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A study on bubble growth mechanisms and underlying physical phenomena of flow boiling in silicon nanowire (SiNW) microchannels has been performed and compared these results with plainwall microchannels. A new approach in studying bubble dynamics and forces acting on liquid–vapor (L–V) interface of growing bubble has been proposed based on theoretical, experimental and visual studies. Bubble size, liquid film thickness, interfacial properties are measured and L–V interfaces are detected from high speed visualization data and results are analyzed by vision-based approach. Force analysis during instantaneous bubble growth from bubble nucleation to formation of annular flow regime has been performed for both the SiNW and plainwall microchannel configurations. Results from force analysis show the dominance of surface tension at L–V interface of growing bubble which resulted higher heat transfer contact area, lower thermal resistance and higher thin film evaporation. Whereas, inertia force is dominant at L–V interface of fully grown bubble and it helps in bubble removal process and rewetting before flow reversal. Significant differences between SiNW and plainwall microchannels have been observed in bubble growth mechanism, heat transfer mode and forces acting on L–V interface. [ABSTRACT FROM AUTHOR]

Abstract: Real-time simulation and rapid prototyping of power electronics, critical loads, and control systems have prompted recent interest in accurate electrical terminal models of photovoltaic (PV) panels and array systems. Advancement in computing technologies, such as parallel computing and digital signal processing techniques for real-time simulations have allowed the prototyping of novel apparatus to be investigated in a virtual system under a wide range of realistic conditions repeatedly, safely, and economically. This paper accesses numerical iteration methods, selects appropriate techniques, and combines them with model construction methods well suited for boosting the computational speed of an electro-thermal dynamic model of a PV panel. The target computational engine is a parallel processor based real-time simulator to be used in a power hardware-in-the-loop (PHIL) application. Significant improvements resulting from the proposed modeling approach in computation time and numerical convergence speed are verified using experimental results for the target PV panel using Opal-RT’s RT-Lab Matlab/Simulink based real-time engineering simulator. [Copyright &y& Elsevier]

• Bubble dynamics in one single confined microchannel was experimentally investigated. • The effects of hydraulic diameter (D h) of channel, flow rate and heat flux on bubble dynamics are discussed. • The velocity and acceleration of L- V interface were estimated through the analysis of recorded videos using vision-based technique. • The interfacial heat transfer (Nu c) changes with re b during bubble growth and bubble shrinking. • An analysis of energy distributions by bubble dynamics is conducted, heat flux through interface counts over 96% of total input power. Bubble dynamics are fundamental to understand boiling heat transfer mechanism at microscale. In this study, bubble dynamics in one single confined microchannel was experimentally investigated through vision-assisted technique. Experimental studies were performed to understand the effects of hydraulic diameter (D h) of channel, flow rate and heat flux on bubble dynamics, which highly affect the boiling heat transfer performance. First of all, experimental results show that D h has a vital effect on the volume change rate of confined bubble, which can be used to compute the heat flux transported by single bubble. The liquid-vapor (L- V) interfaces were tracked by non-rigid image registration and the velocity and acceleration of L- V interface were estimated through the analysis of recorded videos using vision-based technique. To quantitatively evaluate the impact of bubble dynamics, transient heat transfer rates were presented at different flow rates. Furthermore, the interfacial heat transfer (Nu c) influenced by bubble dynamics was evaluated. Nu c changes with Re b during bubble growth and bubble shrinking. Finally, an analysis of energy distributions by bubble dynamics is conducted. Compared to energy transported by bubble and kinetic energy of bubble, heat flux through interface is significant, dissipating over 96% of total input power. [ABSTRACT FROM AUTHOR]

Identifying Photovoltaic (PV) array faults is crucial for improving the service life and consolidating system performance overall. The strategies based on the supervised Machine Learning (ML) approach represent an attractive solution to identify the PV array faults. However, attainable labeled data to train supervised ML algorithms present challenges in practice. Therefore, this work introduces a novel strategy that employs an ensemble learning concept in conjunction with a semi-supervised learning approach based on a self-training philosophy to realize the faults diagnosis of an arc, line-to-line, power tracker unit, open-circuit, and partial shading, under different of aspects which can directly be impacting faults behavior. The developed ensemble learning paradigm comprises multiple merged ML models, which enhances the overall diagnostics performance. Moreover, it works to alleviate the resource-intensive process, which, in turn, contributes to overcoming standard supervised ML algorithms limitations. To ensure high fault diagnostic capabilities through the proposed fault identification strategy, the principal component analysis is introduced to mitigate the correlation between variables. Moreover, the Bayesian optimization method is adopted to control the behaviors of training ML algorithms, providing models with better characterization results. The merits of the proposed strategy are corroborated through simulation and experimental case studies. [Display omitted] • A novel strategy for effective identification of faults in PV arrays. • The strategy takes into consideration of the minimum number of sensors. • The strategy works to alleviate the resource-intensive process. • The strategy can identify the faults under harsh environmental scenarios. • Strategy effectiveness has been validated by simulation and experimental results. [ABSTRACT FROM AUTHOR]

Superparamagnetic iron oxide nanoparticles (SPION) Fe 3 O 4 nanoparticles were prepared using different approaches: co-precipitation and sonochemical methods. This article is a comparative study on how different synthesis techniques greatly affect the magnetic properties and heating efficiency of such nanomaterial. Another important issue addressed here is the correlation between microstructure, colloidal stability, magnetization and specific absorption rate (SAR) of the nanoparticles. The results reveal that the sonochemical method for polyethylene glycol (PEGylated) Fe 3 O 4 with size 5 nm leads to pseudo single domain with smallest loop area. Additionally, large SAR values are obtained within 10–15 min using low magnetic field. [ABSTRACT FROM AUTHOR]

All available Pulse Width Modulation (PWM) techniques employed to different Matrix Converter (MC) topologies generally generate switching Common-Mode Voltage (CMV), which introduces numerous operational concerns in electric drives. Although a body of research for the three-phase case has been undertaken to either reduce or eliminate CMV, corresponding discussions for multiphase MC remain scarce. Interestingly enough, the three- to five-phase (3 × 5) Indirect MC (IMC) is a potential converter topology for five-phase based high power motor drives. In this paper, the different available switching states of a 3 × 5 IMC are classified based on their corresponding CMV levels. Accordingly, two different Space Vector Modulation (SVM) techniques are proposed, which can successfully reduce the peak CMV by 28% and 48%, respectively, when compared with the conventional modulation strategy, while the same maximum Voltage Transfer Ratio (VTR) is preserved. Although the 28% reduction has been alternatively achieved in literature based on carrier-based PWM, the 48% reduction attained in this study represents the maximum achievable reduction for this MC topology. The main concept is firstly introduced; then, both simulations and experiments are used to validate the proposed schemes. [ABSTRACT FROM AUTHOR]

Employing the LCL passive filter in inverter-based distributed generation to ensure high quality power delivery comes at the expense of poor performance due to the resonance phenomenon. Literature elucidated several active approaches to mitigate this phenomenon. This paper proposes a sensorless active damping technique that is able to restrain the resonant current component through the estimation of the filter capacitor current using the Kalman filter. The Kalman filter is able to improve the quality of the estimated variables in noisy environments accompanied with measurements and model uncertainties. The effect of LCL filter parameter mismatch on the performance of the Kalman filter is assessed. Stability and convergence analyses are also conducted. An effective tuning method for the grid current controller employing a proportional-resonant controller is adopted. Experimental evaluations were conducted to validate the proposed control strategy. [ABSTRACT FROM AUTHOR]

This article has been retracted: please see Elsevier Policy on Article Withdrawal (https://www.elsevier.com/about/our-business/policies/article-withdrawal). This article has been retracted at the request of Editor-in-Chief in consultation with the authors. The article duplicates multiple figures that had previously appeared in Desalination, 453 (2019) 22-36 without proper citation. (Box 6) [ABSTRACT FROM AUTHOR]