Active control of sound radiated by a submarine hull in axisymmetric vibration using inertial actuators

This paper investigates the use of inertial actuators to reduce the sound radiated by a submarine hull under excitation from the propeller. The axial forces from the propeller are tonal at the blade passing frequency. The hull is modeled as a fluid-loaded cylindrical shell with ring stiffeners and equally spaced bulkheads. The cylinder is closed at each end by circular plates and conical end caps. The forces from the propeller are transmitted to the hull by a rigid foundation connected to the propeller shaft. Inertial actuators are used as the structural control inputs. The actuators are arranged in circumferential arrays and attached to the internal end plates of the hull. Two active control techniques corresponding to active vibration control and discrete structural acoustic sensing are implemented to attenuate the structural and acoustic responses of the submarine. In the latter technique, error information on the radiated sound fields is provided by a discrete structural acoustic sensor. An acoustic transfer function is defined to estimate the far field sound pressure from a single point measurement on the hull. The inertial actuators are shown to provide control forces with a magnitude large enough to reduce the sound due to hull vibration. © 2012 American Society of Mechanical Engineers.

Lowering the excitation threshold of a random laser using the dynamic scattering states of an organosiloxane smectic A liquid crystal

Smectic A liquid crystals, based upon molecular structures that consist of combined siloxane and mesogenic moieties, exhibit strong multiple scattering of light with and without the presence of an electric field. This paper demonstrates that when one adds a laser dye to these compounds it is possible to observe random laser emission under optical excitation, and that the output can be varied depending upon the scattering state that is induced by the electric field. Results are presented to show that the excitation threshold of a dynamic scattering state, consisting of chaotic motion due to electro-hydrodynamic instabilities, exhibits lower lasing excitation thresholds than the scattering states that exist in the absence of an applied electric field. However, the lowest threshold is observed for a dynamic scattering state that does not have the largest scattering strength but which occurs when there is optimization of the combined light absorption and scattering properties. © 2012 American Institute of Physics.

Characterization of multimode fiber by selective mode excitation

Each mode of a 2 km 50 μ OM2 grade multimode fiber is precisely excited at multiple orientations using a binary phase spatial light modulator (SLM) to generate a detailed modal description of the fiber and minimize modal dispersion over 4.5 THz of optical bandwidth. © 2012 IEEE.

Robust F0 estimation based on a multi-microphone periodicity function for distant-talking speech

This work addresses the problem of deriving F0 from distanttalking speech signals acquired by a microphone network. The method here proposed exploits the redundancy across the channels by jointly processing the different signals. To this purpose, a multi-microphone periodicity function is derived from the magnitude spectrum of all the channels. This function allows to estimate F0 reliably, even under reverberant conditions, without the need of any post-processing or smoothing technique. Experiments, conducted on real data, showed that the proposed frequency-domain algorithm is more suitable than other time-domain based ones.

Mode division multiplexing over 2km of OM2 fibre using rotationally optimized mode excitation with fibre coupler demultiplexer

A Spatial Light Modulator and a non-specialized multimode coupler are used together to provide sufficient channel isolation and modal bandwidth for 2x12.5Gbps NRZ over 2km of standard graded-index multimode fibre without DSP. © 2012 IEEE.

Random function priors for exchangeable arrays with applications to graphs and relational data

A fundamental problem in the analysis of structured relational data like graphs, networks, databases, and matrices is to extract a summary of the common structure underlying relations between individual entities. Relational data are typically encoded in the form of arrays; invariance to the ordering of rows and columns corresponds to exchangeable arrays. Results in probability theory due to Aldous, Hoover and Kallenberg show that exchangeable arrays can be represented in terms of a random measurable function which constitutes the natural model parameter in a Bayesian model. We obtain a flexible yet simple Bayesian nonparametric model by placing a Gaussian process prior on the parameter function. Efficient inference utilises elliptical slice sampling combined with a random sparse approximation to the Gaussian process. We demonstrate applications of the model to network data and clarify its relation to models in the literature, several of which emerge as special cases.

Function propagation through nested systems

Concepts of function are central to design but statements about a device's functions can be interpreted in different ways. This raises problems for researchers trying to clarify the foundations of design theory and for those developing design support-tools that can represent and reason about function. By showing how functions relate systems to their sub-systems and super-systems, this article illustrates some limitations of existing function terminology and some problems with existing function statements. To address these issues, a system-relative function terminology is introduced. This is used to demonstrate that systems function not only with respect to their most local super-system, but also with respect to their more global super-systems. © 2012 Elsevier Ltd. All rights reserved.

Er3+ excitation and up-conversion processes in y 2-xErxSi2O7 films for planar optical amplifiers

Structural and optical properties of Y2-xErxSi 2O7 thin films have been studied. For higher Er content mechanisms related to Er-Er interactions increase optical efficiency. Moreover the influence of up-conversion has been estimated. ©2009 IEEE.

Dynamical structure function identifiability conditions enabling signal structure reconstruction

Networks of controlled dynamical systems exhibit a variety of interconnection patterns that could be interpreted as the structure of the system. One such interpretation of system structure is a system's signal structure, characterized as the open-loop causal dependencies among manifest variables and represented by its dynamical structure function. Although this notion of structure is among the weakest available, previous work has shown that if no a priori structural information is known about the system, not even the Boolean structure of the dynamical structure function is identifiable. Consequently, one method previously suggested for obtaining the necessary a priori structural information is to leverage knowledge about target specificity of the controlled inputs. This work extends these results to demonstrate precisely the a priori structural information that is both necessary and sufficient to reconstruct the network from input-output data. This extension is important because it significantly broadens the applicability of the identifiability conditions, enabling the design of network reconstruction experiments that were previously impossible due to practical constraints on the types of actuation mechanisms available to the engineer or scientist. The work is motivated by the proteomics problem of reconstructing the Per-Arnt-Sim Kinase pathway used in the metabolism of sugars. © 2012 IEEE.

On the applicability of the lognormal distribution in random dynamical systems

This paper is concerned with the probability density function of the energy of a random dynamical system subjected to harmonic excitation. It is shown that if the natural frequencies and mode shapes of the system conform to the Gaussian Orthogonal Ensemble, then under common types of loading the distribution of the energy of the response is approximately lognormal, providing the modal overlap factor is high (typically greater than two). In contrast, it is shown that the response of a system with Poisson natural frequencies is not approximately lognormal. Numerical simulations are conducted on a plate system to validate the theoretical findings and good agreement is obtained. Simulations are also conducted on a system made from two plates connected with rotational springs to demonstrate that the theoretical findings can be extended to a built-up system. The work provides a theoretical justification of the commonly used empirical practice of assuming that the energy response of a random system is lognormal.

Blocking central opiate function modulates hedonic impact and anterior cingulate response to rewards and losses.

Reward processing is linked to specific neuromodulatory systems with a dopaminergic contribution to reward learning and motivational drive being well established. Neuromodulatory influences on hedonic responses to actual receipt of reward, or punishment, referred to as experienced utility are less well characterized, although a link to the endogenous opioid system is suggested. Here, in a combined functional magnetic resonance imaging-psychopharmacological investigation, we used naloxone to block central opioid function while subjects performed a gambling task associated with rewards and losses of different magnitudes, in which the mean expected value was always zero. A graded influence of naloxone on reward outcome was evident in an attenuation of pleasure ratings for larger reward outcomes, an effect mirrored in attenuation of brain activity to increasing reward magnitude in rostral anterior cingulate cortex. A more striking effect was seen for losses such that under naloxone all levels of negative outcome were rated as more unpleasant. This hedonic effect was associated with enhanced activity in anterior insula and caudal anterior cingulate cortex, areas implicated in aversive processing. Our data indicate that a central opioid system contributes to both reward and loss processing in humans and directly modulates the hedonic experience of outcomes.

When will a flame describing function approach to thermoacoustics work well?

In any thermoacoustic analysis, it is important not only to predict linear frequencies and growth rates, but also the amplitude and frequencies of any limit cycles. The Flame Describing Function (FDF) approach is a quasi-linear analysis which allows the prediction of both the linear and nonlinear behaviour of a thermoacoustic system. This means that one can predict linear growth rates and frequencies, and also the amplitudes and frequencies of any limit cycles. The FDF achieves this by assuming that the acoustics are linear and that the flame, which is the only nonlinear element in the thermoacoustic system, can be adequately described by considering only its response at the frequency at which it is forced. Therefore any harmonics generated by the flame's nonlinear response are not considered. This implies that these nonlinear harmonics are small or that they are sufficiently filtered out by the linear dynamics of the system (the low-pass filter assumption). In this paper, a flame model with a simple saturation nonlinearity is coupled to simple duct acoustics, and the success of the FDF in predicting limit cycles is studied over a range of flame positions and acoustic damping parameters. Although these two parameters affect only the linear acoustics and not the nonlinear flame dynamics, they determine the validity of the low-pass filter assumption made in applying the flame describing function approach. Their importance is highlighted by studying the level of success of an FDF-based analysis as they are varied. This is achieved by comparing the FDF's prediction of limit-cycle amplitudes to the amplitudes seen in time domain simulations.

Shock dynamics of random structures.

Predicting the response of a structure following an impact is of interest in situations where parts of a complex assembly may come into contact. Standard approaches are based on the knowledge of the impulse response function, requiring the knowledge of the modes and the natural frequencies of the structure. In real engineering structures the statistics of higher natural frequencies follows those of the Gaussian Orthogonal Ensemble, this allows the application of random point process theory to get a mean impulse response function by the knowledge of the modal density of the structure. An ensemble averaged time history for both the response and the impact force can be predicted. Once the impact characteristics are known in the time domain, a simple Fourier Transform allows the frequency range of the impact excitation to be calculated. Experimental and numerical results for beams, plates, and cylinders are presented to confirm the validity of the method.