983 resultados para Terminazione forzata, Flight Termination System, FTS, APR


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Experimental evidence suggests that high strain rates, stresses, strains and temperatures are experienced near sliding interfaces. The associated microstructural changes are due to several dynamic an interacting phenomena. 3D non-equilibrium molecular dynamics (MD) simulations of sliding were conducted with the aim of understanding the dynamic processes taking place in crystalline tribopairs, with a focus on plastic deformation and microstructural evolution. Embedded atom potentials were employed for simulating sliding of an Fe-Cu tribopair. Sliding velocity, crystal orientation and presence of lattice defects were some of the variables in these simulations. Extensive plastic deformation involving dislocation and twin activity, dynamic recrystallization, amorphization and/or nanocrystallization, mechanical mixing and material transfer were observed. Mechanical mixing in the vicinity of the sliding interface was observed even in the Fe-Cu system, which would cluster under equilibrium conditions, hinting at the ballistic nature of the process. Flow localization was observed at high velocities implying the possible role of adiabatic heating. The presence of preexisting defects (such as dislocations and interfaces) played a pivotal role in determining friction and microstructural evolution. The study also shed light on the relationship between adhesion and plastic deformation, and friction. Comparisons with experiments suggest that such simulations can indeed provide valuable insights that are difficult to obtain from experiments.

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There is an increased interest on the use of UAVs for environmental research such as tracking bush fires, volcanic eruptions, chemical accidents or pollution sources. The aim of this paper is to describe the theory and results of a bio-inspired plume tracking algorithm. A method for generating sparse plumes in a virtual environment was also developed. Results indicated the ability of the algorithms to track plumes in 2D and 3D. The system has been tested with hardware in the loop (HIL) simulations and in flight using a CO2 gas sensor mounted to a multi-rotor UAV. The UAV is controlled by the plume tracking algorithm running on the ground control station (GCS).

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There is an increased interest in the use of Unmanned Aerial Vehicles for load transportation from environmental remote sensing to construction and parcel delivery. One of the main challenges is accurate control of the load position and trajectory. This paper presents an assessment of real flight trials for the control of an autonomous multi-rotor with a suspended slung load using only visual feedback to determine the load position. This method uses an onboard camera to take advantage of a common visual marker detection algorithm to robustly detect the load location. The load position is calculated using an onboard processor, and transmitted over a wireless network to a ground station integrating MATLAB/SIMULINK and Robotic Operating System (ROS) and a Model Predictive Controller (MPC) to control both the load and the UAV. To evaluate the system performance, the position of the load determined by the visual detection system in real flight is compared with data received by a motion tracking system. The multi-rotor position tracking performance is also analyzed by conducting flight trials using perfect load position data and data obtained only from the visual system. Results show very accurate estimation of the load position (~5% Offset) using only the visual system and demonstrate that the need for an external motion tracking system is not needed for this task.

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The use of UAVs for remote sensing tasks; e.g. agriculture, search and rescue is increasing. The ability for UAVs to autonomously find a target and perform on-board decision making, such as descending to a new altitude or landing next to a target is a desired capability. Computer-vision functionality allows the Unmanned Aerial Vehicle (UAV) to follow a designated flight plan, detect an object of interest, and change its planned path. In this paper we describe a low cost and an open source system where all image processing is achieved on-board the UAV using a Raspberry Pi 2 microprocessor interfaced with a camera. The Raspberry Pi and the autopilot are physically connected through serial and communicate via MAVProxy. The Raspberry Pi continuously monitors the flight path in real time through USB camera module. The algorithm checks whether the target is captured or not. If the target is detected, the position of the object in frame is represented in Cartesian coordinates and converted into estimate GPS coordinates. In parallel, the autopilot receives the target location approximate GPS and makes a decision to guide the UAV to a new location. This system also has potential uses in the field of Precision Agriculture, plant pest detection and disease outbreaks which cause detrimental financial damage to crop yields if not detected early on. Results show the algorithm is accurate to detect 99% of object of interest and the UAV is capable of navigation and doing on-board decision making.

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This report summarises the development of an Unmanned Aerial System and an integrated Wireless Sensor Network (WSN), suitable for the real world application in remote sensing tasks. Several aspects are discussed and analysed to provide improvements in flight duration, performance and mobility of the UAV, while ensuring the accuracy and range of data from the wireless sensor system.

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Transparent glasses and glass nano crystal composites (GNCs) of various compositions in the system (100 - x)Li2B4O7-x (BaO-Bi2O3-Nb2O5) (where x = 10, 20, and 30 in molar ratio) were fabricated via splat-quenching technique. The glassy nature of the as quenched samples was established by differential thermal analyses. X-ray powder diffraction and transmission electron microscopic (TEM) studies confirmed the formation of layered perovskite BBN via a fluorite like phase. TEM studies revealed the presence of 10 nm sized spherical crystallites of fluorite like BaBi2Nb2O9 phase in the glassy matrix of Li2B4O7 (LBO). The influence of composition on the dielectric and the optical properties (transmission, optical band gap) of these samples has been investigated. (c) 2007 Elsevier B.V. All rights reserved.

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A reliable protection against direct lightning hit is very essential for satellite launch pads. In view of this, suitable protection systems are generally employed. The evaluation of efficacy of the lightning protection schemes among others requires an accurate knowledge of the consequential potential rise at the struck point and the current injected into soil at the earth termination. The present work has made a detailed effort to deduce these quantities for the lightning protection scheme of the Indian satellite launch pad-I. A reduced scale model of the system with a frequency domain approach is employed for the experimental study. For further validation of the experimental approach, numerical simulations using numerical electromagnetic code-2 are also carried out on schemes involving single tower. The study results on the protection system show that the present design is quite safe with regard to top potential rise. It is shown that by connecting ground wires to the tower, its base current and, hence, the soil potential rise can be reduced. An evaluation of an alternate design philosophy involving insulated mast scheme is also made. The potential rise in that design is quantified and the possibility of a flashover to supporting tower is briefly looked into. The supporting tower is shown to have significant induced currents.

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This chapter presents the real time validation of fixed order robust 112 controller designed for the lateral stabilisation of a micro air vehicle named Sarika2. Digital signal processor (DSP) based onboard computer named flight instrumentation controller (FIC) is designed to operate under automatic or manual mode. FIC gathers data from multitude of sensors and is capable of closed loop control to enable autonomous flight. Fixed order lateral H-2 controller designed with the features such as incorporation of level I flying qualities, gust alleviation and noise rejection is coded on to the FIC. Challenging real time hardware in loop simulation (HILS) is done with dSPACE1104 RTI/RTW. Responses obtained from the HILS are compared with those obtained from the offline simulation. Finally, flight trials are conducted to demonstrate the satisfactory performance of the closed loop system. The generic design methodology developed is applicable to all classes of Mini and Micro air vehicles.

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The motivation behind the fusion of Intrusion Detection Systems was the realization that with the increasing traffic and increasing complexity of attacks, none of the present day stand-alone Intrusion Detection Systems can meet the high demand for a very high detection rate and an extremely low false positive rate. Multi-sensor fusion can be used to meet these requirements by a refinement of the combined response of different Intrusion Detection Systems. In this paper, we show the design technique of sensor fusion to best utilize the useful response from multiple sensors by an appropriate adjustment of the fusion threshold. The threshold is generally chosen according to the past experiences or by an expert system. In this paper, we show that the choice of the threshold bounds according to the Chebyshev inequality principle performs better. This approach also helps to solve the problem of scalability and has the advantage of failsafe capability. This paper theoretically models the fusion of Intrusion Detection Systems for the purpose of proving the improvement in performance, supplemented with the empirical evaluation. The combination of complementary sensors is shown to detect more attacks than the individual components. Since the individual sensors chosen detect sufficiently different attacks, their result can be merged for improved performance. The combination is done in different ways like (i) taking all the alarms from each system and avoiding duplications, (ii) taking alarms from each system by fixing threshold bounds, and (iii) rule-based fusion with a priori knowledge of the individual sensor performance. A number of evaluation metrics are used, and the results indicate that there is an overall enhancement in the performance of the combined detector using sensor fusion incorporating the threshold bounds and significantly better performance using simple rule-based fusion.

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Hypertension is a major risk factor for stroke, ischaemic heart disease, and the development of heart failure. Hypertension-induced heart failure is usually preceded by the development of left ventricular hypertrophy (LVH), which represents an adaptive and compensatory response to the increased cardiac workload. Biomechanical stress and neurohumoral activation are the most important triggers of pathologic hypertrophy and the transition of cardiac hypertrophy to heart failure. Non-clinical and clinical studies have also revealed derangements of energy metabolism in hypertensive heart failure. The goal of this study was to investigate in experimental models the molecular mechanisms and signalling pathways involved in hypertension-induced heart failure with special emphasis on local renin-angiotensin-aldosterone system (RAAS), cardiac metabolism, and calcium sensitizers, a novel class of inotropic agents used currently in the treatment of acute decompensated heart failure. Two different animal models of hypertensive heart failure were used in the present study, i.e. hypertensive and salt-sensitive Dahl/Rapp rats on a high salt diet (a salt-sensitive model of hypertensive heart failure) and double transgenic rats (dTGR) harboring human renin and human angiotensinogen genes (a transgenic model of hypertensive heart failure with increased local RAAS activity). The influence of angiotensin II (Ang II) on cardiac substrate utilization and cardiac metabolomic profile was investigated by using gas chromatography coupled to time-of-flight mass spectrometry to detect 247 intermediary metabolites. It was found that Ang II could alter cardiac metabolomics both in normotensive and hypertensive rats in an Ang II receptor type 1 (AT1)-dependent manner. A distinct substrate use from fatty acid oxidation towards glycolysis was found in dTGR. Altered cardiac substrate utilization in dTGR was associated with mitochondrial dysfunction. Cardiac expression of the redox-sensitive metabolic sensor sirtuin1 (SIRT1) was increased in dTGR. Resveratrol supplementation prevented cardiovascular mortality and ameliorated Ang II-induced cardiac remodeling in dTGR via blood pressure-dependent pathways and mechanisms linked to increased mitochondrial biogenesis. Resveratrol dose-dependently increased SIRT1 activity in vitro. Oral levosimendan treatment was also found to improve survival and systolic function in dTGR via blood pressure-independent mechanisms, and ameliorate Ang II-induced coronary and cardiomyocyte damage. Finally, using Dahl/Rapp rats it was demonstrated that oral levosimendan as well as the AT1 receptor antagonist valsartan improved survival and prevented cardiac remodeling. The beneficial effects of levosimendan were associated with improved diastolic function without significantly improved systolic changes. These positive effects were potentiated when the drug combination was administered. In conclusion, the present study points to an important role for local RAAS in the pathophysiology of hypertension-induced heart failure as well as its involvement as a regulator of cardiac substrate utilization and mitochondrial function. Our findings suggest a therapeutic role for natural polyphenol resveratrol and calcium sensitizer, levosimendan, and the novel drug combination of valsartan and levosimendan, in prevention of hypertension-induced heart failure. The present study also provides a better understanding of the pathophysiology of hypertension-induced heart failure, and may help identify potential targets for novel therapeutic interventions.

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A fuzzy logic system is developed for helicopter rotor system fault isolation. Inputs to the fuzzy logic system are measurement deviations of blade bending and torsion response and vibration from a "good" undamaged helicopter rotor. The rotor system measurements used are flap and lag bending tip deflections, elastic twist deflection at the tip, and three forces and three moments at the rotor hub. The fuzzy logic system uses rules developed from an aeroelastic model of the helicopter rotor with implanted faults to isolate the fault while accounting for uncertainty in the measurements. The faults modeled include moisture absorption, loss of trim mass, damaged lag damper, damaged pitch control system, misadjusted pitch link, and damaged flap. Tests with simulated data show that the fuzzy system isolates rotor system faults with an accuracy of about 90-100%. Furthermore, the fuzzy system is robust and gives excellent results, even when some measurements are not available. A rule-based expert system based on similar rules from the aeroelastic model performs much more poorly than the fuzzy system in the presence of high levels of uncertainty.

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In arriving at the ideal filter transfer function for an active noise control system in a duct, the effect of the auxiliary sources (generally loudspeakers) on the waves generated by the primary source has invariably been neglected in the existing literature, implying a rigid wall or infinite impedance. The present paper presents a fairly general analysis of a linear one-dimensional noise control system by means of block diagrams and transfer functions. It takes into account the passive as well as active role of a terminal primary source, wall-mounted auxiliary source, open duct radiation impedance, and the effects of mean flow and damping. It is proved that the pressure generated by a source against a load impedance can be looked upon as a sum of two pressure waves, one generated by the source against an anechoic termination and the other by reflecting the rearward wave (incident on the source) off the passive source impedance. Application of this concept is illustrated for both the types of sources. A concise closed-form expression for the ideal filter transfer function is thus derived and discussed. Finally, the dynamics of an adaptive noise control system is discussed briefly, relating its standing-wave variables and transfer functions with those of the progressive-wave model presented here.

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SARAS is a correlation spectrometer purpose designed for precision measurements of the cosmic radio background and faint features in the sky spectrum at long wavelengths that arise from redshifted 21-cm from gas in the reionization epoch. SARAS operates in the octave band 87.5-175 MHz. We present herein the system design arguing for a complex correlation spectrometer concept. The SARAS design concept provides a differential measurement between the antenna temperature and that of an internal reference termination, with measurements in switched system states allowing for cancellation of additive contaminants from a large part of the signal flow path including the digital spectrometer. A switched noise injection scheme provides absolute spectral calibration. Additionally, we argue for an electrically small frequency-independent antenna over an absorber ground. Various critical design features that aid in avoidance of systematics and in providing calibration products for the parametrization of other unavoidable systematics are described and the rationale discussed. The signal flow and processing is analyzed and the response to noise temperatures of the antenna, reference termination and amplifiers is computed. Multi-path propagation arising from internal reflections are considered in the analysis, which includes a harmonic series of internal reflections. We opine that the SARAS design concept is advantageous for precision measurement of the absolute cosmic radio background spectrum; therefore, the design features and analysis methods presented here are expected to serve as a basis for implementations tailored to measurements of a multiplicity of features in the background sky at long wavelengths, which may arise from events in the dark ages and subsequent reionization era.

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We present a localization system that targets rapid deployment of stationary wireless sensor networks (WSN). The system uses a particle filter to fuse measurements from multiple localization modalities, such as RF ranging, neighbor information or maps, to obtain position estimations with higher accuracy than that of the individual modalities. The system isolates different modalities into separate components which can be included or excluded independently to tailor the system to a specific scenario. We show that position estimations can be improved with our system by combining multiple modalities. We evaluate the performance of the system in both an indoor and outdoor environment using combinations of five different modalities. Using two anchor nodes as reference points and combining all five modalities, we obtain RMS (Root Mean Square) estimation errors of approximately 2.5m in both cases, while using the components individually results in errors within the range of 3.5 and 9 m.

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Facial emotions are the most expressive way to display emotions. Many algorithms have been proposed which employ a particular set of people (usually a database) to both train and test their model. This paper focuses on the challenging task of database independent emotion recognition, which is a generalized case of subject-independent emotion recognition. The emotion recognition system employed in this work is a Meta-Cognitive Neuro-Fuzzy Inference System (McFIS). McFIS has two components, a neuro-fuzzy inference system, which is the cognitive component and a self-regulatory learning mechanism, which is the meta-cognitive component. The meta-cognitive component, monitors the knowledge in the neuro-fuzzy inference system and decides on what-to-learn, when-to-learn and how-to-learn the training samples, efficiently. For each sample, the McFIS decides whether to delete the sample without being learnt, use it to add/prune or update the network parameter or reserve it for future use. This helps the network avoid over-training and as a result improve its generalization performance over untrained databases. In this study, we extract pixel based emotion features from well-known (Japanese Female Facial Expression) JAFFE and (Taiwanese Female Expression Image) TFEID database. Two sets of experiment are conducted. First, we study the individual performance of both databases on McFIS based on 5-fold cross validation study. Next, in order to study the generalization performance, McFIS trained on JAFFE database is tested on TFEID and vice-versa. The performance The performance comparison in both experiments against SVNI classifier gives promising results.