929 resultados para Adaptive swing doors trending


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The transfers of air driven by a revolving door connecting two rooms of initially different temperatures are investigated. The results of small-scale laboratory modelling show that a critical revolution rate exists for which transfers are maximal for a given combination of door geometry, revolution rate and temperature contrast. This critical revolution rate divides two possible transfer regimes for revolving doors. Potential implications of our findings to revolving door operation, to heat losses across the doorway and to ventilation driven by the door are discussed.

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This paper presents a heterogeneous reconfigurable system for real-time applications applying particle filters. The system consists of an FPGA and a multi-threaded CPU. We propose a method to adapt the number of particles dynamically and utilise the run-time reconfigurability of the FPGA for reduced power and energy consumption. An application is developed which involves simultaneous mobile robot localisation and people tracking. It shows that the proposed adaptive particle filter can reduce up to 99% of computation time. Using run-time reconfiguration, we achieve 34% reduction in idle power and save 26-34% of system energy. Our proposed system is up to 7.39 times faster and 3.65 times more energy efficient than the Intel Xeon X5650 CPU with 12 threads, and 1.3 times faster and 2.13 times more energy efficient than an NVIDIA Tesla C2070 GPU. © 2013 Springer-Verlag.

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This paper presents new methods for computing the step sizes of the subband-adaptive iterative shrinkage-thresholding algorithms proposed by Bayram & Selesnick and Vonesch & Unser. The method yields tighter wavelet-domain bounds of the system matrix, thus leading to improved convergence speeds. It is directly applicable to non-redundant wavelet bases, and we also adapt it for cases of redundant frames. It turns out that the simplest and most intuitive setting for the step sizes that ignores subband aliasing is often satisfactory in practice. We show that our methods can be used to advantage with reweighted least squares penalty functions as well as L1 penalties. We emphasize that the algorithms presented here are suitable for performing inverse filtering on very large datasets, including 3D data, since inversions are applied only to diagonal matrices and fast transforms are used to achieve all matrix-vector products.

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This paper addresses the speed and flux regulation of induction motors under the assumption that the motor parameters are poorly known. An adaptive passivity-based control is proposed that guarantees robust regulation as well as accurate estimation of the electrical parameters that govern the motor performance. This paper provides a local stability analysis of the adaptive scheme, which is illustrated by simulations and supported by a successful experimental validation on an industrial product. © 2009 IEEE.

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We present reaction free energy calculations using the adaptive buffered force mixing quantum mechanics/molecular mechanics (bf-QM/MM) method. The bf-QM/MM method combines nonadaptive electrostatic embedding QM/MM calculations with extended and reduced QM regions to calculate accurate forces on all atoms, which can be used in free energy calculation methods that require only the forces and not the energy. We calculate the free energy profiles of two reactions in aqueous solution: the nucleophilic substitution reaction of methyl chloride with a chloride anion and the deprotonation reaction of the tyrosine side chain. We validate the bf-QM/MM method against a full QM simulation, and show that it correctly reproduces both geometrical properties and free energy profiles of the QM model, while the electrostatic embedding QM/MM method using a static QM region comprising only the solute is unable to do so. The bf-QM/MM method is not explicitly dependent on the details of the QM and MM methods, so long as it is possible to compute QM forces in a small region and MM forces in the rest of the system, as in a conventional QM/MM calculation. It is simple, with only a few parameters needed to control the QM calculation sizes, and allows (but does not require) a varying and adapting QM region which is necessary for simulating solutions.

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Genetic algorithms (GAs) have been used to tackle non-linear multi-objective optimization (MOO) problems successfully, but their success is governed by key parameters which have been shown to be sensitive to the nature of the particular problem, incorporating concerns such as the numbers of objectives and variables, and the size and topology of the search space, making it hard to determine the best settings in advance. This work describes a real-encoded multi-objective optimizing GA (MOGA) that uses self-adaptive mutation and crossover, and which is applied to optimization of an airfoil, for minimization of drag and maximization of lift coefficients. The MOGA is integrated with a Free-Form Deformation tool to manage the section geometry, and XFoil which evaluates each airfoil in terms of its aerodynamic efficiency. The performance is compared with those of the heuristic MOO algorithms, the Multi-Objective Tabu Search (MOTS) and NSGA-II, showing that this GA achieves better convergence.

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In this Letter, we use a reconfigurable hologram to dynamically control the position of incidence of the pump beam onto a liquid-crystal dye-based laser. The results show that there is an increase in the stability of the laser output with time and the average power when compared with the output of the same laser when it is optically excited using a static pump beam. This technique also provides additional functionality, such as wavelength tuning and spatial shaping of the pump beam, both of which are demonstrated here. © 2013 Optical Society of America.

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A binary grating on a Spatial Light Modulator generates twin antiphase spots with adjustable positions across the core of a multimode fibre allowing adaptive excitation of antisymmetric mode-groups for improving modal dispersion or modal multiplexing. © 2011 AOS.

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The control of a class of combustion systems, suceptible to damage from self-excited combustion oscillations, is considered. An adaptive stable controller, called Self-Tuning Regulator (STR), has recently been developed, which meets the apparently contradictory challenge of relying as little as possible on a particular combustion model while providing some guarantee that the controller will cause no harm. The controller injects some fuel unsteadily into the burning region, thereby altering the heat release, in response to an input signal detecting the oscillation. This paper focuses on an extension of the STR design, when, due to stringent emission requirements and to the danger of flame extension, the amount of fuel used for control is limited in amplitude. A Lyapunov stability analysis is used to prove the stability of the modified STR when the saturation constraint is imposed. The practical implementation of the modified STR remains straightforward, and simulation results, based on the nonlinear premixed flame model developed by Dowling, show that in the presence of a saturation constraint, the self-excited oscillations are damped more rapidly with the modified STR than with the original STR. © 2001 by S. Evesque. Published by the American Institute of Aeronautics and Astronautics, Inc.