Influence of shock wave propagation on dielectric barrier discharge plasma actuator performance

Interest in plasma actuators as active flow control devices is growing rapidly due to their lack of mechanical parts, light weight and high response frequency. Although the flow induced by these actuators has received much attention, the effect that the external flow has on the performance of the actuator itself must also be considered, especially the influence of unsteady high-speed flows which are fast becoming a norm in the operating flight envelopes. The primary objective of this study is to examine the characteristics of a dielectric barrier discharge (DBD) plasma actuator when exposed to an unsteady flow generated by a shock tube. This type of flow, which is often used in different studies, contains a range of flow regimes from sudden pressure and density changes to relatively uniform high-speed flow regions. A small circular shock tube is employed along with the schlieren photography technique to visualize the flow. The voltage and current traces of the plasma actuator are monitored throughout, and using the well-established shock tube theory the change in the actuator characteristics are related to the physical processes which occur inside the shock tube. The results show that not only is the shear layer outside of the shock tube affected by the plasma but the passage of the shock front and high-speed flow behind it also greatly influences the properties of the plasma

Self-adaptive agent modelling of wind farm for energy capture optimisation

© 2017, Springer-Verlag GmbH Germany. Typical approaches to wind turbines placement problem take into account the wind distribution and wake effects to maximise the total aggregate farm’s energy production in a centralised top–down optimisation problem. An alternative approach, however, is yet to be addressed as the problem can be instead modelled in a decentralised bottom–up manner emulating a system of self-adaptive agents. The potential advantages of this is that it offers easier scalability for high dimension problems as well as it enables an easier adaptation to the complex structure of the design problem. This paper contributes to this and presents an evolutionary algorithm to model and solve the wind farm layout design problem as a system of interrelated agents. The framework is applied to problems with different complexities where the quality of the results is examined. The convergence and scalability of the suggested technique indicate promising results for small to large scale wind farms, which, in turn, encourage the application of such an evolutionary based algorithm for real world wind farm design problem

Trading Off Environmental and Economic Scheduling of a Renewable Energy Based Microgrid Under Uncertainties

Smart power grids are transitioning towards effective employment of distributed energy resources including renewable energy sources to address the growing environmental concerns related to the pollutant emissions of fossil fuels. In this context, this paper proposes the directed search domain (DSD) method to compute the combined environmental and economic dispatch in a microgrid with battery energy storage systems, photovoltaic plants, wind turbines, fuel cells, and microturbines. The DSD algorithm is implemented for a multiobjective problem to obtain evenly-distributed Pareto optimal points by shrinking the original search domain into hypercone. This paper computes the optimal unit commitment and the related power dispatch while simultaneously minimizing the total pollutant emissions and operating costs. The best trade-off solution among the entire set of Pareto optimal points is computed by using the Fuzzy satisfying technique. The uncertainties associated with the forecasting of prices, load demand, wind, and photovoltaic power outputs are accounted for by employing the stochastic programming. The empirical results indicate the potential of the presented DSD algorithm in terms of the objective values, solution times, and quasi-even distribution of the Pareto set

Spatial Characterization of Wetting in Porous Media Using Local Lattice-Boltzmann Simulations

Wettability is one of the critical parameters affecting multiphase flow in porous media. The wettability is determined by the affinity of fluids to the rock surface, which varies due to factors such as mineral heterogeneity, roughness, ageing, and pore-space geometry. It is well known that wettability varies spatially in natural rocks, and it is still generally considered a constant parameter in pore-scale simulation studies. The accuracy of pore-scale simulation of multiphase flow in porous media is undermined by such inadequate wettability models. The advent of in situ visualization techniques, e.g. X-ray imaging and microtomography, enables us to characterize the spatial distribution of wetting more accurately. There are several approaches for such characterization. Most include the construction of a meshed surface of the interface surfaces in a segmented X-ray image and are known to have significant errors arising from insufficient resolution and surface-smoothing algorithms. This work presents a novel approach for spatial determination of wetting properties using local lattice-Boltzmann simulations. The scheme is computationally efficient as the segmented X-ray image is divided into subdomains before conducting the lattice-Boltzmann simulations, enabling fast simulations. To test the proposed method, it was applied to two synthetic cases with known wettability and three datasets of imaged fluid distributions. The wettability map was obtained for all samples using local lattice-Boltzmann calculations on trapped ganglia and optimization on surface affinity parameters. The results were quantitatively compared with a previously developed geometrical contact angle determination method. The two synthetic cases were used to validate the results of the developed workflow, as well as to compare the wettability results with the geometrical analysis method. It is shown that the developed workflow accurately characterizes the wetting state in the synthetic porous media with an acceptable uncertainty and is better to capture extreme wetting conditions. For the three datasets of imaged fluid distributions, our results show that the obtained contact angle distributions are consistent with the geometrical method. However, the obtained contact angle distributions tend to have a narrower span and are considered more realistic compared to the geometrical method. Finally, our results show the potential of the proposed scheme to efficiently obtain wettability maps of porous media using X-ray images of multiphase fluid distributions. The developed workflow can help for more accurate characterization of the wettability map in the porous media using limited experimental data, and hence more accurate digital rock analysis of multiphase flow in porous media

CFD modelling of velocity fields around a fume cupboard: Evaluating static and dynamic meshes with experimental measurements

This paper presents a comparison of experimental and numerical modelling results of the velocity field around a fume cupboard with a static and a dynamic mesh. During fume cupboard testing, components are required to move which mimic typical operating conditions, the amount of tracer gas released is then measured. This tracer gas is harmful to the environment and so an alternative is required. Advanced Computational Fluid Dynamics (CFD) techniques, such as dynamic meshing, have been utilised to replicate aspects of the current tests. The fume cupboard was tested in normal operating conditions and under the influence of a board inducing a wake close to the fume cupboard entrance. The velocity fields have been compared and show a reasonable level of accuracy with a percentage difference between experimental and simulated results of around 5% using both a static and a dynamic domain. This is an improvement on the 15–20% accuracy for detecting concentration of tracer gas using previous experimental methods. The aim of this work is to satisfy the scientific community and fume cupboard operators that CFD is sufficiently accurate to assess fume cupboard performance under real world scenarios

An Empirical Study of Service Quality and Customer Satisfaction of Malaysian Air Passenger

The vast majority of Malaysian air passenger have competitive choices among airlines and different service options. Customer satisfaction is what guarantees the survival of airlines and it is achievable only by matching the passengers needs with the services. Assessment of service quality and its subsequent management is of utmost importance for them to be competitive and successful in this industry. Thus, the purpose of this study was set to determine the relationship between service quality (SERVQUAL) and customer satisfaction of Malaysian air passenger. An adopted SERVQUAL instrument including five service quality constructs: empathy, tangibles, responsiveness, reliability and assurance were employed to measure the passengers perceptions about the service quality of airlines. Data were collected from 187 respondents using convenience sampling. The outcome of multiple regression analysis showed that responsiveness, reliability and assurance have a positive significant impact on customer satisfaction. However, empathy and tangible variables recorded an insignificant relationship with customer satisfaction. Conclusion and recommendation were discussed.     Keywords: service quality, customer satisfaction, air passenge

Plasma actuator: influence of dielectric surface temperature

Plasma actuators have become the topic of interest of many researchers for the purpose of flow control. They have the advantage of manipulating the flow without the need for any moving parts, a small surface profile which does not disturb the free stream flow, and the ability to switch them on or off depending on the particular situation (active flow control). Due to these characteristics they are becoming very popular for flow control over aircraft wings. The objective of the current study is to examine the effect of the actuator surface temperature on its performance. This is an important topic to understand when dealing with real life aircraft equipped with plasma actuators. The temperature variations encountered during a flight envelope may have adverse effects in actuator performance. A peltier heater along with dry ice are used to alter the actuator temperature, while particle image velocimetry (PIV) is utilised to analyse the flow field. The results show a significant change in the induced flow field by the actuator as the surface temperature is varied. It is found that for a constant peak-to-peak voltage the maximum velocity produced by the actuator depends directly on the dielectric surface temperature. The findings suggest that by changing the actuator temperature the performance can be maintained or even altered at different environmental conditions

Active flow control over a backward-facing step using plasma actuation

© 2016 IAA.Due to the more stringent aviation regulations on fuel consumption and noise reduction, the interest for smaller and mechanically less complex devices for flow separation control has increased. Plasma actuators are currently among the most studied typology of devices for active flow control purposes due to their small size and lightweight. In this study, a single dielectric barrier discharge (SDBD) actuator is used on a backward-facing step to assess its effects on the separated turbulent shear layer and its reattachment location. A range of actuating modulation frequencies, related to the natural frequencies of shear layer instability (flapping) and vortex shedding instability, are examined. The particle image velocimetry technique is used to analyse the flow over the step and the reattachment location. The bulk-flow experiments show negligible effects both on the shear layer and on the reattachment location for every frequency considered, and the actuator is not able to induce a sufficient velocity increase at the step separation point

Scalable and Interpretable One-class SVMs with Deep Learning and Random Fourier features

One-class support vector machine (OC-SVM) for a long time has been one of the most effective anomaly detection methods and extensively adopted in both research as well as industrial applications. The biggest issue for OC-SVM is yet the capability to operate with large and high-dimensional datasets due to optimization complexity. Those problems might be mitigated via dimensionality reduction techniques such as manifold learning or autoencoder. However, previous work often treats representation learning and anomaly prediction separately. In this paper, we propose autoencoder based one-class support vector machine (AE-1SVM) that brings OC-SVM, with the aid of random Fourier features to approximate the radial basis kernel, into deep learning context by combining it with a representation learning architecture and jointly exploit stochastic gradient descent to obtain end-to-end training. Interestingly, this also opens up the possible use of gradient-based attribution methods to explain the decision making for anomaly detection, which has ever been challenging as a result of the implicit mappings between the input space and the kernel space. To the best of our knowledge, this is the first work to study the interpretability of deep learning in anomaly detection. We evaluate our method on a wide range of unsupervised anomaly detection tasks in which our end-to-end training architecture achieves a performance significantly better than the previous work using separate training.Comment: Accepted at European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD) 201

Development of DBD plasma actuators: The double encapsulated electrode

Plasma actuators are electrical devices that generate a wall bounded jet without the use of any moving parts. For aerodynamic applications they can be used as flow control devices to delay separation and augment lift on a wing. The standard plasma actuator consists of a single encapsulated (ground) electrode. The aim of this project is to investigate the effect of varying the number and distribution of encapsulated electrodes in the dielectric layer. Utilising a transformer cascade, a variety of input voltages are studied for their effect. In the quiescent environment of a Faraday cage the velocity flow field is recorded using particle image velocimetry. Through understanding of the mechanisms involved in producing the wall jet and the importance of the encapsulated electrode a novel actuator design is proposed. The actuator design distributes the encapsulated electrode throughout the dielectric layer. The experiments have shown that actuators with a shallow initial encapsulated electrode induce velocities greater than the baseline case at the same voltage. Actuators with a deep initial encapsulated electrode are able to induce the highest velocities as they can operate at higher voltages without breakdown of the dielectric