Performance Investigation of Three Combined Airfoils Bladed Small Scale Horizontal Axis wind Turbine by BEM and CFD Analysis

The present work is based on the comparative study between “Blade-Element- Momentum” (BEM) analysis and “Computational-Fluid-Dynamics” (CFD) analysis of small-scale horizontal axis wind turbine blade. In this study, the pitch is considered as fixed and rotor speed is variable. Firstly, the aerodynamic characteristics of three different specialized airfoils were analyzed to get optimum design parameters of wind turbine blade. Then BEM was performed with the application of the open source wind turbine design and performance computation software Q-Blade v0.6. After that, CFD simulation was done by Ansys CFX software. Here, k-ω “Shear-Stress-Transport” (SST) model was conducted for three-dimensional visualization of turbine performance. However, the best coefficient of performance was observed at 6o angle of attack. At this angle of attack, in the case of BEM, the highest coefficient of performance was 0.47 whereby CFD analysis, it was 0.43. Both studies showed good performance prediction which was a positive step to accelerate the continuous revolution in wind energy sector.

An Analysis on Position Estimation, Drifting and Accumulated Error Accuracy during 3D Tracking in Electronic Handheld Devices

This work focuses on a brief discussion of new concepts of using smartphone sensors for 3D painting in virtual or augmented reality. Motivation of this research comes from the idea of using different types of sensors which exist in our smartphones such as accelerometer, gyroscope, magnetometer etc. to track the position for painting in virtual reality, like Google Tilt Brush, but cost effectively. Research studies till date on estimating position and localization and tracking have been thoroughly reviewed to find the appropriate algorithm which will provide accurate result with minimum drift error. Sensor fusion, Inertial Measurement Unit (IMU), MEMS inertial sensor, Kalman filter based global translational localization systems are studied. It is observed, prevailing approaches consist issues such as stability, random bias drift, noisy acceleration output, position estimation error, robustness or accuracy, cost effectiveness etc. Moreover, issues with motions that do not follow laws of physics, bandwidth, restrictive nature of assumptions, scale optimization for large space are noticed as well. Advantages of such smartphone sensor based position estimation approaches include, less memory demand, very fast operation, making them well suited for real time problems and embedded systems. Being independent of the size of the system, they can work effectively for high dimensional systems as well. Through study of these approaches it is observed, extended Kalman filter gives the highest accuracy with reduced requirement of excess hardware during tracking. It renders better and faster result when used in accelerometer sensor. With the aid of various software, error accuracy can be increased further as well.

Structural Damage Localization by Linear Technique of Acoustic Emission

Linear source location of acoustic emission (AE) technique has been applied in the present paper for finding the source of material damage under fatigue loading. A plate type structure of ductile cast iron has been used to undergo fatigue damage in a servopulsing machine in the experiment. AE sensors were attached to the specimen for getting the time delay of AE signal propagations through the specimen. After receiving the time delay data of AE signals due to the damage initiation in the material for the provided fatigue loads, linear source location algorithm has been applied and the crack positions are identified. Before applying the technique, a series of pencil lead breaks (PLBs) tests have been conducted upon a ductile cast iron plate of same dimension for verifying the applied algorithm. According to the PLBs varification, the failure location of ductile cast iron (pearlite type) due to the fatigue loading has been characterized. In both experiments, the active ability of the proposed technique for source location of structural damage has been identified clearly and successfully.

Optical wavelength meter with machine learning enhanced precision

A photonic implementation of a wavelength meter typically applies an interferometer to measure the frequencydependent phase shift provided by an optical delay line.This work shows that the information to be retrieved is encoded by a vector restricted to a circular cone within a 3D Cartesian object space.The measured data belong to the image of the object space under a linear orthogonal map.Component impairments result in broken orthogonal symmetry,but the mapping remains linear.The circular cone is retained as the object space,which suggests that the conventional conic section fitting for the wavelength meter application is a premature reduction of the object space from R^(3)to R^(2).The inverse map,constructed by a learning algorithm,compensates impairments such as source intensity fluctuation and errors in delay time,coupler transmission,and photoreceiver sensitivity while being robust to noise.The simple algorithm does not require initial estimates for all parameters except for a broad bracket of the delay;further,weak nonlinearity introduced by uncertain delay can be corrected by a robust golden search algorithm.The phase-retrieval process is invariant to source power and its fluctuation.Simulations demonstrate that,to the extent that the ten parameters of the interferometer model capture all significant impairments,a precision limited only by the level of random noise is attainable.Applied to measured data collected from a fabricated Si_(3)N_(4)wavelength meter,greater than an order of magnitude improvement in precision compared with the conventional method is achieved.

Structural, Dielectric, and Magnetic Properties of Ba-Doped Multiferroic Bismuth Ferrite

The main focus of the research was to correlate the microstructure with dielectric and magnetic properties of Bi1-xBaxFeO3 samples. Bi1-xBaxFeO3 samples（x = 0.1, 0.2 and 0.3） were synthesized by the conventional solid-state reaction method using nano-powders of Bi2O3, Fe2O3, and BaCO3. Thereafter, field emission scanning electron microscope and X-ray diffraction（XRD） techniques were used to examine the structure and phase of the samples. Phase analysis by XRD indicated that the single-phase perovskite structure was formed with possible increment in lattice parameter with increasing Ba doping. Complex permeability（u＇iand u＇＇i） measured using impedance analyzer confirmed the increase in magnetic property with increasing Ba doping. Finally, dielectric constant（k） was analyzed as a function of temperature at different frequencies. Dielectric constant as high as 2900 was attained in this research for Bi0.8Ba0.2FeO3 sample due to reduction in leakage current at this composition.