A single-rate context-dependent learning process underlies rapid adaptation to familiar object dynamics.

Motor learning has been extensively studied using dynamic (force-field) perturbations. These induce movement errors that result in adaptive changes to the motor commands. Several state-space models have been developed to explain how trial-by-trial errors drive the progressive adaptation observed in such studies. These models have been applied to adaptation involving novel dynamics, which typically occurs over tens to hundreds of trials, and which appears to be mediated by a dual-rate adaptation process. In contrast, when manipulating objects with familiar dynamics, subjects adapt rapidly within a few trials. Here, we apply state-space models to familiar dynamics, asking whether adaptation is mediated by a single-rate or dual-rate process. Previously, we reported a task in which subjects rotate an object with known dynamics. By presenting the object at different visual orientations, adaptation was shown to be context-specific, with limited generalization to novel orientations. Here we show that a multiple-context state-space model, with a generalization function tuned to visual object orientation, can reproduce the time-course of adaptation and de-adaptation as well as the observed context-dependent behavior. In contrast to the dual-rate process associated with novel dynamics, we show that a single-rate process mediates adaptation to familiar object dynamics. The model predicts that during exposure to the object across multiple orientations, there will be a degree of independence for adaptation and de-adaptation within each context, and that the states associated with all contexts will slowly de-adapt during exposure in one particular context. We confirm these predictions in two new experiments. Results of the current study thus highlight similarities and differences in the processes engaged during exposure to novel versus familiar dynamics. In both cases, adaptation is mediated by multiple context-specific representations. In the case of familiar object dynamics, however, the representations can be engaged based on visual context, and are updated by a single-rate process.

Application of the fixed point method for solution in time stepping finite element analysis using the inverse vector Jiles-Atherton model

An implementation of the inverse vector Jiles-Atherton model for the solution of non-linear hysteretic finite element problems is presented. The implementation applies the fixed point method with differential reluctivity values obtained from the Jiles-Atherton model. Differential reluctivities are usually computed using numerical differentiation, which is ill-posed and amplifies small perturbations causing large sudden increases or decreases of differential reluctivity values, which may cause numerical problems. A rule based algorithm for conditioning differential reluctivity values is presented. Unwanted perturbations on the computed differential reluctivity values are eliminated or reduced with the aim to guarantee convergence. Details of the algorithm are presented together with an evaluation of the algorithm by a numerical example. The algorithm is shown to guarantee convergence, although the rate of convergence depends on the choice of algorithm parameters. © 2011 IEEE.

Short- and long-term changes in joint co-contraction associated with motor learning as revealed from surface EMG.

In the field of motor control, two hypotheses have been controversial: whether the brain acquires internal models that generate accurate motor commands, or whether the brain avoids this by using the viscoelasticity of musculoskeletal system. Recent observations on relatively low stiffness during trained movements support the existence of internal models. However, no study has revealed the decrease in viscoelasticity associated with learning that would imply improvement of internal models as well as synergy between the two hypothetical mechanisms. Previously observed decreases in electromyogram (EMG) might have other explanations, such as trajectory modifications that reduce joint torques. To circumvent such complications, we required strict trajectory control and examined only successful trials having identical trajectory and torque profiles. Subjects were asked to perform a hand movement in unison with a target moving along a specified and unusual trajectory, with shoulder and elbow in the horizontal plane at the shoulder level. To evaluate joint viscoelasticity during the learning of this movement, we proposed an index of muscle co-contraction around the joint (IMCJ). The IMCJ was defined as the summation of the absolute values of antagonistic muscle torques around the joint and computed from the linear relation between surface EMG and joint torque. The IMCJ during isometric contraction, as well as during movements, was confirmed to correlate well with joint stiffness estimated using the conventional method, i.e., applying mechanical perturbations. Accordingly, the IMCJ during the learning of the movement was computed for each joint of each trial using estimated EMG-torque relationship. At the same time, the performance error for each trial was specified as the root mean square of the distance between the target and hand at each time step over the entire trajectory. The time-series data of IMCJ and performance error were decomposed into long-term components that showed decreases in IMCJ in accordance with learning with little change in the trajectory and short-term interactions between the IMCJ and performance error. A cross-correlation analysis and impulse responses both suggested that higher IMCJs follow poor performances, and lower IMCJs follow good performances within a few successive trials. Our results support the hypothesis that viscoelasticity contributes more when internal models are inaccurate, while internal models contribute more after the completion of learning. It is demonstrated that the CNS regulates viscoelasticity on a short- and long-term basis depending on performance error and finally acquires smooth and accurate movements while maintaining stability during the entire learning process.

Adaptation to stable and unstable dynamics achieved by combined impedance control and inverse dynamics model.

This study compared adaptation in novel force fields where trajectories were initially either stable or unstable to elucidate the processes of learning novel skills and adapting to new environments. Subjects learned to move in a null force field (NF), which was unexpectedly changed either to a velocity-dependent force field (VF), which resulted in perturbed but stable hand trajectories, or a position-dependent divergent force field (DF), which resulted in unstable trajectories. With practice, subjects learned to compensate for the perturbations produced by both force fields. Adaptation was characterized by an initial increase in the activation of all muscles followed by a gradual reduction. The time course of the increase in activation was correlated with a reduction in hand-path error for the DF but not for the VF. Adaptation to the VF could have been achieved solely by formation of an inverse dynamics model and adaptation to the DF solely by impedance control. However, indices of learning, such as hand-path error, joint torque, and electromyographic activation and deactivation suggest that the CNS combined these processes during adaptation to both force fields. Our results suggest that during the early phase of learning there is an increase in endpoint stiffness that serves to reduce hand-path error and provides additional stability, regardless of whether the dynamics are stable or unstable. We suggest that the motor control system utilizes an inverse dynamics model to learn the mean dynamics and an impedance controller to assist in the formation of the inverse dynamics model and to generate needed stability.

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.

Investigation of self excited and acoustically forced combustion instabilities with laser diagnostics

Combustion oscillations in gas turbines can result in serious damage. One method used to predict such oscillations is to analyze the combustor acoustics using a simple linear model. Such a model requires a flame transfer function to describe the response of the heat release to flow perturbations inside the combustor. This paper reports on the application of Planar Laser Induced Fluorescence (PLIF) of OH radicals to analyze the response of a lean premixed flame to oncoming flow perturbations. Both self-excited oscillations and low amplitude forced oscillations at various frequencies are investigated in an atmospheric pressure model combustor rig. In order to visualize fluctuations of local fuel distribution, acetone-PLIF was also applied in non-reacting and acoustically forced flows at oscillation frequencies of 200 Hz and 510 Hz, respectively. OH-PLIF images were acquired over a range of operating parameters. The results presented in this paper originate from data sets acquired at fixed phase angles during the oscillation cycle. Comparative experiments in self excited and forced acoustic oscillations show that the flame and the combustion intensity develop similarly throughout the pressure cycle in both cases. Although the peak fluorescence intensities differ between self excited and the forced instabilities, there is a clear correspondence in the observed frequency and phase information from the two cases. This result encourages a comparison of the OH-PLIF and the acetone-PLIF results. Quantitative measurements of the equivalence ratio in specific areas of the measurement plane offer insight on the complex phenomena coupling acoustic perturbations, i.e. flow velocity fluctuations, to fluctuations in fuel distribution and combustion intensity, ultimately resulting in self excited combustion oscillations.

Task-dependent coordination of rapid bimanual motor responses.

Optimal feedback control postulates that feedback responses depend on the task relevance of any perturbations. We test this prediction in a bimanual task, conceptually similar to balancing a laden tray, in which each hand could be perturbed up or down. Single-limb mechanical perturbations produced long-latency reflex responses ("rapid motor responses") in the contralateral limb of appropriate direction and magnitude to maintain the tray horizontal. During bimanual perturbations, rapid motor responses modulated appropriately depending on the extent to which perturbations affected tray orientation. Specifically, despite receiving the same mechanical perturbation causing muscle stretch, the strongest responses were produced when the contralateral arm was perturbed in the opposite direction (large tray tilt) rather than in the same direction or not perturbed at all. Rapid responses from shortening extensors depended on a nonlinear summation of the sensory information from the arms, with the response to a bimanual same-direction perturbation (orientation maintained) being less than the sum of the component unimanual perturbations (task relevant). We conclude that task-dependent tuning of reflexes can be modulated online within a single trial based on a complex interaction across the arms.

Measurements of triggering and transient growth in a model lean-premixed gas turbine combustor

Instability triggering and transient growth of thermoacoustic oscillations were experimentally investigated in combination with linear/nonlinear flame transfer function (FTF) methodology in a model lean-premixed gas turbine combustor operated with CH 4 and air at atmospheric pressure. A fully premixed flame with 10kW thermal power and an equivalence ratio of 0.60 was chosen for detailed characterization of the nonlinear transient behaviors. Flame transfer functions were experimentally determined by simultaneous measurements of inlet velocity fluctuations and heat release rate oscillations using a constant temperature anemometer and OH */CH * chemiluminescence emissions, respectively. The phase-resolved variation of the local flame structure at a limit cycle was measured by planar laser-induced fluorescence of OH. Simultaneous measurements of inlet velocity, OH */CH * emission, and acoustic pressure were performed to investigate the temporal evolution of the system from a stable to a limit cycle operation. This measurement allows us to describe an unsteady instability triggering event in terms of several distinct stages: (i) initiation of a small perturbation, (ii) exponential amplification, (iii) saturation, (iv) nonlinear evolution of the perturbations towards a new unstable periodic state, (v) quasi-steady low-amplitude periodic oscillation, and (vi) fully-developed high-amplitude limit cycle oscillation. Phase-plane portraits of instantaneous inlet velocity and heat release rate clearly show the presence of two different attractors. Depending on its initial position in phase space at infinitesimally small amplitude, the system evolves towards either a high-amplitude oscillatory state or a low-amplitude oscillatory state. This transient phenomenon was analyzed using frequency- and amplitude-dependent damping mechanisms, and compared to subcritical and supercritical bifurcation theories. The results presented in this paper experimentally demonstrate the hypothesis proposed by Preetham et al. based on analytical and computational solutions of the nonlinear G-equation [J. Propul. Power 24 (2008) 1390-1402]. Good quantitative agreement was obtained between measurements and predictions in terms of the conditions for the onset of triggering and the amplitude of triggered combustion instabilities. © 2011 The Combustion Institute.

In vivo dynamics of the internal fibrous structure in smooth adhesive pads of insects.

Many insects with smooth adhesive pads can rapidly enlarge their contact area by centripetal pulls on the legs, allowing them to cope with sudden mechanical perturbations such as gusts of wind or raindrops. The short time scale of this reaction excludes any neuromuscular control; it is thus more likely to be caused by mechanical properties of the pad's specialized cuticle. This soft cuticle contains numerous branched fibrils oriented almost perpendicularly to the surface. Assuming a fixed volume of the water-filled cuticle, we hypothesized that pulls could decrease the fibril angle, thereby helping the contact area to expand laterally and longitudinally. Three-dimensional fluorescence microscopy on the cuticle of smooth stick insect pads confirmed that pulls significantly reduced the fibril angle. However, the fibril angle variation appeared insufficient to explain the observed increase in contact area. Direct strain measurements in the contact zone demonstrated that pulls not only expand the cuticle laterally, but also add new contact area at the pad's outer edge.

Low-order modelling of ducted flames with temporally varying equivalence ratio in realistic geometries

The interaction between unsteady heat release and acoustic pressure oscillations in gas turbines results in self-excited combustion oscillations which can potentially be strong enough to cause significant structural damage to the combustor. Correctly predicting the interaction of these processes, and anticipating the onset of these oscillations can be difficult. In recent years much research effort has focused on the response of premixed flames to velocity and equivalence ratio perturbations. In this paper, we develop a flame model based on the socalled G-Equation, which captures the kinematic evolution of the flame surfaces, under the assumptions of axisymmetry, and ignoring vorticity and compressibility. This builds on previous work by Dowling [1], Schuller et al. [2], Cho & Lieuwen [3], among many others, and extends the model to a realistic geometry, with two intersecting flame surfaces within a non-uniform velocity field. The inputs to the model are the free-stream velocity perturbations, and the associated equivalence ratio perturbations. The model also proposes a time-delay calculation wherein the time delay for the fuel convection varies both spatially and temporally. The flame response from this model was compared with experiments conducted by Balachandran [4, 5], and found to show promising agreement with experimental forced case. To address the primary industrial interest of predicting self-excited limit cycles, the model has then been linked with an acoustic network model to simulate the closed-loop interaction between the combustion and acoustic processes. This has been done both linearly and nonlinearly. The nonlinear analysis is achieved by applying a describing function analysis in the frequency domain to predict the limit cycle, and also through a time domain simulation. In the latter case, the acoustic field is assumed to remain linear, with the nonlinearity in the response of the combustion to flow and equivalence ratio perturbations. A transfer function from unsteady heat release to unsteady pressure is obtained from a linear acoustic network model, and the corresponding Green function is used to provide the input to the flame model as it evolves in the time domain. The predicted unstable frequency and limit cycle are in good agreement with experiment, demonstrating the potential of this approach to predict instabilities, and as a test bench for developing control strategies. Copyright © 2011 by ASME.

Flux pumping, fluctuations and climbing fields

This paper describes the behaviour of bulk superconductors when subjected to a varying magnetic field. A magnetic model is described together with experimental results which explain and describe the behaviour of superconducting bulks when subjected to varying magnetic fields. We demonstrate how the behaviour is dependent on the magnitude and period of the perturbations in the fields. The model which we use has been implemented using the Comsol™pde solver. It is a fully integrated model which uses a variable heat source to regulate the magnetic circuit and thereby to achieve flux pumping. Comsol™is used for post solution visualization and the model is presented alongside experimental results which support and confirm the conclusions from the model. © 2012 IOP Publishing Ltd.

A finite element model of magnetization of superconducting bulks using a solid-state flux pump

Superconductors have a bright future; they are able to carry very high current densities, switch rapidly in electronic circuits, detect extremely small perturbations in magnetic fields, and sustain very high magnetic fields. Of most interest to large-scale electrical engineering applications are the ability to carry large currents and to provide large magnetic fields. There are many projects that use the first property, and these have concentrated on power generation, transmission, and utilization; however, there are relatively few, which are currently exploiting the ability to sustain high magnetic fields. The main reason for this is that high field wound magnets can and have been made from both BSCCO and YBCO, but currently, their cost is much higher than the alternative provided by low-Tc materials such as Nb3Sn and NbTi. An alternative form of the material is the bulk form, which can be magnetized to high fields. This paper explains the mechanism, which allows superconductors to be magnetized without the need for high field magnets to perform magnetization. A finite-element model is presented, which is based on the E-J current law. Results from this model show how magnetization of the superconductor builds up cycle upon cycle when a traveling magnetic wave is induced above the superconductor. © 2011 IEEE.

Raman spectroscopy as a versatile tool for studying the properties of graphene.

Raman spectroscopy is an integral part of graphene research. It is used to determine the number and orientation of layers, the quality and types of edge, and the effects of perturbations, such as electric and magnetic fields, strain, doping, disorder and functional groups. This, in turn, provides insight into all sp(2)-bonded carbon allotropes, because graphene is their fundamental building block. Here we review the state of the art, future directions and open questions in Raman spectroscopy of graphene. We describe essential physical processes whose importance has only recently been recognized, such as the various types of resonance at play, and the role of quantum interference. We update all basic concepts and notations, and propose a terminology that is able to describe any result in literature. We finally highlight the potential of Raman spectroscopy for layered materials other than graphene.

Nonlinear phenomena in thermoacoustics: A comparison between single-mode and multi-mode methods

Nonlinear analysis of thermoacoustic instability is essential for prediction of frequencies and amplitudes of limit cycles. In frequency domain analyses, a quasi-linear transfer function between acoustic velocity and heat release rate perturbations, called the flame describing function (FDF), is obtained from a flame model or experiments. The FDF is a function of the frequency and amplitude of velocity perturbations but only contains the heat release response at the forcing frequency. While the gain and phase of the FDF provide insight into the nonlinear dynamics of the system, the accuracy of its predictions remains to be verified for different types of nonlinearity. In time domain analyses, the governing equations of the fully coupled problem are solved to find the time evolution of the system. One method is to discretize the governing equations using a suitable basis, such as the natural acoustic modes of the system. The number of modes used in the discretization alters the accuracy of the solution. In our previous work we have shown that predictions using the FDF are almost exactly the same as those obtained from the time-domain using only one mode for the discretization. We call this the single-mode method. In this paper we compare results from the single-mode and multi-mode methods, applied to a thermoacoustic system of a premixed flame in a tube. For some cases, the results differ greatly in both amplitude as well as frequency content. This study shows that the contribution from higher and subharmonics to the nonlinear dynamics can be significant and must be considered for an accurate and comprehensive analysis of thermoacoustic systems. Hence multi-mode simulations are necessary, and the single-mode method or the FDF may be insufficient to capture some of the complex nonlinear behaviour in fhermoacoustics.

Experimental investigation of dynamic response of acoustically forced turbulent premixed CH4/CO2/air flames

Increasing demand for energy and continuing increase in environmental as well as financial cost of use of fossil fuels drive the need for utilization of fuels from sustainable sources for power generation. Development of fuel-flexible combustion systems is vital in enabling the use of sustainable fuels. It is also important that these sustainable combustion systems meet the strict governmental emission legislations. Biogas is considered as one of the viable sustainable fuels that can be used to power modern gas turbines: However, the change in chemical, thermal and transport properties as well as change in Wobbe index due to the variation of the fuel constituents can have a significant effect on the performance of the combustor. It is known that the fuel properties have strong influence on the dynamic flame response; however there is a lack of detailed information regarding the effect of fuel compositions on the sensitivity of the flames subjected to flow perturbations. In this study, we describe an experimental effort investigating the response of premixed biogas-air turbulent flames with varying proportions of CH4 and CO2 to velocity perturbations. The flame was stabilized using a centrally placed conical bluff body. Acoustic perturbations were imposed to the flow using loud speakers. The flame dynamics and the local heat release rate of these acoustically excited biogas flames were studied using simultaneous measurements of OH and H2CO planar laser induced fluorescence. OH* chemiluminescence along with acoustic pressure measurements were also recorded to estimate the total flame heat release modulation and the velocity fluctuations. The measurements were carried out by keeping the theoretical laminar flame speed constant while varying the bulk velocity and the fuel composition. The results indicate that the flame sensitivity to perturbations increased with increased dilution of CH4 by CO2 at low amplitude forcing, while at high amplitude forcing conditions the magnitude of the flame response was independent of dilution.