Fabrication and testing of a high resolution extensometer based on resonant MEMS strain sensors

A novel type of linear extensometer with exceptionally high resolution of 4 nm based on MEMS resonant strain sensors bonded on steel and operating in a vacuum package is presented. The tool is implemented by means of a steel thin bar that can be pre-stressed in tension within two fixing anchors. The extension of the bar is detected by using two vacuum-packaged resonant MEMS double- ended tuning fork (DETF) sensors bonded on the bar with epoxy glue, one of which is utilized for temperature compensation. Both sensors are driven by a closed loop self-oscillating transresistance amplifier feedback scheme implemented on a PCB (Printed Circuit Board). On the same board, a microcontroller-based frequency measurement circuit is also implemented, which is able to count the square wave fronts of the MEMS oscillator output with a resolution of 20 nsec. The system provides a frequency noise of 0.2 Hz corresponding to an extension resolution of 4 nm for the extensometer. Nearly perfect temperature compensation of the frequency output is achieved in the temperature range 20-35 C using the reference sensor. © 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.

Mergui Archipelago Joint Stakeholder Workshop report, Phuket, Thailand, 18-19 January, 2011

Data, information gaps and related monitoring requirements including trans-boundry issues; alternative livelihoods; critical habitat and develoment issues; policy, planning and institutional development.

On the use of combined compact scheme for numerical solution of the two-layer oceanic shallow water equations

Many types of oceanic physical phenomena have a wide range in both space and time. In general, simplified models, such as shallow water model, are used to describe these oceanic motions. The shallow water equations are widely applied in various oceanic and atmospheric extents. By using the two-layer shallow water equations, the stratification effects can be considered too. In this research, the sixth-order combined compact method is investigated and numerically implemented as a high-order method to solve the two-layer shallow water equations. The second-order centered, fourth-order compact and sixth-order super compact finite difference methods are also used to spatial differencing of the equations. The first part of the present work is devoted to accuracy assessment of the sixth-order super compact finite difference method (SCFDM) and the sixth-order combined compact finite difference method (CCFDM) for spatial differencing of the linearized two-layer shallow water equations on the Arakawa's A-E and Randall's Z numerical grids. Two general discrete dispersion relations on different numerical grids, for inertia-gravity and Rossby waves, are derived. These general relations can be used for evaluation of the performance of any desired numerical scheme. For both inertia-gravity and Rossby waves, minimum error generally occurs on Z grid using either the sixth-order SCFDM or CCFDM methods. For the Randall's Z grid, the sixth-order CCFDM exhibits a substantial improvement , for the frequency of the barotropic and baroclinic modes of the linear inertia-gravity waves of the two layer shallow water model, over the sixth-order SCFDM. For the Rossby waves, the sixth-order SCFDM shows improvement, for the barotropic and baroclinic modes, over the sixth-order CCFDM method except on Arakawa's C grid. In the second part of the present work, the sixth-order CCFDM method is used to solve the one-layer and two-layer shallow water equations in their nonlinear form. In one-layer model with periodic boundaries, the performance of the methods for mass conservation is compared. The results show high accuracy of the sixth-order CCFDM method to simulate a complex flow field. Furthermore, to evaluate the performance of the method in a non-periodic domain the sixth-order CCFDM is applied to spatial differencing of vorticity-divergence-mass representation of one-layer shallow water equations to solve a wind-driven current problem with no-slip boundary conditions. The results show good agreement with published works. Finally, the performance of different schemes for spatial differencing of two-layer shallow water equations on Z grid with periodic boundaries is investigated. Results illustrate the high accuracy of combined compact method.

Notes on the larval rearing scheme at SEAFDEC/AQD

For tiger shrimp, milkfish, and sea bass, larval rearing starts with the hatching of artificially spawned eggs. The eggs are stocked in larval rearing tanks, hatched, and metamorphosed larvae are fed and reared with good water management. Fry are harvested after about 30 days.

Electricity Storage Using a Thermal Storage Scheme

The increasing use of renewable energy technologies for electricity generation, many of which have an unpredictably intermittent nature, will inevitably lead to a greater demand for large-scale electricity storage schemes. For example, the expanding fraction of electricity produced by wind turbines will require either backup or storage capacity to cover extended periods of wind lull. This paper describes a recently proposed storage scheme, referred to here as Pumped Thermal Storage (PTS), and which is based on "sensible heat" storage in large thermal reservoirs. During the charging phase, the system effectively operates as a high temperature-ratio heat pump, extracting heat from a cold reservoir and delivering heat to a hot one. In the discharge phase the processes are reversed and it operates as a heat engine. The round- trip efficiency is limited only by process irreversibilities (as opposed to Second Law limitations on the coefficient of performance and the thermal efficiency of the heat pump and heat engine respectively). PTS is currently being developed in both France and England. In both cases, the schemes operate on the Joule-Brayton (gas turbine) cycle, using argon as the working fluid. However, the French scheme proposes the use of turbomachinery for compression and expansion, whereas for that being developed in England reciprocating devices are proposed. The current paper focuses on the impact of the various process irreversibilities on the thermodynamic round-trip efficiency of the scheme. Consideration is given to compression and expansion losses and pressure losses (in pipe-work, valves and thermal reservoirs); heat transfer related irreversibility in the thermal reservoirs is discussed but not included in the analysis. Results are presented demonstrating how the various loss parameters and operating conditions influence the overall performance.