight condition at a total flight time of 1639.5 s, where radiation contributed an estimated 17-36% of the total heat transfer. This contribution is theorized to reduce to <2% in the scaled experiments, and the heating environment on the test model was expected to be dominated by convection. A correlation between reported flight heating rates and expected experimental heating, referred to as the reduced flight value, was developed to predict the level of heating expected on the test model. At the given flow conditions, the reduced flight value was calculated to be 150 MW/m2. Average stagnation-point total heat transfer was measured to be 140 ± 7% W/m2, showing good agreement with the predicted value. Experimentally measured heat transfer was found to have good agreement of between 5 and 15% with a number of convective heating correlations, confirming that convection dominates the tunnel heating environment, and that useful experimental measurements could be made in weakly coupled radiating flow

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We present a pole inspection system for outdoor environments comprising a high-speed camera on a vertical take-off and landing (VTOL) aerial platform. The pole inspection task requires a vehicle to fly close to a structure while maintaining a fixed stand-off distance from it. Typical GPS errors make GPS-based navigation unsuitable for this task however. When flying outdoors a vehicle is also affected by aerodynamics disturbances such as wind gusts, so the onboard controller must be robust to these disturbances in order to maintain the stand-off distance. Two problems must therefor be addressed: fast and accurate state estimation without GPS, and the design of a robust controller. We resolve these problems by a) performing visual + inertial relative state estimation and b) using a robust line tracker and a nested controller design. Our state estimation exploits high-speed camera images (100Hz) and 70Hz IMU data fused in an Extended Kalman Filter (EKF). We demonstrate results from outdoor experiments for pole-relative hovering, and pole circumnavigation where the operator provides only yaw commands. Lastly, we show results for image-based 3D reconstruction and texture mapping of a pole to demonstrate the usefulness for inspection tasks.

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The design activities of the development of the SCRAMSPACE I scramjet-powered free-flight experiment are described in this paper. The objectives of this flight are first described together with the definition of the primary, secondary and tertiary experiments. The Scramjet configuration studied is first discussed together with the rocket motor system selected for this flight. The different flight sequences are then explained, highlighting the SCRAMSPACE I free-flyer separation and re-orientation procedures. A design trade-off study is then described considering vehicle stability, packaging, thermo-structural analysis and trajectory, discussing the alignment of the predicted performance with the mission scientific requirements. The global system architecture and instrumentation of the vehicle are then explained. The conclusions of this design phase are that a vehicle design has been produced which is able to meet the mission scientific goals and the procurement & construction of the vehicle are ongoing.

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In this paper, we propose a framework for joint allocation and constrained control design of flight controllers for Unmanned Aircraft Systems (UAS). The actuator configuration is used to map actuator constraint set into the space of the aircraft generalised forces. By constraining the demanded generalised forces, we ensure that the allocation problem is always feasible; and therefore, it can be solved without constraints. This leads to an allocation problem that does not require on-line numerical optimisation. Furthermore, since the controller handles the constraints, and there is no need to implement heuristics to inform the controller about actuator saturation. The latter is fundamental for avoiding Pilot Induced Oscillations (PIO) in remotely operated UAS due to the rate limit on the aircraft control surfaces.

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As Unmanned Aircraft Systems (UAS) grow in complexity, and their level of autonomy increases|moving away from the concept of a remotely piloted systems and more towards autonomous systems|there is a need to further improve reliability and tolerance to faults. The traditional way to accommodate actuator faults is by using standard control allocation techniques as part of the flight control system. The allocation problem in the presence of faults often requires adding constraints that quantify the maximum capacity of the actuators. This in turn requires on-line numerical optimisation. In this paper, we propose a framework for joint allocation and constrained control scheme via vector input scaling. The actuator configuration is used to map actuator constraints into the space of the aircraft generalised forces, which are the magnitudes demanded by the light controller. Then by constraining the output of controller, we ensure that the allocation function always receive feasible demands. With the proposed framework, the allocation problem does not require numerical optimisation, and since the controller handles the constraints, there is not need to implement heuristics to inform the controller about actuator saturation.