950 resultados para tuning


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A series of 7 cerium double-decker complexes with various tetrapyrrole ligands including porphyrinates, phthalocyaninates, and 2,3-naphthalocyaninates have been prepared by previously described methodologies and characterized with elemental analysis and a range of spectroscopic methods. The molecular structures of two heteroleptic \[(na)phthalocyaninato](porphyrinato) complexes have also been determined by X-ray diffraction analysis which exhibit a slightly distorted square antiprismatic geometry with two domed ligands. Having a range of tetrapyrrole ligands with very different electronic properties, these compounds have been systematically investigated for the effects of ligands on the valence of the cerium center. On the basis of the spectroscopic (UV−vis, near-IR, IR, and Raman), electrochemical, and structural data of these compounds and compared with those of the other rare earth(III) counterparts reported earlier, it has been found that the cerium center adopts an intermediate valence in these complexes. It assumes a virtually trivalent state in cerium bis(tetra-tert-butylnaphthalocyaninate) as a result of the two electron rich naphthalocyaninato ligands, which facilitate the delocalization of electron from the ligands to the metal center. For the rest of the cerium double-deckers, the cerium center is predominantly tetravalent. The valences (3.59−3.68) have been quantified according to their LIII-edge X-ray absorption near-edge structure (XANES) profiles.

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Magneto-rheological (MR) fluid damper is a semi-active control device that has recently received more attention by the vibration control community. But inherent nonlinear hysteresis character of magneto-rheological fluid dampers is one of the challenging aspects for utilizing this device to achieve high system performance. So the development of accurate model is necessary to take the advantage their unique characteristics. Research by others [3] has shown that a system of nonlinear differential equations can successfully be used to describe the hysteresis behavior of the MR damper. The focus of this paper is to develop an alternative method for modeling a damper in the form of centre average fuzzy interference system, where back propagation learning rules are used to adjust the weight of network. The inputs for the model are used from the experimental data. The resulting fuzzy interference system is satisfactorily represents the behavior of the MR fluid damper with reduced computational requirements. Use of the neuro-fuzzy model increases the feasibility of real time simulation.

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Any incident on motorways potentially can be followed by secondary crashes. Rear-end crashes also could happen as a result of queue formation downstream of high speed platoons. To decrease the occurrence of secondary crashes and rear-end crashes, Variable Speed Limits (VSL) can be applied to protect queue formed downstream. This paper focuses on fine tuning the Queue Protection algorithm of VSL. Three performance indicators: activation time, deactivation time and number of false alarms are selected to optimise the Queue Protection algorithm. A calibrated microscopic traffic simulation model of Pacific Motorway in Brisbane is used for the optimisation. Performance of VSL during an incident and heavy congestion and the benefit of VSL will be presented in the paper.

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A magneto-rheological (MR) fluid damper is a semi-active control device that has recently begun to receive more attention in the vibration control community. However, the inherent nonlinear nature of the MR fluid damper makes it challenging to use this device to achieve high damping control system performance. Therefore the development of an accurate modeling method for a MR fluid damper is necessary to take advantage of its unique characteristics. Our goal was to develop an alternative method for modeling a MR fluid damper by using a self tuning fuzzy (STF) method based on neural technique. The behavior of the researched damper is directly estimated through a fuzzy mapping system. In order to improve the accuracy of the STF model, a back propagation and a gradient descent method are used to train online the fuzzy parameters to minimize the model error function. A series of simulations had been done to validate the effectiveness of the suggested modeling method when compared with the data measured from experiments on a test rig with a researched MR fluid damper. Finally, modeling results show that the proposed STF interference system trained online by using neural technique could describe well the behavior of the MR fluid damper without need of calculation time for generating the model parameters.

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Gold nanoparticles supported on CeO2 were found to be efficient photocatalysts for three selective reductions of organic compounds at ambient temperatures, under irradiation of visible light; their reduction ability can be tuned by manipulating the irradiation wavelength.

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This paper proposes the use of battery energy storage (BES) system for the grid-connected doubly fed induction generator (DFIG). The BES would help in storing/releasing additional power in case of higher/lower wind speed to maintain constant grid power. The DC link capacitor is replaced with the BES system in a DFIG-based wind turbine to achieve the above-mentioned goal. The control scheme is modified and the co-ordinated tuning of the associated controllers to enhance the damping of the oscillatory modes is presented using bacterial foraging technique. The results from eigenvalue analysis and the time domain simulation studies are presented to elucidate the effectiveness of the BES systems in maintaining the grid stability under normal operation.

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Power system stabilizer (PSS) is one of the most important controllers in modern power systems for damping low frequency oscillations. Many efforts have been dedicated to design the tuning methodologies and allocation techniques to obtain optimal damping behaviors of the system. Traditionally, it is tuned mostly for local damping performance, however, in order to obtain a globally optimal performance, the tuning of PSS needs to be done considering more variables. Furthermore, with the enhancement of system interconnection and the increase of system complexity, new tools are required to achieve global tuning and coordination of PSS to achieve optimal solution in a global meaning. Differential evolution (DE) is a recognized as a simple and powerful global optimum technique, which can gain fast convergence speed as well as high computational efficiency. However, as many other evolutionary algorithms (EA), the premature of population restricts optimization capacity of DE. In this paper, a modified DE is proposed and applied for optimal PSS tuning of 39-Bus New-England system. New operators are introduced to reduce the probability of getting premature. To investigate the impact of system conditions on PSS tuning, multiple operating points will be studied. Simulation result is compared with standard DE and particle swarm optimization (PSO).

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This paper proposes a self-tuning feedforward active noise control (ANC) system with online secondary path modeling. The step-size parameters of the controller and modeling filters have crucial rule on the system performance. In literature, these parameters are adjusted by trial-and-error. In other words, they are manually initialized before system starting, which require performing extensive experiments to ensure the convergence of the system. Hence there is no guarantee that the system could perform well under different situations. In the proposed method, the appropriate values for the step-sizes are obtained automatically. Computer simulation results indicate the effectiveness of the proposed method.

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The common goal of tissue engineering is to develop substitutes that can closely mimic the structure of extracellular matrix (ECM). However, similarly important is the intensive material properties which have often been overlooked, in particular, for soft tissues that are not to bear load assumingly. The mechanostructural properties determine not only the structural stability of biomaterials but also their physiological functionality by directing cellular activity and regulating cell fate decision. The aim here is to emphasize that cells could sense intensive material properties like elasticity and reside, proliferate, migrate and differentiate accordinglyno matter if the construct is from a natural source like cartilage, skin etc. or of synthetic one. Meanwhile, the very objective of this work is to provide a tunable scheme for manipulating the elasticity of collagen-based constructs to be used to demonstrate how to engineer cell behavior and regulate mechanotransduction. Articular cartilage was chosen as it represents one of the most complex hierarchical arrangements of collagen meshwork in both connective tissues and ECM-like biomaterials. Corona discharge treatment was used to produce constructs with varying density of crosslinked collagen and stiffness accordingly. The results demonstrated that elastic modulus increased up to 33% for samples treated up to one minute as crosslink density was found to increase with exposure time. According to the thermal analysis, longer exposure to corona increased crosslink density as the denaturation enthalpy increased. However the spectroscopy results suggested that despite the stabilization of the collagen structure the integrity of the triple helical structure remained intact. The in vitro superficial culture of heterologous chondrocytes also determined that the corona treatment can modulate migration with increased focal adhesion of cells due to enhanced stiffness, without cytotoxicity effects, and providing the basis for reinforcing three-dimensional collagen-based biomaterials in order to direct cell function and mediate mechanotransduction.

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Nitrogen-doped TiO2 nanofibres of anatase and TiO2(B) phases were synthesised by a reaction between titanate nanofibres of a layered structure and gaseous NH3 at 400–700 °C, following a different mechanism than that for the direct nitrogen doping from TiO2. The surface of the N-doped TiO2 nanofibres can be tuned by facial calcination in air to remove the surface-bonded N species, whereas the core remains N doped. N-Doped TiO2 nanofibres, only after calcination in air, became effective photocatalysts for the decomposition of sulforhodamine B under visible-light irradiation. The surface-oxidised surface layer was proven to be very effective for organic molecule adsorption, and the activation of oxygen molecules, whereas the remaining N-doped interior of the fibres strongly absorbed visible light, resulting in the generation of electrons and holes. The N-doped nanofibres were also used as supports of gold nanoparticle (Au NP) photocatalysts for visible-light-driven hydroamination of phenylacetylene with aniline. Phenylacetylene was activated on the N-doped surface of the nanofibres and aniline on the Au NPs. The Au NPs adsorbed on N-doped TiO2(B) nanofibres exhibited much better conversion (80 % of phenylacetylene) than when adsorbed on undoped fibres (46 %) at 40 °C and 95 % of the product is the desired imine. The surface N species can prevent the adsorption of O2 that is unfavourable for the hydroamination reaction, and thus, improve the photocatalytic activity. Removal of the surface N species resulted in a sharp decrease of the photocatalytic activity. These photocatalysts are feasible for practical applications, because they can be easily dispersed into solution and separated from a liquid by filtration, sedimentation or centrifugation due to their fibril morphology.