Bar-Halo Friction in Galaxies II: Metastability

It is well-established that strong bars rotating in dense halos generally slow down as they lose angular momentum to the halo through dynamical friction. Angular momentum exchanges between the bar and halo particles take place at resonances. While some particles gain and others lose, friction arises when there is an excess of gainers over losers. This imbalance results from the generally decreasing numbers of particles with increasing angular momentum, and friction can therefore be avoided if there is no gradient in the density of particles across the major resonances. Here we show that anomalously weak friction can occur for this reason if the pattern speed of the bar fluctuates upwards. After such an event, the density of resonant halo particles has a local inflexion created by the earlier exchanges, and bar slowdown can be delayed for a long period; we describe this as a metastable state. We show that this behavior in purely collisionless N-body simulations is far more likely to occur in methods with adaptive resolution. We also show that the phenomenon could arise in nature, since bar-driven gas inflow could easily raise the bar pattern speed enough to reach the metastable state. Finally, we demonstrate that mild external, or internal, perturbations quickly restore the usual frictional drag, and it is unlikely therefore that a strong bar in a galaxy having a dense halo could rotate for a long period without friction.Comment: 13 pages, 11 figures, to appear in Ap

Benchmarking Cerebellar Control

Cerebellar models have long been advocated as viable models for robot dynamics control. Building on an increasing insight in and knowledge of the biological cerebellum, many models have been greatly refined, of which some computational models have emerged with useful properties with respect to robot dynamics control. Looking at the application side, however, there is a totally different picture. Not only is there not one robot on the market which uses anything remotely connected with cerebellar control, but even in research labs most testbeds for cerebellar models are restricted to toy problems. Such applications hardly ever exceed the complexity of a 2 DoF simulated robot arm; a task which is hardly representative for the field of robotics, or relates to realistic applications. In order to bring the amalgamation of the two fields forwards, we advocate the use of a set of robotics benchmarks, on which existing and new computational cerebellar models can be comparatively tested. It is clear that the traditional approach to solve robotics dynamics loses ground with the advancing complexity of robotic structures; there is a desire for adaptive methods which can compete as traditional control methods do for traditional robots. In this paper we try to lay down the successes and problems in the fields of cerebellar modelling as well as robot dynamics control. By analyzing the common ground, a set of benchmarks is suggested which may serve as typical robot applications for cerebellar models

To develop an efficient variable speed compressor motor system

This research presents a proposed new method of improving the energy efficiency of a Variable Speed Drive (VSD) for induction motors. The principles of VSD are reviewed with emphasis on the efficiency and power losses associated with the operation of the variable speed compressor motor drive, particularly at low speed operation.The efficiency of induction motor when operated at rated speed and load torque is high. However at low load operation, application of the induction motor at rated flux will cause the iron losses to increase excessively, hence its efficiency will reduce dramatically. To improve this efficiency, it is essential to obtain the flux level that minimizes the total motor losses. This technique is known as an efficiency or energy optimization control method. In practice, typical of the compressor load does not require high dynamic response, therefore improvement of the efficiency optimization control that is proposed in this research is based on scalar control model.In this research, development of a new neural network controller for efficiency optimization control is proposed. The controller is designed to generate both voltage and frequency reference signals imultaneously. To achieve a robust controller from variation of motor parameters, a real-time or on-line learning algorithm based on a second order optimization Levenberg-Marquardt is employed. The simulation of the proposed controller for variable speed compressor is presented. The results obtained clearly show that the efficiency at low speed is significant increased. Besides that the speed of the motor can be maintained. Furthermore, the controller is also robust to the motor parameters variation. The simulation results are also verified by experiment

Androgynous Fasteners for Robotic Structural Assembly

We describe the design and analysis of an androgynous fastener for autonomous robotic assembly of high performance structures. The design of these fasteners aims to prioritize ease of assembly through simple actuation with large driver positioning tolerance requirements, while producing a reversible mechanical connection with high strength and stiffness per mass. This can be applied to high strength to weight ratio structural systems, such as discrete building block based systems that offer reconfigurability, scalability, and system lifecycle efficiency. Such periodic structures are suitable for navigation and manipulation by relatively small mobile robots. The integration of fasteners, which are lightweight and can be robotically installed, into a high performance robotically managed structural system is of interest to reduce launch energy requirements, enable higher mission adaptivity, and decrease system life-cycle costs

Imaging high-speed friction at the nanometer scale

Friction is a complicated phenomenon involving nonlinear dynamics at different length and time scales[1, 2]. The microscopic origin of friction is poorly understood, due in part to a lack of methods for measuring the force on a nanometer-scale asperity sliding at velocity of the order of cm/s.[3, 4] Despite enormous advance in experimental techniques[5], this combination of small length scale and high velocity remained illusive. Here we present a technique for rapidly measuring the frictional forces on a single asperity (an AFM tip) over a velocity range from zero to several cm/s. At each image pixel we obtain the velocity dependence of both conservative and dissipative forces, revealing the transition from stick-slip to a smooth sliding friction[1, 6]. We explain measurements on graphite using a modified Prandtl-Tomlinson model that takes into account the damped elastic deformation of the asperity. With its greatly improved force sensitivity and very small sliding amplitude, our method enables rapid and detailed surface mapping of the full velocity-dependence of frictional forces with less than 10~nm spatial resolution.Comment: 7 pages, 4 figure

Development of flow focusing device for the visualization of leukocyte rolling adhesion

La microfluídica es un área de la microtecnología basada en chips de PDMS que está siendo utilizada cada vez más en multitud de aplicaciones. Una de estas aplicaciones es la investigación biomédica. La microfluídica o “Lab on a Chip” se ha convertido en una manera de realizar experimentos biomédicos y diagnósticos de una manera barata, rápida y eficaz. Cuando se realizan estudios sobre la extravasación leucocitaria utilizando chips microfluídicos, podemos observar la inconsistencia en la trayectoria de rodadura de los leucocitos debido a un flujo laminar. En este trabajo de fin de grado presentamos un método para centrar la interfaz de células en el centro de canal microfluídico. Cuando las células circulan por los sistemas microfluídicos, las células tienden a circular de manera aleatoria por los canales. Por tanto, con el sistema propuesto en este trabajo, dichas células serán redirigidas a la porción central del canal con el fin de recrear el fenómeno de rodadura presente en nuestro sistema circulatorio y así obtener información más detallada. Los resultados de este trabajo muestran la utilidad y la versatilidad de este dispositivo para experimentos relacionados

Frontiers of finance: Evolution and efficient markets

In this review article we explore several recent advances in the quantitative modeling of financial markets. We begin with the Efficient Markets Hypothesis and describe how this controversial idea has stimulated a number of new directions of research, some focusing on more elaborate mathematical models that are captable of rationalizing the empirical facrts, others taking a completely different different tack in rejecting rationality altogether. One of the most promising directions is to view financial markets from a biological perspective and, specifically, with an evolutionary framework in which markets, instruments, institutions, and investors interact and evolve dynamically according to the "law" of economic selection. Under this view, financial agents compete and adapt, but they do not necessarily do so in an optimal fashion. Evolutionary and ecological models of financial markets is truly a new frontier whose exploration has just begun.Comment: 2 page