On the transition from finite-volume negatively buoyant releases to continuous fountains

An experimental investigation to identify the source conditions that distinguish finite-volume negatively buoyant fluid projectile behaviour from fountain behaviour in quiescent environments of uniform density is described. Finite-volume releases are governed by their source Froude number Fr D and the aspect ratio L/D of the release, where L denotes the length of the column of fluid dispensed vertically from the nozzle of diameter D. We establish the influence of L/D on the peak rise heights of a release formed by dispensing saline solution into fresh water for 0

Model reductions for inference: generality of pairwise, binary, and planar factor graphs.

We offer a solution to the problem of efficiently translating algorithms between different types of discrete statistical model. We investigate the expressive power of three classes of model-those with binary variables, with pairwise factors, and with planar topology-as well as their four intersections. We formalize a notion of "simple reduction" for the problem of inferring marginal probabilities and consider whether it is possible to "simply reduce" marginal inference from general discrete factor graphs to factor graphs in each of these seven subclasses. We characterize the reducibility of each class, showing in particular that the class of binary pairwise factor graphs is able to simply reduce only positive models. We also exhibit a continuous "spectral reduction" based on polynomial interpolation, which overcomes this limitation. Experiments assess the performance of standard approximate inference algorithms on the outputs of our reductions.

On the time delay in continuous in-cylinder sampling from IC engines

When gas sample is continuously drawn from the cylinder of an internal combustion engine, the sample that appears at the end of the sampling system corresponds to the in-cylinder content sometime ago because of the finite transit time which is a function of the cylinder pressure history. This variable delay causes a dispersion of the sample signal and makes the interpretation of the signal difficult An unsteady flow analysis of a typical sampling system was carried out for selected engine loads and speeds. For typical engine operation, a window in which the delay is approximately constant may be found. This window gets smaller with increase in engine speed, with decrease in load, and with the increase in exit pressure of the sampling system.

Reinforcement learning using a continuous time actor-critic framework with spiking neurons.

Animals repeat rewarded behaviors, but the physiological basis of reward-based learning has only been partially elucidated. On one hand, experimental evidence shows that the neuromodulator dopamine carries information about rewards and affects synaptic plasticity. On the other hand, the theory of reinforcement learning provides a framework for reward-based learning. Recent models of reward-modulated spike-timing-dependent plasticity have made first steps towards bridging the gap between the two approaches, but faced two problems. First, reinforcement learning is typically formulated in a discrete framework, ill-adapted to the description of natural situations. Second, biologically plausible models of reward-modulated spike-timing-dependent plasticity require precise calculation of the reward prediction error, yet it remains to be shown how this can be computed by neurons. Here we propose a solution to these problems by extending the continuous temporal difference (TD) learning of Doya (2000) to the case of spiking neurons in an actor-critic network operating in continuous time, and with continuous state and action representations. In our model, the critic learns to predict expected future rewards in real time. Its activity, together with actual rewards, conditions the delivery of a neuromodulatory TD signal to itself and to the actor, which is responsible for action choice. In simulations, we show that such an architecture can solve a Morris water-maze-like navigation task, in a number of trials consistent with reported animal performance. We also use our model to solve the acrobot and the cartpole problems, two complex motor control tasks. Our model provides a plausible way of computing reward prediction error in the brain. Moreover, the analytically derived learning rule is consistent with experimental evidence for dopamine-modulated spike-timing-dependent plasticity.

Slowness: an objective for spike-timing-dependent plasticity?

Our nervous system can efficiently recognize objects in spite of changes in contextual variables such as perspective or lighting conditions. Several lines of research have proposed that this ability for invariant recognition is learned by exploiting the fact that object identities typically vary more slowly in time than contextual variables or noise. Here, we study the question of how this "temporal stability" or "slowness" approach can be implemented within the limits of biologically realistic spike-based learning rules. We first show that slow feature analysis, an algorithm that is based on slowness, can be implemented in linear continuous model neurons by means of a modified Hebbian learning rule. This approach provides a link to the trace rule, which is another implementation of slowness learning. Then, we show analytically that for linear Poisson neurons, slowness learning can be implemented by spike-timing-dependent plasticity (STDP) with a specific learning window. By studying the learning dynamics of STDP, we show that for functional interpretations of STDP, it is not the learning window alone that is relevant but rather the convolution of the learning window with the postsynaptic potential. We then derive STDP learning windows that implement slow feature analysis and the "trace rule." The resulting learning windows are compatible with physiological data both in shape and timescale. Moreover, our analysis shows that the learning window can be split into two functionally different components that are sensitive to reversible and irreversible aspects of the input statistics, respectively. The theory indicates that irreversible input statistics are not in favor of stable weight distributions but may generate oscillatory weight dynamics. Our analysis offers a novel interpretation for the functional role of STDP in physiological neurons.

Continuous-time subspace flows related to the symmetric eigenproblem

The classes of continuous-time flows on Rn×p that induce the same flow on the set of p- dimensional subspaces of Rn×p are described. The power flow is briefly reviewed in this framework, and a subspace generalization of the Rayleigh quotient flow [Linear Algebra Appl. 368C, 2003, pp. 343-357] is proposed and analyzed. This new flow displays a property akin to deflation in finite time. © 2008 Yokohama Publishers.

Continuous dynamical systems that realize discrete optimization on the hypercube

We study the problem of finding a local minimum of a multilinear function E over the discrete set {0,1}n. The search is achieved by a gradient-like system in [0,1]n with cost function E. Under mild restrictions on the metric, the stable attractors of the gradient-like system are shown to produce solutions of the problem, even when they are not in the vicinity of the discrete set {0,1}n. Moreover, the gradient-like system connects with interior point methods for linear programming and with the analog neural network studied by Vidyasagar (IEEE Trans. Automat. Control 40 (8) (1995) 1359), in the same context. © 2004 Elsevier B.V. All rights reserved.

An experimental study of loss sources in a fan operating with continuous inlet stagnation pressure distortion

The viability of Boundary Layer Ingesting (BLI) engines for future aircraft propulsion is dependent on the ability to design robust, efficient engine fan systems for operation with continuously distorted inlet flow. A key step in this process is to develop an understanding of the specific mechanisms by which an inlet distortion affects the performance of a fan stage. In this paper, detailed full-annulus experimental measurements of the flow field within a low-speed fan stage operating with a continuous 60-degree inlet stagnation pressure distortion are presented. These results are used to describe the three-dimensional fluid mechanics governing the interaction between the fan and the distortion and to make a quantitative assessment of the impact on loss generation within the fan. A 5.3 percentage point reduction in stage total-to-total efficiency is observed as a result of the inlet distortion. The reduction in performance is shown to be dominated by increased loss generation in the rotor due to off-design incidence values at its leading edge, an effect which occurs throughout the annulus despite the localised nature of the inlet distortion. Increased loss generation in the stator row is also observed due to flow separations that are shown to be caused by whirl angle distortion at rotor exit. By addressing these losses, it should be possible to achieve improved efficiency in BLI fan systems. Copyright © 2012 by ASME.

Continuous weak measurement of a trapped electron using a percolation field effect transistor

We investigate the use of a percolation-field-effect-transistor for the continuous weak measurement of a spatially Rabi oscillating trapped electron through the change in percolation pathway of the transistor channel. In contrast to conventional devices, this detection mechanism in principle does not require a change in the stored energy of the gate capacitance to modify the drain current, so reducing the measurement back-action. The signal-to-noise ratio and measurement bandwidth are seen to be improved compared to conventional devices, allowing further aspects of the dynamic behaviour to be observed. © 2013 AIP Publishing LLC.

Multi-objective optimisation of horizontal axis wind turbine structure and energy production using aerofoil and blade properties as design variables

The design of wind turbine blades is a true multi-objective engineering task. The aerodynamic effectiveness of the turbine needs to be balanced with the system loads introduced by the rotor. Moreover the problem is not dependent on a single geometric property, but besides other parameters on a combination of aerofoil family and various blade functions. The aim of this paper is therefore to present a tool which can help designers to get a deeper insight into the complexity of the design space and to find a blade design which is likely to have a low cost of energy. For the research we use a Computational Blade Optimisation and Load Deflation Tool (CoBOLDT) to investigate the three extreme point designs obtained from a multi-objective optimisation of turbine thrust, annual energy production as well as mass for a horizontal axis wind turbine blade. The optimisation algorithm utilised is based on Multi-Objective Tabu Search which constitutes the core of CoBOLDT. The methodology is capable to parametrise the spanning aerofoils with two-dimensional Free Form Deformation and blade functions with two tangentially connected cubic splines. After geometry generation we use a panel code to create aerofoil polars and a stationary Blade Element Momentum code to evaluate turbine performance. Finally, the obtained loads are fed into a structural layout module to estimate the mass and stiffness of the current blade by means of a fully stressed design. For the presented test case we chose post optimisation analysis with parallel coordinates to reveal geometrical features of the extreme point designs and to select a compromise design from the Pareto set. The research revealed that a blade with a feasible laminate layout can be obtained, that can increase the energy capture and lower steady state systems loads. The reduced aerofoil camber and an increased L/. D-ratio could be identified as the main drivers. This statement could not be made with other tools of the research community before. © 2013 Elsevier Ltd.

An experimental study of loss sources in a fan operating with continuous inlet stagnation pressure distortion

The viability of boundary layer ingesting (BLI) engines for future aircraft propulsion is dependent on the ability to design robust, efficient engine fan systems for operation with continuously distorted inlet flow. A key step in this process is to develop an understanding of the specific mechanisms by which an inlet distortion affects the performance of a fan stage. In this paper, detailed full-annulus experimental measurements of the flow field within a low-speed fan stage operating with a continuous 60 deg inlet stagnation pressure distortion are presented. These results are used to describe the three-dimensional fluid mechanics governing the interaction between the fan and the distortion and to make a quantitative assessment of the impact on loss generation within the fan. A 5.3 percentage point reduction in stage total-to-total efficiency is observed as a result of the inlet distortion. The reduction in performance is shown to be dominated by increased loss generation in the rotor due to off-design incidence values at its leading edge, an effect that occurs throughout the annulus despite the localized nature of the inlet distortion. Increased loss in the stator row is also observed due to flow separations that are shown to be caused by whirl angle distortion at rotor exit. By addressing these losses, it should be possible to achieve improved efficiency in BLI fan systems. © 2013 by ASME.