Statistical energy analysis of a built-up structure excited through its stiffening members

A new method of analysing high frequency vibrations in stiffened structures requires the calculation of a "power absorbing impedance matrix" for each plate in the system. The present paper is concerned with formulating this matrix by using point collocation in conjunction with basis functions representing incoming cylindrical waves. Key numerical issues are highlighted by considering the special case of a membrane, rather than a plate, and conclusions are made regarding the utility of the method.

Theoretical performance of a coiled coil piezoelectric bimorph

The electromechanical coupling behaviour of a novel, highly coiled piezoelectric strip structure is developed in full, in order to expound its performance and efficiency. The strip is doubly coiled for compactness and, compared to a standard straight actuator of the same cross-section, it is shown that the actuator here offers better generative forces and energy conversion, and substantial actuated displacements, however, at the expense of a much lower stiffness. The device is therefore proposed for high-displacement, quasi-static applications. © 2006 Elsevier B.V. All rights reserved.

Simplifying mooring analysis for deepwater systems using truncation

Over recent years academia and industry have engaged with the challenge of model testing deepwater structures at conventional scales. One approach to the limited depth problem has been to truncate the lines. This concept will be introduced, highlighting the need to better understand line dynamic processes. The type of line truncation developed here models the upper sections of each line in detail, capturing wave action and all coupling effects with the vessel, terminating to an approximate analytical model that aims to simulate the remainder of the line. A rationale for this is that in deep water transverse elastic waves of a line are likely to decay before they are reflected at the seabed because of nonlinear hydrodynamic drag forces. The first part of this paper is centered on verification of this rationale. A simplified model of a mooring line that describes the transverse dynamics in wave frequency is used, adopting the equation of motion of an inextensible taut string. The line is submerged in still water, one end fixed at the bottom the other assumed to follow the vessel response, which can be harmonic or random. A dimensional analysis, supported by exact benchmark numerical solutions, has shown that it is possible to produce a universal curve for the decay of transverse vibrations along the line, which is suitable for any kind of line with any top motion. This has a significant engineering benefit, allowing for a rapid assessment of line dynamics - it can be useful in deciding whether a truncated line model is appropriate, and if so, at which point truncation might be applied. This is followed by developing a truncation mechanism, formulating an end approximation that can reproduce the correct impedance, had the line been continuous to full depth. It has been found that below a certain length criterion, which is also universal, the transverse vibrational characteristics for each line are inertia driven. As such the truncated model can assume a linear damper whose coefficient depends on the line properties and frequency of vibration. Copyright © 2011 by the International Society of Offshore and Polar Engineers (ISOPE).

Adaptive control of stiffness to stabilize hand position with large loads.

The goal of this work was to investigate stability in relation to the magnitude and direction of forces applied by the hand. The endpoint stiffness and joint stiffness of the arm were measured during a postural task in which subjects exerted up to 30% maximum voluntary force in each of four directions while controlling the position of the hand. All four coefficients of the joint stiffness matrix were found to vary linearly with both elbow and shoulder torque. This contrasts with the results of a previous study, which employed a force control task and concluded that the joint stiffness coefficients varied linearly with either shoulder or elbow torque but not both. Joint stiffness was transformed into endpoint stiffness to compare the effect on stability as endpoint force increased. When the joint stiffness coefficients were modeled as varying with the net torque at only one joint, as in the previous study, we found that hand position became unstable if endpoint force exceeded about 22 N in a specific direction. This did not occur when the joint stiffness coefficients were modeled as varying with the net torque at both joints, as in the present study. Rather, hand position became increasingly more stable as endpoint force increased for all directions of applied force. Our analysis suggests that co-contraction of biarticular muscles was primarily responsible for the increased stability. This clearly demonstrates how the central nervous system can selectively adapt the impedance of the arm in a specific direction to stabilize hand position when the force applied by the hand has a destabilizing effect in that direction.

Different mechanisms involved in adaptation to stable and unstable dynamics.

Recently, we demonstrated that humans can learn to make accurate movements in an unstable environment by controlling magnitude, shape, and orientation of the endpoint impedance. Although previous studies of human motor learning suggest that the brain acquires an inverse dynamics model of the novel environment, it is not known whether this control mechanism is operative in unstable environments. We compared learning of multijoint arm movements in a "velocity-dependent force field" (VF), which interacted with the arm in a stable manner, and learning in a "divergent force field" (DF), where the interaction was unstable. The characteristics of error evolution were markedly different in the 2 fields. The direction of trajectory error in the DF alternated to the left and right during the early stage of learning; that is, signed error was inconsistent from movement to movement and could not have guided learning of an inverse dynamics model. This contrasted sharply with trajectory error in the VF, which was initially biased and decayed in a manner that was consistent with rapid feedback error learning. EMG recorded before and after learning in the DF and VF are also consistent with different learning and control mechanisms for adapting to stable and unstable dynamics, that is, inverse dynamics model formation and impedance control. We also investigated adaptation to a rotated DF to examine the interplay between inverse dynamics model formation and impedance control. Our results suggest that an inverse dynamics model can function in parallel with an impedance controller to compensate for consistent perturbing force in unstable environments.

How is somatosensory information used to adapt to changes in the mechanical environment?

Recent studies examining adaptation to unexpected changes in the mechanical environment highlight the use of position error in the adaptation process. However, force information is also available. In this chapter, we examine adaptation processes in three separate studies where the mechanical environment was changed intermittently. We compare the expected consequences of using position error and force information in the changes to motor commands following a change in the mechanical environment. In general, our results support the use of position error over force information and are consistent with current computational models of motor learning. However, in situations where the change in the mechanical environment eliminates position error the central nervous system does not necessarily respond as would be predicted by these models. We suggest that it is necessary to take into account the statistics of prior experience to account for our observations. Another deficiency in these models is the absence of a mechanism for modulating limb mechanical impedance during adaptation. We propose a relatively simple computational model based on reflex responses to perturbations which is capable of accounting for iterative changes in temporal patterns of muscle co-activation.

Reflex contributions to the directional tuning of arm stiffness

It has been shown that during arm movement, humans selectively change the endpoint stiffness of their arm to compensate for the instability in an unstable environment. When the direction of the instability is rotated with respect to the direction of movement, it was found that humans modify the antisymmetric component of their endpoint stiffness. The antisymmetric component of stiffness arises due to reflex responses suggesting that the subjects may have tuned their reflex responses as part of the feedforward adaptive control. The goal of this study was to examine whether the CNS modulates the gain of the reflex response for selective tuning of endpoint impedance. Subjects performed reaching movements in three unstable force fields produced by a robotic manipulandum, each field differing only in the rotational component. After subjects had learned to compensate for the field, allowing them to make unperturbed movements to the target, the endpoint stiffness of the arm was estimated in the middle of the movements. At the same time electromyographic activity (EMG) of six arm muscles was recorded. Analysis of the EMG revealed differences across force fields in the reflex gain of these muscles consistent with stiffness changes. This study suggests that the CNS modulates the reflex gain as part of the adaptive feedforward command in which the endpoint impedance is selectively tuned to overcome environmental instability. © 2008 Springer-Verlag Berlin Heidelberg.

Learning the dynamics of the external world: Brain inspired learning for robotic applications

Humans have exceptional abilities to learn new skills, manipulate tools and objects, and interact with our environment. In order to be successful at these tasks, our brain has become exceptionally well adapted to learning to deal not only with the complex dynamics of our own limbs but also with novel dynamics in the external world. While learning of these dynamics includes learning the complex time-varying forces at the end of limbs through the updating of internal models, it must also include learning the appropriate mechanical impedance in order to stabilize both the limb and any objects contacted in the environment. This article reviews the field of human learning by examining recent experimental evidence about adaptation to novel unstable dynamics and explores how this knowledge about the brain and neuro-muscular system can expand the learning capabilities of robotics and prosthetics. © 2006.

Learning feedforward commands to muscles using time-shifted sensory feedback

In adapting to changing forces in the mechanical environment, humans change the force being applied by the limb by reciprocal changes in the activation of antagonistic muscles. However, they also cocontract these muscles when interaction with the environment is mechanically unstable to increase the mechanical impedance of the limb. We have postulated that appropriate patterns of muscle activation could be learned using a simple scheme in which the naturally occurring stretch reflex is used as a template to adjust feedforward commands to muscles. Feedforward commands are modified iteratively by shifting a scaled version of the reflex response forward in time and adding it to the previous feedforward command. We show that such an algorithm can account for the principal features of changes in muscle activation observed when human subjects adapt to instabilities in the mechanical environment. © 2006.

Fabrication of high-Q film bulk acoustic resonator (FBAR) filters withcarbon nanotube (CNT) electrodes

FBAR devices with carbon nanotube (CNT) electrodes have been developed withthe aim of taking advantage of the low density and high acoustic impedance ofthe CNTs compared to other known materials. The influence of the CNTs on thefrequency response of the FBAR devices was studied by comparing two identicalsets of devices, one set comprised FBARs fabricated with chromium/gold bilayerelectrodes, and the second set comprised FBARs fabricated with CNT electrodes.It was found that the CNTs had a significant effect on attenuating travellingwaves at the surface of the FBARs membranes due to their high elastic stiffness.Finite element analysis of the devices fabricated was carried out using COMSOLMultiphysics, and the numerical results confirmed the experimental resultsobtained. © 2010 IEEE.

Computational mechanisms of sensorimotor control.

In order to generate skilled and efficient actions, the motor system must find solutions to several problems inherent in sensorimotor control, including nonlinearity, nonstationarity, delays, redundancy, uncertainty, and noise. We review these problems and five computational mechanisms that the brain may use to limit their deleterious effects: optimal feedback control, impedance control, predictive control, Bayesian decision theory, and sensorimotor learning. Together, these computational mechanisms allow skilled and fluent sensorimotor behavior.

Eccentricity effects on acoustic radiation from a spherical source suspended within a thermoviscous fluid sphere.

Acoustic radiation from a spherical source undergoing angularly periodic axisymmetric harmonic surface vibrations while eccentrically suspended within a thermoviscous fluid sphere, which is immersed in a viscous thermally conducting unbounded fluid medium, is analyzed in an exact fashion. The formulation uses the appropriate wave-harmonic field expansions along with the translational addition theorem for spherical wave functions and the relevant boundary conditions to develop a closed-form solution in form of infinite series. The analytical results are illustrated with a numerical example in which the vibrating source is eccentrically positioned within a chemical fluid sphere submerged in water. The modal acoustic radiation impedance load on the source and the radiated far-field pressure are evaluated and discussed for representative values of the parameters characterizing the system. The proposed model can lead to a better understanding of dynamic response of an underwater acoustic lens. It is equally applicable in miniature transducer analysis and design with applications in medical ultrasonics.

ZnO-Based FBAR resonators with carbon nanotube electrodes

Film bulk acoustic resonator (FBAR) devices with carbon nanotube (CNT) electrodes directly grown on a ZnO film by thermal chemical vapor deposition have been fabricated. CNT electrodes possess a very low density and high acoustic impedance, which reduces the intrinsic mass loading effect resulting from the electrodes' weight and better confines the longitudinal acoustic standing waves inside the resonator, in turn providing a resonator with a higher quality factor. The influence of the CNTs on the frequency response of the FBAR devices was studied by comparing two identical sets of devices; one set comprised FBARs fabricated with chromium/ gold bilayer electrodes, and the second set comprised FBARs fabricated with CNT electrodes. It was found that the CNTs had a significant effect on attenuating traveling waves at the surface of the FBARs' membranes because of their high elastic stiffness. Three-dimensional finite element analysis of the devices fabricated was carried out, and the numerical simulations were consistent with the experimental results obtained. © 2011 IEEE.