7 resultados para Relative Phase

em Cambridge University Engineering Department Publications Database


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Even though synchronization in autonomous systems has been observed for over three centuries, reports of systematic experimental studies on synchronized oscillators are limited. Here, we report on observations of internal synchronization in coupled silicon micromechanical oscillators associated with a reduction in the relative phase random walk that is modulated by the magnitude of the reactive coupling force between the oscillators. Additionally, for the first time, a significant improvement in the frequency stability of synchronized micromechanical oscillators is reported. The concept presented here is scalable and could be suitably engineered to establish the basis for a new class of highly precise miniaturized clocks and frequency references. © 2013 American Physical Society.

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Measurement of acceleration in dynamic tests is carried out routinely, and in most cases, piezoelectric accelerometers are used at present. However, a new class of instruments based on MEMS technology have become available and are gaining use in many applications due to their small size, low mass and low-cost. This paper describes a centrifuge lateral spreading experiment in which MEMS and piezoelectric accelerometers were placed at similar depths. Good agreement was obtained when the instruments were located in dense sands, but significant differences were observed in loose, liquefiable soils. It was found that the performance of the piezoelectric accelerometer is poor at low frequency, and that the relative phase difference between the piezoelectric and MEMS accelerometer varies significantly at low frequency. © 2010 Taylor & Francis Group, London.

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We describe an RFID tag reading system for reading one or more RFID Tags, the system comprising an RF transmitter and an RF receiver, a plurality of transmit/receive antennas coupled to said RF transmitter and to said RF receiver, to provide spatial transmit/receive signal diversity, and a tag signal decoder coupled to at least said RF receiver, wherein said system is configured to combine received RF signals from said antennas to provide a combined received RF signal, wherein said RF receiver has said combined received RF signal as an input; wherein said antennas are spaced apart from one another sufficiently for one said antenna not to be within the near field of another said antenna, wherein said system is configured to perform a tag inventory cycle comprising a plurality of tag read rounds to read said tags, a said tag read round comprising transmission of one or more RF tag interrogation signals simultaneously from said plurality of antennas and receiving a signal from one or more of said tags, a said tag read round having a set of time slots during which a said tag is able to transmit tag data including a tag ID for reception by said antenna, and wherein said system is configured to perform, during a said tag inventory cycle, one or both of: a change in a frequency of said tag interrogation signals transmitted simultaneously from said plurality of antennas, and a change in a relative phase of a said RF tag interrogation signals transmitted from one of said antennas with respect to another of said antennas.

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While it is well known that it is possible to determine the effective flexoelectric coefficient of nematic liquid crystals using hybrid cells [1], this technique can be difficult due to the necessity of using a D.C. field. We have used a second method[2], requiring an A.C. field, to determine this parameter and here we compare the two techniques. The A.C. method employs the linear flexoelectrically induced linear electro-optic switching mechanism observed in chiral nematics. In order to use this second technique a chiral nematic phase is induced in an achiral nematic by the addition of a small amount of chiral additive (∼3% concentration w/w) to give helix pitch lengths of typically 0.5-1.0 μm. We note that the two methods can be used interchangeably, since they produce similar results, and we conclude with a discussion of their relative merits.

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The measurement of cantilever parameters is an essential part of performing a calibrated measurement with an atomic force microscope (AFM). The thermal motion method is a widely used technique for calibrating the spring constant of an AFM cantilever, which can be applied to non-rectangular cantilevers. Given the trend towards high frequency scanning, calibration of non-rectangular cantilevers is of increasing importance. This paper presents two results relevant to cantilever calibration via the thermal motion method. We demonstrate the possibility of using the AFM's phase signal to acquire the thermal motion. This avoids the challenges associated with connecting the raw photodiode signal to a separate spectrum analyser. We also describe how numerical calculations may be used to calculate the parameters needed in a thermal motion calibration of a non-rectangular cantilever. Only accurate knowledge of the relative size of the in-plane dimensions of the cantilever is needed in this computation. We use this pair of results in the calibration of a variety of rectangular and non-rectangular cantilevers. We observe an average difference between the Sader and thermal motion values of cantilever stiffness of 10%.

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Computational fluid dynamics (CFD) simulations are becoming increasingly widespread with the advent of more powerful computers and more sophisticated software. The aim of these developments is to facilitate more accurate reactor design and optimization methods compared to traditional lumped-parameter models. However, in order for CFD to be a trusted method, it must be validated using experimental data acquired at sufficiently high spatial resolution. This article validates an in-house CFD code by comparison with flow-field data obtained using magnetic resonance imaging (MRI) for a packed bed with a particle-to-column diameter ratio of 2. Flows characterized by inlet Reynolds numbers, based on particle diameter, of 27, 55, 111, and 216 are considered. The code used employs preconditioning to directly solve for pressure in low-velocity flow regimes. Excellent agreement was found between the MRI and CFD data with relative error between the experimentally determined and numerically predicted flow-fields being in the range of 3-9%. © 2012 American Institute of Chemical Engineers (AIChE).

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We show how machine learning techniques based on Bayesian inference can be used to reach new levels of realism in the computer simulation of molecular materials, focusing here on water. We train our machine-learning algorithm using accurate, correlated quantum chemistry, and predict energies and forces in molecular aggregates ranging from clusters to solid and liquid phases. The widely used electronic-structure methods based on density-functional theory (DFT) give poor accuracy for molecular materials like water, and we show how our techniques can be used to generate systematically improvable corrections to DFT. The resulting corrected DFT scheme gives remarkably accurate predictions for the relative energies of small water clusters and of different ice structures, and greatly improves the description of the structure and dynamics of liquid water.