196 resultados para Air search


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This paper addresses a search problem with multiple limited capability search agents in a partially connected dynamical networked environment under different information structures. A self assessment-based decision-making scheme for multiple agents is proposed that uses a modified negotiation scheme with low communication overheads. The scheme has attractive features of fast decision-making and scalability to large number of agents without increasing the complexity of the algorithm. Two models of the self assessment schemes are developed to study the effect of increase in information exchange during decision-making. Some analytical results on the maximum number of self assessment cycles, effect of increasing communication range, completeness of the algorithm, lower bound and upper bound on the search time are also obtained. The performance of the various self assessment schemes in terms of total uncertainty reduction in the search region, using different information structures is studied. It is shown that the communication requirement for self assessment scheme is almost half of the negotiation schemes and its performance is close to the optimal solution. Comparisons with different sequential search schemes are also carried out. Note to Practitioners-In the futuristic military and civilian applications such as search and rescue, surveillance, patrol, oil spill, etc., a swarm of UAVs can be deployed to carry out the mission for information collection. These UAVs have limited sensor and communication ranges. In order to enhance the performance of the mission and to complete the mission quickly, cooperation between UAVs is important. Designing cooperative search strategies for multiple UAVs with these constraints is a difficult task. Apart from this, another requirement in the hostile territory is to minimize communication while making decisions. This adds further complexity to the decision-making algorithms. In this paper, a self-assessment-based decision-making scheme, for multiple UAVs performing a search mission, is proposed. The agents make their decisions based on the information acquired through their sensors and by cooperation with neighbors. The complexity of the decision-making scheme is very low. It can arrive at decisions fast with low communication overheads, while accommodating various information structures used for increasing the fidelity of the uncertainty maps. Theoretical results proving completeness of the algorithm and the lower and upper bounds on the search time are also provided.

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In this work, one-dimensional flow-acoustic analysis of two basic configurations of air cleaners, (i) Rectangular Axial-Inlet, Axial-Outlet (RAIAO) and (ii) Rectangular Transverse-Inlet, Transverse-Outlet (RTITO), has been presented. This 1-D analytical approach has been verified with the help of 3-D FEM based software. Through subtraction of the acoustic performance of the bare plenum (without filter element) from that of the complete air cleaner box, the solitary performance of the filter element has been evaluated. Part of the present analysis illustrates that the analytical formulation remains effective even with offset positioning of the air pipes from the centre of the cross section of the air cleaner. The 1-D analytical tool computes much faster than its 3-D simulation counterpart. The present analysis not only predicts the acoustical impact of mean flow, but it also depicts the scenario with increased resistance of the filter element. Thus, the proposed 1-D analysis would help in the design of acoustically efficient air cleaners for automotive applications. (C) 2011 Institute of Noise Control Engineering.

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The standard quantum search algorithm lacks a feature, enjoyed by many classical algorithms, of having a fixed-point, i.e. a monotonic convergence towards the solution. Here we present two variations of the quantum search algorithm, which get around this limitation. The first replaces selective inversions in the algorithm by selective phase shifts of $\frac{\pi}{3}$. The second controls the selective inversion operations using two ancilla qubits, and irreversible measurement operations on the ancilla qubits drive the starting state towards the target state. Using $q$ oracle queries, these variations reduce the probability of finding a non-target state from $\epsilon$ to $\epsilon^{2q+1}$, which is asymptotically optimal. Similar ideas can lead to robust quantum algorithms, and provide conceptually new schemes for error correction.

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This paper presents a robust fixed order H2controller design using strengthened discrete optimal projection equations, which approximate the first order necessary optimality condition. The novelty of this work is the application of the robust H2controller to a micro aerial vehicle named Sarika2 developed in house. The controller is designed in discrete domain for the lateral dynamics of Sarika2 in the presence of low frequency atmospheric turbulence (gust) and high frequency sensor noise. The design specification includes simultaneous stabilization, disturbance rejection and noise attenuation over the entire flight envelope of the vehicle. The resulting controller performance is comprehensively analyzed by means of simulation

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Soot particles are generated in a flame caused by burning ethylene gas. The particles are collected thermophoretically at different locations of the flame. The particles are used to lubricate a steel/steel ball on flat reciprocating sliding contact, as a dry solid lubricant and also as suspended in hexadecane. Reciprocating contact is shown to establish a protective and low friction tribo-film. The friction correlates with the level of graphitic order of the soot, which is highest in the soot extracted from the mid-flame region and is low in the soot extracted from the flame root and flame tip regions. Micro-Raman spectroscopy of the tribo-film shows that the a priori graphitic order, the molecular carbon content of the soot and the graphitization of the film as brought about by tribology distinguish between the frictions of soot extracted from different regions of the flame, and differentiate the friction associated with dry tribology from that recorded under lubricated tribology.

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Many of the research institutions and universities across the world are facilitating open-access (OA) to their intellectual outputs through their respective OA institutional repositories (IRs) or through the centralized subject-based repositories. The registry of open access repositories (ROAR) lists more than 2850 such repositories across the world. The awareness about the benefits of OA to scholarly literature and OA publishing is picking up in India, too. As per the ROAR statistics, to date, there are more than 90 OA repositories in the country. India is doing particularly well in publishing open-access journals (OAJ). As per the directory of open-access journals (DOAJ), to date, India with 390 OAJs, is ranked 5th in the world in terms of numbers of OAJs being published. Much of the research done in India is reported in the journals published from India. These journals have limited readership and many of them are not being indexed by Web of Science, Scopus or other leading international abstracting and indexing databases. Consequently, research done in the country gets hidden not only from the fellow countrymen, but also from the international community. This situation can be easily overcome if all the researchers facilitate OA to their publications. One of the easiest ways to facilitate OA to scientific literature is through the institutional repositories. If every research institution and university in India set up an open-access IR and ensure that copies of the final accepted versions of all the research publications are uploaded in the IRs, then the research done in India will get far better visibility. The federation of metadata from all the distributed, interoperable OA repositories in the country will serve as a window to the research done across the country. Federation of metadata from the distributed OAI-compliant repositories can be easily achieved by setting up harvesting software like the PKP Harvester. In this paper, we share our experience in setting up a prototype metadata harvesting service using the PKP harvesting software for the OAI-compliant repositories in India.

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A nonlinear suboptimal guidance law is presented in this paper for successful interception of ground targets by air-launched missiles and guided munitions. The main feature of this guidance law is that it accurately satisfies terminal impact angle constraints in both azimuth as well as elevation simultaneously. In addition, it is capable of hitting the target with high accuracy as well as minimizing the lateral acceleration demand. The guidance law is synthesized using recently developed model predictive static programming (MPSP). Performance of the proposed MPSP guidance is demonstrated using three-dimensional (3-D) nonlinear engagement dynamics by considering stationary, moving, and maneuvering targets. Effectiveness of the proposed guidance has also been verified by considering first. order autopilot lag as well as assuming inaccurate information about target maneuvers. Multiple munitions engagement results are presented as well. Moreover, comparison studies with respect to an augmented proportional navigation guidance (which does not impose impact angle constraints) as well as an explicit linear optimal guidance (which imposes the same impact angle constraints in 3-D) lead to the conclusion that the proposed MPSP guidance is superior to both. A large number of randomized simulation studies show that it also has a larger capture region.

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The air we breathe is being polluted by activities such as vehicles; burning coal, oil, and other fossil fuels; and manufacturing chemicals. Air pollution can even come from smaller, everyday activities such as cooking, space heating, and degreasing and painting operations. These activities add gases and particles to the air we breathe. When these gases and particles accumulate in the air in high enough concentrations, they can harm us and our environment. The module on Air Pollution deals with the various sources of air pollution and the associated environmental and health impacts. It also discusses the appropriate measures to control/prevent the same.

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This paper deals with the characterisation of tar from two configurations of bioresidue thermochemical conversion reactors designed for producer gas based power generation systems. The pulverised fuel reactor is a cyclone system (R1) and the solid bioresidue reactor (denoted R2) is an open top twin air entry system both at 75-90 kg/h capacity (to generate electricity similar to 100 kVA). The reactor, R2, has undergone rigorous test in a major Indo-Swiss programme for the tar quantity at various conditions. The former is a recent technology development. Tars collected from these systems by a standard tar collection apparatus at the laboratory at Indian Institute of Science have been analysed at the Royal Institute of Technology (KTH), Sweden. The results of these analyses show that these thermochemical conversion reactors behave differently from the earlier reactors reported in literature in so far as tar generation is concerned. The extent of tar in hot gas is about 700-800 ppm for R1 and 70-100 ppm for R2. The amounts of the major compounds - naphthalene and phenol-are much lower that what is generally understood to happen in the gasifiers in Europe. It is suggested that the longer residence times at high temperatures allowed for in these reactors is responsible for this behavior. It is concluded the new generation reactor concepts extensively tried out at lower power levels hold promise for high power atmospheric gasification systems for woody as well as pulverisable bioresidues.