DNS of EGR-type turbulent flame in MILD condition

Three-dimensional direct numerical simulation (DNS) of exhaust gas recirculation (EGR)-type turbulent combustion operated in moderate and intense low-oxygen dilution (MILD) condition has been carried out to study the flame structure and flame interaction. In order to achieve adequate EGR-type initial/inlet mixture fields, partially premixed mixture fields which are correlated with the turbulence are carefully preprocessed. The chemical kinetics is modelled using a skeletal mechanism for methane-air combustion. The results suggest that the flame fronts have thin flame structure and the direct link between the mean reaction rate and scalar dissipation rate remains valid in the EGR-type combustion with MILD condition. However, the commonly used canonical flamelet is not fully representative for MILD combustion. During the flame-flame interactions, the heat release rate increases higher than the maximum laminar flame value, while the gradient of progress variable becomes smaller than laminar value. It is also proposed that the reaction rate and the scalar gradient can be used as a marker for the flame interaction. © 2012 The Combustion Institute. Published by Elsevier Inc. All rights reserved.

Real-time marker prediction and CoR estimation in optical motion capture

Optical motion capture systems suffer from marker occlusions resulting in loss of useful information. This paper addresses the problem of real-time joint localisation of legged skeletons in the presence of such missing data. The data is assumed to be labelled 3d marker positions from a motion capture system. An integrated framework is presented which predicts the occluded marker positions using a Variable Turn Model within an Unscented Kalman filter. Inferred information from neighbouring markers is used as observation states; these constraints are efficient, simple, and real-time implementable. This work also takes advantage of the common case that missing markers are still visible to a single camera, by combining predictions with under-determined positions, resulting in more accurate predictions. An Inverse Kinematics technique is then applied ensuring that the bone lengths remain constant over time; the system can thereby maintain a continuous data-flow. The marker and Centre of Rotation (CoR) positions can be calculated with high accuracy even in cases where markers are occluded for a long period of time. Our methodology is tested against some of the most popular methods for marker prediction and the results confirm that our approach outperforms these methods in estimating both marker and CoR positions. © 2012 Springer-Verlag.

A high-resolution atlas and statistical model of the human heart from multislice CT

Atlases and statistical models play important roles in the personalization and simulation of cardiac physiology. For the study of the heart, however, the construction of comprehensive atlases and spatio-temporal models is faced with a number of challenges, in particular the need to handle large and highly variable image datasets, the multi-region nature of the heart, and the presence of complex as well as small cardiovascular structures. In this paper, we present a detailed atlas and spatio-temporal statistical model of the human heart based on a large population of 3D+time multi-slice computed tomography sequences, and the framework for its construction. It uses spatial normalization based on nonrigid image registration to synthesize a population mean image and establish the spatial relationships between the mean and the subjects in the population. Temporal image registration is then applied to resolve each subject-specific cardiac motion and the resulting transformations are used to warp a surface mesh representation of the atlas to fit the images of the remaining cardiac phases in each subject. Subsequently, we demonstrate the construction of a spatio-temporal statistical model of shape such that the inter-subject and dynamic sources of variation are suitably separated. The framework is applied to a 3D+time data set of 138 subjects. The data is drawn from a variety of pathologies, which benefits its generalization to new subjects and physiological studies. The obtained level of detail and the extendability of the atlas present an advantage over most cardiac models published previously. © 1982-2012 IEEE.

Variability in encoding precision accounts for visual short-term memory limitations.

It is commonly believed that visual short-term memory (VSTM) consists of a fixed number of "slots" in which items can be stored. An alternative theory in which memory resource is a continuous quantity distributed over all items seems to be refuted by the appearance of guessing in human responses. Here, we introduce a model in which resource is not only continuous but also variable across items and trials, causing random fluctuations in encoding precision. We tested this model against previous models using two VSTM paradigms and two feature dimensions. Our model accurately accounts for all aspects of the data, including apparent guessing, and outperforms slot models in formal model comparison. At the neural level, variability in precision might correspond to variability in neural population gain and doubly stochastic stimulus representation. Our results suggest that VSTM resource is continuous and variable rather than discrete and fixed and might explain why subjective experience of VSTM is not all or none.

No evidence for an item limit in change detection.

Change detection is a classic paradigm that has been used for decades to argue that working memory can hold no more than a fixed number of items ("item-limit models"). Recent findings force us to consider the alternative view that working memory is limited by the precision in stimulus encoding, with mean precision decreasing with increasing set size ("continuous-resource models"). Most previous studies that used the change detection paradigm have ignored effects of limited encoding precision by using highly discriminable stimuli and only large changes. We conducted two change detection experiments (orientation and color) in which change magnitudes were drawn from a wide range, including small changes. In a rigorous comparison of five models, we found no evidence of an item limit. Instead, human change detection performance was best explained by a continuous-resource model in which encoding precision is variable across items and trials even at a given set size. This model accounts for comparison errors in a principled, probabilistic manner. Our findings sharply challenge the theoretical basis for most neural studies of working memory capacity.

Convex relaxation of mixture regression with efficient algorithms

We develop a convex relaxation of maximum a posteriori estimation of a mixture of regression models. Although our relaxation involves a semidefinite matrix variable, we reformulate the problem to eliminate the need for general semidefinite programming. In particular, we provide two reformulations that admit fast algorithms. The first is a max-min spectral reformulation exploiting quasi-Newton descent. The second is a min-min reformulation consisting of fast alternating steps of closed-form updates. We evaluate the methods against Expectation-Maximization in a real problem of motion segmentation from video data.

A Novel System for Reducing Turbo-Lag by Injection of Compressed Gas into the Exhaust Manifold

A key challenge in achieving good transient performance of highly boosted engines is the difficulty of accelerating the turbocharger from low air flow conditions (“turbo lag”). Multi-stage turbocharging, electric turbocharger assistance, electric compressors and hybrid powertrains are helpful in the mitigation of this deficit, but these technologies add significant cost and integration effort. Air-assist systems have the potential to be more cost-effective. Injecting compressed air into the intake manifold has received considerable attention, but the performance improvement offered by this concept is severely constrained by the compressor surge limit. The literature describes many schemes for generating the compressed gas, often involving significant mechanical complexity and/or cost. In this paper we demonstrate a novel exhaust assist system in which a reservoir is charged during braking. Experiments have been conducted using a 2.0 litre light-duty Diesel engine equipped with exhaust gas recirculation (EGR) and variable geometry turbine (VGT) coupled to an AC transient dynamometer, which was controlled to mimic engine load during in-gear braking and acceleration. The experimental results confirm that the proposed system reduces the time to torque during the 3rd gear tip-in by around 60%. Such a significant improvement was possible due to the increased acceleration of turbocharger immediately after the tip-in. Injecting the compressed gas into the exhaust manifold circumvents the problem of compressor surge and is the key enabler of the superior performance of the proposed concept.

The Effect of Inlet Guide Vanes on Inlet Flow Distortion Transfer and Transonic Fan Stability

An investigation was carried out into the effects of variable inlet guide vanes (VIGVs) on the performance and stability margin of a transonic fan in the presence of inlet flow distortion. The study was carried out using computational fluid dynamics (CFD) and validated with experimental data. The capability of CFD to predict the changes in performance with or without VIGVs in the presence of an inlet flow distortion is assessed. Results show that the VIGVs improve the performance and stability margin and do so by reducing the amount of swirl at inlet to the rotor component of the fan.

The behaviour of laminar stratified methane/air flames in counterflow

Flames propagating through a mixture with a gradient of equivalence ratio have been previously demonstrated to travel faster or slower than their equivalent premixed flames. The present study aims to numerically investigate the response of strained laminar methane-air flames to such gradients. The flames are simulated in a counterflow configuration where a premixed reactant stream at equivalence ratio φR opposes a hot equilibrium stream at equivalence ratio φP. Premixed and stratified flames are compared with respect to the equivalence ratio φ* and the corresponding gradient ∇φ* at the point of peak heat release rate, for three strain rates, a=50, 300 and 500s-1 and a range of φ*. The effect of different stratification levels is also investigated by varying the ratio of φP to φR, Θ. Results indicate that, as long as flames stabilize within the diffusion layer and Θ>1, increased heat release rate Q is seen throughout the progress variable space in comparison to the premixed state. In contrast, an attenuation of heat release rate is seen for Θ<1. The enhancement (or attenuation) of heat release varies monotonically with Θ. The effect of stratification on flame behavior becomes more pronounced as the strain rate increases. The present study reveals the mechanisms for the propagation of quasi-steady stratified flames under lean and rich conditions: stratified flames are primarily dominated by the diffusion of heat under lean conditions, and diffusion of H2 under rich conditions. Thanks to species and thermal support, stratified flames continue to burn beyond the premixed lean and rich flammability limits. Further investigation on the unsteady response of flames to the fluctuating equivalence ratio implies that the steady results represent the unsteady response well, as long as φ* and ∇φ* are similar in both steady and unsteady cases. © 2013 The Combustion Institute.

Vibration of a high-altitude tethered balloon with application to climate engineering

A balloon tethered at an altitude of 20 km could deliver a particulate cloud leading to global cooling. Tethering a balloon at this altitude poses significant problems with respect to vibration and stability, especially in regions of high wind. No-one has ever proposed, yet alone launched, a balloon at an altitude of 20 km tethered to the ground. Owing to wind, the tether needs to be 23 km in length and is to be fixed to a ship at sea or on land in equatorial regions. Whilst the balloon at 20 km is subject to relatively modest wind conditions, at jet stream altitudes (10km) the tether will experience much higher wind loadings, not only because of the high wind speeds of up to 300 km / hr but also because of the high air density. A tether of circular cross section in these high winds will be subject to horizontal and downward drag forces that would bring the aerostat down. For this reason it is advantageous to consider a self-aligning tether of an aerodynamic cross section whereby it is possible to reduce the drag substantially. One disadvantage of a non-circular tether is the possibility of flutter and galloping instabilities. It is reasonably straightforward to model these phenomena for short lengths of aerofoil, but the situation becomes more complex for a 20 km tensioned tether with large deflection and curvature, variable wind speed, variable air density and variable tension. Analysis using models of infinite length are used to establish the stability at a local scale where the tension, aerodynamic and geometric properties are considered constant. Dispersion curve analysis is useful here. But for dynamics on a long-wavelength scale (several km) then a full non-linear analysis is required. This non-linear model can be used to establish the local values of tension appropriate for the dispersion analysis. This keynote presentation will give some insight into these issues.

Reynolds number effects on scalar dissipation rate transport and its modeling in turbulent premixed combustion

The effects of turbulent Reynolds number, Ret, on the transport of scalar dissipation rate of reaction progress variable in the context of Reynolds averaged Navier-Stokes simulations have been analyzed using three-dimensional simplified chemistry-based direct numerical simulation (DNS) data of freely propagating turbulent premixed flames with different values of Ret. Scaling arguments have been used to explain the effects of Ret on the turbulent transport, scalar-turbulence interaction, and the combined reaction and molecular dissipation terms. Suitable modifications to the models for these terms have been proposed to account for Ret effects, and the model parameters include explicit Ret dependence. These expressions approach expected asymptotic limits for large values of Ret. However, turbulent Reynolds number Ret does not seem to have any major effects on the modeling of the term arising from density variation. Copyright © Taylor and Francis Group, LLC.

A fast detailed-chemistry modelling approach for simulating the SI-HCCI transition

An established Stochastic Reactor Model (SRM) is used to simulate the transition from Spark Ignition (SI) to Homogeneous Charge Compression Ignition (HCCI) combustion mode in a four cylinder in-line four-stroke naturally aspirated direct injection SI engine with cam profile switching. The SRM is coupled with GT-Power, a one-dimensional engine simulation tool used for modelling engine breathing during the open valve portion of the engine cycle, enabling multi-cycle simulations. The mode change is achieved by switching the cam profiles and phasing, resulting in a Negative Valve Overlap (NVO), opening the throttle, advancing the spark timing and reducing the fuel mass as well as using a pilot injection. A proven technique for tabulating the model is used to create look-up tables in both SI and HCCI modes. In HCCI mode several tables are required, including tables for the first NVO, transient valve timing NVO, transient valve timing HCCI and steady valve timing HCCI and NVO. This results in the ability to simulate the transition with detailed chemistry in very short computation times. The tables are then used to optimise the transition with the goal of reducing NO x emissions and fluctuations in IMEP. Copyright © 2010 SAE International.

A detailed chemistry simulation of the SI-HCCI transition

A Stochastic Reactor Model (SRM) has been used to simulate the transition from Spark Ignition (SI) mode to Homogeneous Charge Compression Ignition (HCCI) mode in a four cylinder in-line four-stroke naturally aspirated direct injection SI engine with cam profile switching. The SRM is coupled with GT-Power, a one-dimensional engine simulation tool used for modelling engine breathing during the open valve portion of the engine cycle, enabling multi-cycle simulations. The model is initially calibrated in both modes using steady state data from SI and HCCI operation. The mode change is achieved by switching the cam profiles and phasing, resulting in a Negative Valve Overlap (NVO), opening the throttle, advancing the spark timing and reducing the fuel mass as well as utilising a pilot injection. Experimental data is presented along with the simulation results. The model is used to investigate key control parameters and their effects on parameters that are difficult to measure experimentally. The effect of the spark in the first HCCI cycles is found to have a major impact on the stability of the transition. Copyright © 2010 SAE International.

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.