Wind turbine speed control of a contactless piezoelectric wind energy harvester

ABSTRACT

Wind turbine control is an important task to make the electricity generation secure in terms of energy demand and machine safety. It also yields to control the desired power level and optimized energy because of the assignment of turbine speed. The contactless piezoelectric wind energy harvester (CPWEH) used in this study has three piezoelectric layers located around the shaft with 120 degrees apart and they are buckled by the magnetic force without any physical contact. The superiority of this device is to generate energy for low wind speeds such as 1.5 m/s. However, for high speeds, high total harmonic distortions (THDs) govern the waveforms, thus controlling the turbine speed becomes necessary for optimizing the output power. Encouraged by this, a small low inertia dc generator is coupled with the wind turbine, and the generator terminals are connected to a resistor through a power switch to generate a braking torque that opposes to wind speed direction. By controlling the switch properly, turbine speed is ensured to remain within a certain band, which accordingly prevents the turbine from rotating very fast at damaging wind speeds. Several experiments are performed on the developed CPWEH with/without the presented control scheme which prove the existence of promising performance of our proposal.     

A comparative study on structural,morphological and photocatalytic properties of anodically grown ZnO nanowires under varying parameters

Journal of Materials Science: Materials in Electronics - In this study, zinc oxide (ZnO) nanowires (NWs) were successfully produced on Zn plates through electrochemical anodization in potassium...     

Electrochemical copper (II) sensor based on chitosan covered gold nanoparticles

This study outlines a new sensing platform based on glassy carbon electrodes modified by gold nanoparticles (AuNPs) for the determination of heavy metal. A glassy carbon electrode was modified by chitosan stabilized AuNPs. AuNPs were prepared by reducing gold salt with a polysaccharide chitosan. Here, chitosan acted as a reducing/stabilizing agent. The AuNPs were characterized with UV–Visible absorption spectroscopy, Fourier transform infrared spectroscopy, and transmission electron microscopy. Chitosan covered AuNPs were immobilized on the glassy carbon electrode for the determination of Cu (II) in aqueous solutions. The electrochemical determination of Cu (II) ions was performed using the differential pulse voltammetry technique. Some parameters for Cu (II) determination, such as pH, preconcentration time and electrolysis potential of Cu (II), were optimized. The detection limit was calculated as 5 × 10^?9 mol L^?1 by means of the 3:1 current-to-noise ratio. The interference of Cr(III), Fe(II), Ni(II), Pb(II), Mg(II), Zn(II), Ba(II) ions was investigated and showed a negligible effect on the electrode response. Recovery studies were carried out using tap water.     

Blends of poly(3‐hydroxybutyrate) with poly(β‐alanine) and its derivatives

Nanofibers and films of poly(3‐hydroxybutyrate) (PHB)/nylon 3 [poly(β‐alanine) (N3)], PHB/poly(α‐methyl‐β‐alanine) (2mN3), and PHB/poly(β‐methyl‐β‐alanine) (3mN3) blends were prepared by electrospinning and film‐casting techniques, respectively. The miscibility of the blends was studied by Fourier transform infrared spectrometry, differential scanning calorimetry, thermogravimetric analysis, and X‐ray diffraction (XRD). The electrospinnability of the blends was studied by scanning electron microscopy. Some characteristic IR absorption bands of the components in the blends shifted gradually with changes in the compositions. The melting temperature and decomposition temperature of PHB decreased gradually with increasing fractions of N3, 2mN3, and 3mN3. The XRD spectra of all of the blends exhibited peaks with lower intensities compared to those of the neat species. The suppression of PHB crystallinity in the blends after blending was attributed to the disruption of its crystal lattice and the prevention of recrystallization of each component by means of other components and segmental interactions between the components in the amorphous phase. Thermal, spectroscopic, and optical analyses of the polymer blends revealed that the polymers were miscible with good compatibility, and this could have improved the scaffold properties of PHB. © 2014 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2014 , 131, 40484.     

振动荷载下级配碎石颗粒运动及其能量特征试验研究

大空隙级配碎石因其良好的透(排)水性能逐渐用作“海绵城市”路面结构的基层填料,但振动荷载作用下填料颗粒在重新排列过程中的运动姿态变化以及能量状态空间分布规律仍不明确。文章基于颗粒堆积理论设计了不同级配的碎石填料,开展不同激振参数组合下的室内新型平板振动压实试验,在试样内部不同位置处放置新型智能颗粒传感器(SmartRock)实时监测压实过程中颗粒的运动姿态变化,由颗粒加速度响应分析填料内部运动能量的时空演变规律,进而提出基于颗粒运动和能量分布的填料压实质量评价新指标。研究结果表明,级配碎石填料振动压实过程可明显分为两个不同阶段：第一阶段大部分能量耗散于碎石颗粒的竖向运动及空隙的压缩,占主导的颗粒竖向运动未形成致密的骨架结构;第二阶段颗粒主要发生水平面内的平动以及竖直面内的滚动,颗粒的长轴取向逐渐趋近于“平躺”状态,大部分能量耗散于颗粒间空隙的填充,颗粒逐渐互相紧密咬合嵌挤并形成稳定的骨架结构。试样中上部颗粒的运动指标可较好地评判压实状态,当颗粒水平向运动能量从逐渐增大过渡到逐渐减小至几乎没有任何能量分布但竖向能量分布突增时,表明试样已达到较优的压实状态,新的颗粒运动和能量指标可为连续压...     

Effects of Electrospinning Parameters on Gelatin/Poly(ϵ‐Caprolactone) Nanofiber Diameter

An electrospinning procedure was carried out to fabricate gelatin/poly(?‐caprolactone) (Gt/PCL) nanofibers. Response surface methodology based on a three‐level, four‐variable Box‐Behnken design technique was used to model the resultant diameter of the as‐spun nanofibers. A second‐order model was obtained to describe the relationship between the fiber diameter and the electrospinning parameters, namely Gt concentration, PCL concentration, content of acetic acid in the overall solvent, and content of Gt solution in the blend solution. The individual and the interactive effects of these parameters on the fiber diameter were determined. Validation experiments verified the accuracy of the model which provided a simple and effective method for fabricating nanofibers with a controllable and predictable fiber diameter.     

Analysis of cross-country variations in the depth of European mortgage markets

To date, quantitative analysis on the depth of mortgage markets across a broad set of countries has been very limited. This paper uses a rich and balanced data set on 31 European countries to investigate the cross-country variations in the depth of mortgage markets during the period 2005–2012. The present paper might be accepted as the updated and enriched version of existing research for the European region in terms of the coverage of countries, historical data and the empirical analyses. Our empirical findings reveal that developed countries have sizeable residential mortgage markets and this is mainly associated with higher urbanization rates and stronger legal rights. One of the most notable results of this study is that, statistical significance of explanatory variables in modeling the depth of the mortgage markets depends heavily on both the variables, countries (regions) included in the models and the regression methodology used. Hence, we argue that strong conclusions based on such analyses should be avoided and the findings of previous research on the variations of the depth of mortgage markets should be carefully evaluated.     

Performance analysis of the tracking of the global extreme on multimodal patterns using the Asymptotic Perturbed Extremum Seeking Control scheme

This paper presents the capability of the Asymptotic Perturbed Extremum Seeking Control (aPESC) scheme to track the Global Extreme on multimodal patterns. The multimodal patterns are simulated based on power characteristics generated by a photovoltaic (PV) array under Partial Shading Conditions (PSCs). The aPESC scheme is tested to evaluate the performance of locating, searching and tracking of the Global Maximum Power Point (GMPP). The following performance indicators such as the searching resolution, tracking accuracy, tracking efficiency, and tracking speed are used to compare the performance of the GMPP tracking (GMPPT) algorithms. The aPESCH1 scheme proposed has been implemented in MATLAB/Simulink package to evaluate the performance indicators mentioned above. The results prove that the proposed aPESCH1 scheme is effective and simple to be implemented.     

Artificial neural network investigation of hardness and fracture toughness of hydroxylapatite

Hardness and fracture toughness of hydroxylapatite were investigated by artificial neural network (ANN). Hardness and fracture toughness of hydroxylapatite were predicted by using its sintering temperature, sintering time, relative density, and grain size with ANN. It was found that prediction results of its hardness and fracture toughness closely matched with the experimental results.