Calculation of subsonic and supersonic steady and unsteady aerodynamic forces using velocity potential aerodynamic elements

Expressions for calculation of subsonic and supersonic, steady and unsteady aerodynamic forces are derived, using the concept of aerodynamic elements applied to the downwash velocity potential method. Aerodynamic elements can be of arbitrary out of plane polygon shape, although numerical calculations are restricted to rectangular elements, and to the steady state case in the supersonic examples. It is suggested that the use of conforming, in place of rectangular elements, would give better results. Agreement with results for subsonic oscillating T tails is fair, but results do not converge as the number of collocation points is increased. This appears to be due to the form of expression used in the calculations. The methods derived are expected to facilitate automated flutter analysis on the computer. In particular, the aerodynamic element concept is consistent with finite element methods already used for structural analysis. The method is universal for the complete Mach number range, and, finally, the calculations can be arranged so that they do not have to be repeated completely for every reduced frequency

Learning by Doing: Evaluation of an Educational VR Application for the Care of Schizophrenic Patients

Nursing students learn a variety of skills to work in a clinic, such as dealing with patients with particular requirements, handling expensive equipment, and assisting doctors with treatments. However, a specific situation may require hands-on experience that cannot be easily conveyed through a textbook or a video, such as caring for a schizophrenic patient. Simulation has been considered as an effective method to replace observation-based clinical placement to overcome safety issues. In this paper, we investigate the possibility of employing a virtual reality (VR) learning platform for nursing students to learn how to care for schizophrenic patients. Using 360-degree video and a head-mounted display (HMD), students experienced virtual patients who have schizophrenia portrayed by professional actors. Our key contribution is in the insights about the design of educational VR applications, highlighting the potential value of VR for training students with non-technical backgrounds

Policies And International Integration: Influences On Trade And Foreign Direct Investment

This paper assesses the importance of border and non-border policies for global economic integration. The focus is on four widely-advocated policies: removing explicit restrictions to trade and FDI; promoting domestic competition; improving the adaptability of labour markets; and ensuring adequate levels of infrastructure capital. The analysis covers FDI and trade in both goods and services, thus aiming to account for the most important channels of globalisation and dealing with most modes of cross-border services supply. It first describes trends in trade, FDI and the four sets of policies using a large set of structural policy indicators recently constructed by the OECD, including the new summary indicators for FDI-specific regulations described in Golub (2003). It then estimates the impact of policies on bilateral trade and bilateral and multilateral FDI. The results highlight that, despite extensive liberalisation over the past two decades, there is scope for further reducing policy barriers to integration of OECD markets. Remaining barriers have a significant impact on trade and FDI, with anticompetitive domestic regulations and restrictive labour market arrangements estimated to curb integration as much as explicit trade and FDI restrictions. Simulating the removal of such barriers suggests that the quantitative effects of further liberalisation of trade, FDI and domestic product and labour markets on global integration could be substantial

Erratum: Dirichlet Forms and Dirichlet Operators for Infinite Particle Systems: Essential Self-adjointness

We reprove the essential self-adjointness of the Dirichlet operators of Dirchlet forms for infinite particle systems with superstable and sub-exponentially decreasing interactions.Comment: This is an erratum to the work appeared in J. Math. Phys. 39(12), 6509-6536 (1998

Depressed clad hollow optical fiber with fundamental LP01 mode cut-off

We propose a depressed clad hollow optical fiber with fundamental (LP01) mode cut-off suitable for high power short-wavelength, especially three-level, fiber laser operation by introducing highly wavelength dependent losses at longer wavelengths. The cut-off characteristic of such fiber structure was investigated. A Yb-doped depressed clad hollow optical fiber laser generating 59.1W of output power at 1046nm with 86% of slope efficiency with respect to the absorbed pump power was realised by placing the LP01 mode cut-off at ~1100nm

Attitude Control System Design & Verification for CNUSAIL-1 with Solar/Drag Sail

CNUSAIL-1, to be launched into low-earth orbit, is a cubesat-class satellite equipped with a 2 m × 2 m solar sail. One of CNUSAIL’s missions is to deploy its solar sail system, thereby deorbiting the satellite, at the end of the satellite’s life. This paper presents the design results of the attitude control system for CNUSAIL-1, which maintains the normal vector of the sail by a 3-axis active attitude stabilization approach. The normal vector can be aligned in two orientations: i) along the anti-nadir direction, which minimizes the aerodynamic drag during the nadir-pointing mode, or ii) along the satellite velocity vector, which maximizes the drag during the deorbiting mode. The attitude control system also includes a B-dot controller for detumbling and an eigen-axis maneuver algorithm. The actuators for the attitude control are magnetic torquers and reaction wheels. The feasibility and performance of the design are verified in high-fidelity nonlinear simulations

Multi-Layered Clustering for Power Consumption Profiling in Smart Grids

Open access publicationSmart Grids (SGs) have many advantages over traditional power grids as they enhance the way electricity is generated, distributed, and consumed by adopting advanced sensing, communication and control functionalities that depend on power consumption profiles of consumers. Clustering algorithms (e.g., centralized clustering) are used for profiling individual’s power consumption. Due to the distributed nature and ever growing size of SGs, it is predicted that massive amounts of data will be created. However, conventional clustering algorithms neither efficient enough nor scalable enough to deal with such amount of data. In addition, the cost for transferring and analyzing large amounts of data is expensive high both computationally and communicationally. This paper thus proposes a power consumption profiling model based on two levels of clustering. At the first level, local power consumption profiles are derived, which are then used by the second level in order to create a global power consumption profile. The followed approach reduces the communication and computation complexity of the proposed two level model and improves the privacy of consumers. We point out that having good knowledge of the local power profiles leads to more effective prediction model and cost-effective power pricing scheme, especially in a heterogeneous grid topology. In addition, the correlations between the local and global profiles can be used to localize/identify power consumption outliers. Simulation results illustrate that the proposed model is effective in reducing the computational complexity without much affecting its accuracy. The reduction in computational complexity is about 52% and the reduction in the communicational complexity is about 95% when compared to the centralized clustering approach

Unsupervised Holistic Image Generation from Key Local Patches

We introduce a new problem of generating an image based on a small number of key local patches without any geometric prior. In this work, key local patches are defined as informative regions of the target object or scene. This is a challenging problem since it requires generating realistic images and predicting locations of parts at the same time. We construct adversarial networks to tackle this problem. A generator network generates a fake image as well as a mask based on the encoder-decoder framework. On the other hand, a discriminator network aims to detect fake images. The network is trained with three losses to consider spatial, appearance, and adversarial information. The spatial loss determines whether the locations of predicted parts are correct. Input patches are restored in the output image without much modification due to the appearance loss. The adversarial loss ensures output images are realistic. The proposed network is trained without supervisory signals since no labels of key parts are required. Experimental results on six datasets demonstrate that the proposed algorithm performs favorably on challenging objects and scenes.Comment: 16 page

Electroweak phase transition in a nonminimal supersymmetric model

The Higgs potential of the minimal nonminimal supersymmetric standard model (MNMSSM) is investigated within the context of electroweak phase transition. We investigate the allowed parameter space yielding correct electroweak phase transitoin employing a high temperature approximation. We devote to phenomenological consequences for the Higgs sector of the MNMSSM for electron-positron colliders. It is observed that a future $e^+ e^-$ linear collider with $\sqrt{s} = 1000$ GeV will be able to test the model with regard to electroweak baryogenesis.Comment: 28 pages, 5 tables, 12 figure

Multi-Cluster Reconfiguration with Traffic Prediction in Hyper-Flex-LION Architecture

We study the performance of Hyper-Flex-LION optical interconnect architecture under dynamic traffic with traffic-prediction-aided multi-cluster reconfiguration. The simulation results show a 17.2% latency improvement and 36.9% packet loss reduction as compared to a fixed topology