Implementation and performance analysis of efficient grid-free integral wall models in unstructured-grid LES solvers

Two zonal wall models based on integral form of the boundary layer differential equations, albeit with algebraic complexity, have been implemented in an unstructured-grid cell-centered finite-volume LES solver. The first model is a novel implementation of the ODE equilibrium wall model, where the velocity profile is expressed in the integral form using the constant shear-stress layer assumption and the integral is evaluated using a spectral quadrature method, resulting in a local and algebraic (grid-free) formulation. The second model, which closely follows the integral wall model of Yang et al. (Phys. Fluids 27, 025112 (2015)), is based on the vertically-integrated thin-boundary-layer PDE along with a prescribed composite velocity profile in the wall-modeled region. Several numerical challenges unique to the implementation of these integral models in unstructured mesh environments, such as the exchange of wall quantities between wall faces and LES cells, and the computation of surface gradients, are identified and possible remedies are proposed. The performance of the wall models is assessed both in a priori and a posteriori settings against the traditional finite-volume based ODE equilibrium wall model, showing a comparable computational cost for the integral wall model, and superior performance for the spectral implementation over the finite-volume based approach. Load imbalance among the processors in parallel simulations seems to severely degrade the parallel efficiency of finite-volume based ODE wall model, whereas the spectral implementation is remarkably agnostic to these effects

Compensation of Torque Ripple in High Performance BLDC Motor Drives

Brushless DC motor drives (BLDC) are finding expanded use in high performance applications where torque smoothness is essential. The nature of the square-wave current excitation waveforms in BLDC motor drives permits some important system simplifications compared to sinusoidal permanent magnet AC (PMAC) machines. However, it is the simplicity of the BLDC motor drive that is responsible for causing an additional source of ripple torque commonly known as commutation torque to develop. In this paper, a compensation technique for reducing the commutation torque ripple is proposed. With the experimental results, the proposed method demonstrates the effectiveness for a control system using the BLDC motors that requires high speed and accuracy

Numerical simulations of oblique shock/boundary-layer interaction at a high Reynolds number

This study investigates numerical analysis of the oblique shock/boundary-layer interaction (OSBLI) in a Mach 1.7 flow with a unit Reynolds number of 35 million. Two methods of simulations are performed and compared with an experiment. While two different delayed detached-eddy simulations (DDES) are performed to simulate the fullspan geometry, a wall-modeled large-eddy simulation (WM-LES) is carried out to study the physics near the mid-span area. In the experiment, the boundary layer is tripped at the leading edge of the flat plate to ensure fully turbulent boundary layer at the interaction zone. The tripping device in the WM-LES computations was simulated by artificial blowing and suction, while in the DDES simulation turbulence is generated by a Reynolds-Averaged Navier-Stokes (RANS) model and its intensity is adjusted to match the experimental one. Challenges to simulate this test case as well as comparison between the two numerical studies with the experimental results a re highlighted in this paper

Carrier-microencapsulation using Al-catecholate complex to suppress arsenopyrite oxidation: Evaluation of the coating stability under simulated weathering conditions

Arsenopyrite (FeAsS) is the most common primary arsenic-sulfide mineral in nature, and its oxidation causes the release of toxic arsenic (As). To mitigate these problems, carrier-microencapsulation (CME), a technique that passivates sulfide minerals by covering their surfaces with a protective coating, has been developed. In the previous study of authors on CME, Al-catecholate complex significantly suppressed arsenopyrite oxidation via electron donating effects of the complex and the formation of an Al-oxyhydroxide coating. For the application of this technique to real tailings, however, further study should be carried out to elucidate long-term effectiveness of the coating to suppress arsenopyrite oxidation. This study investigates the stability of the coating formed on arsenopyrite by Al-based CME using weathering tests. The Al-oxyhydroxide coating suppressed arsenopyrite oxidation until about 50 days of the experiment, but after this, the amounts of oxidation products like dissolved S and As increased due to the gradual dissolution of the coating with time as a result of the low pH of leachate. This suggests that co-disposal of Al-based CME-treated arsenopyrite with minerals that have appropriate neutralization potentials, so that the pH is maintained at around 5 to 8 where Al-oxyhydroxide is stable

25th annual computational neuroscience meeting: CNS-2016

The same neuron may play different functional roles in the neural circuits to which it belongs. For example, neurons in the Tritonia pedal ganglia may participate in variable phases of the swim motor rhythms [1]. While such neuronal functional variability is likely to play a major role the delivery of the functionality of neural systems, it is difficult to study it in most nervous systems. We work on the pyloric rhythm network of the crustacean stomatogastric ganglion (STG) [2]. Typically network models of the STG treat neurons of the same functional type as a single model neuron (e.g. PD neurons), assuming the same conductance parameters for these neurons and implying their synchronous firing [3, 4]. However, simultaneous recording of PD neurons shows differences between the timings of spikes of these neurons. This may indicate functional variability of these neurons. Here we modelled separately the two PD neurons of the STG in a multi-neuron model of the pyloric network. Our neuron models comply with known correlations between conductance parameters of ionic currents. Our results reproduce the experimental finding of increasing spike time distance between spikes originating from the two model PD neurons during their synchronised burst phase. The PD neuron with the larger calcium conductance generates its spikes before the other PD neuron. Larger potassium conductance values in the follower neuron imply longer delays between spikes, see Fig. 17.Neuromodulators change the conductance parameters of neurons and maintain the ratios of these parameters [5]. Our results show that such changes may shift the individual contribution of two PD neurons to the PD-phase of the pyloric rhythm altering their functionality within this rhythm. Our work paves the way towards an accessible experimental and computational framework for the analysis of the mechanisms and impact of functional variability of neurons within the neural circuits to which they belong

26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 - Meeting Abstracts - Antwerp, Belgium. 15–20 July 2017

This work was produced as part of the activities of FAPESP Research,\ud Disseminations and Innovation Center for Neuromathematics (grant\ud 2013/07699-0, S. Paulo Research Foundation). NLK is supported by a\ud FAPESP postdoctoral fellowship (grant 2016/03855-5). ACR is partially\ud supported by a CNPq fellowship (grant 306251/2014-0)