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Breakdown (BD) voltage is significant in high-voltage power electric machines. Currently, BD voltages are mainly predicted by the semi-empirical formula in strongly inhomogeneous electric fields. However, the equation could not be applied for electrodes with weakly inhomogeneous electric fields. In this paper, positive lightning impulse BD voltages are predicted in various sphere-to-plane air gaps using forms of machine learning such as support vector regression (SVR), Bayesian regression (BR) and multilayer perceptron (MLP). Unlike previous studies, a method is also proposed by introducing streamer propagation characteristics as new features and by removing electric field gradients as unnecessary features to find out how to reduce the feature dimension. The streamer propagation characteristics are suggested to reflect the possibility of a discharge process between electrodes. Predicted voltages from machine learning algorithms are compared with the experimental results and calculated voltages from the semi-empirical formula. Firstly, the predictions from each model agreed well with the datasets. New features were observed to be applied for machine learning algorithms and to be as important as known electrostatic features before discharge. Secondly, predicted BD voltages were more accurate than calculated voltages from the semi-empirical equation in strongly inhomogeneous electric fields. Predictions from each model also agreed well with the experimental results in weakly inhomogeneous electric fields. The prediction accuracy of SVR was better than those of BR and MLP. Machine learning algorithms were also shown to be applied for electrodes with a wide range of inhomogeneities, unlike a semi-empirical method. We expect that the suggested features and machine learning algorithms can be used for accurately calculating BD voltages. [ABSTRACT FROM AUTHOR]

Featured Application: The work uses a patch-based inpainting method that is capable of filling the missing areas or removing unwanted objects in a digital image. Patch-based image inpainting methods iteratively fill the missing region via searching the best sample patch from the source region. However, most of the existing approaches basically use the fixed size of patch regardless of content features nearby, which may lead to inpainting defects. Also, global match is needed for searching the best sample patch, but only to fill one target patch in each iteration, resulting in low efficiency. To handle the issues above, we first evaluate the nonuniformity in an image, by which the patch size is adaptively determined. Moreover, we divide the source region into multiple non-overlapping subregions with different nonuniformity levels, and the patch match proceeds in every subregion, respectively. This strategy not only saves the match time for single target patch, but also reduces the mismatch, and enables the simultaneous filling of multiple target patches in a single iteration. Experimental results show that in comparison to previous patch-based works, our method has achieved further improvement both in quality and efficiency. We believe our method could provide a new way for patch match with better accuracy and efficiency in image inpainting tasks. [ABSTRACT FROM AUTHOR]

As a critical parameter of the steady uniform friction model, the roughness coefficient changes with flow unsteadiness in flood events; i.e., the flow conditions of the stream segment significantly affect the flow resistance. In this study, a modified formula was established to improve the unsteady friction simulation; ten terms relating to the first- and second-order time and space partial derivatives of hydraulic parameters were selected as additional terms. The results of a hydraulic experiment show that the hysteresis between flow depth and mean cross-sectional velocity cannot be neglected in unsteady flows that disturb the performance of a steady uniform friction model. Six terms have a strong correlation with objective friction. Further, three of them have a small variance in correlation coefficient. Then, the composition of the proposed formula was determined. The results show that adding too many additional terms provides better performance in the calibration phase, yet reduces the accuracy of the validation phase because of an overfitting phenomenon. The optimal number of additional terms is three, and the established formula can improve the unsteady friction simulation. [ABSTRACT FROM AUTHOR]

In this paper, we propose a new scene-based nonuniformity correction technique for infrared focal plane arrays. Our work is based on the use of two well-known scene-based methods, namely, adaptive and interframe registration-based exploiting pure translation motion model between frames. The two approaches have their benefits and drawbacks, which make them extremely effective in certain conditions and not adapted for others. Following on that, we developed a method robust to various conditions, which may slow or affect the correction process by elaborating a decision criterion that adapts the process to the most effective technique to ensure fast and reliable correction. In addition to that, problems such as bad pixels and ghosting artifacts are also dealt with to enhance the overall quality of the correction. The performance of the proposed technique is investigated and compared to the two state-of-the-art techniques cited above. [ABSTRACT FROM AUTHOR]

Pultruded fiber-reinforced polymer composites are susceptible to microstructural nonuniformity such as variability in fiber volume fraction ( V f ), which can have a profound effect on process-induced residual stress. Until now, this effect of non-uniform V f distribution has been hardly addressed in the process models. In the present study, we characterized the V f distribution and accompanying nonuniformity in a unidirectional fiber-reinforced pultruded profile using optical light microscopy. The identified nonuniformity in V f was subsequently implemented in a mesoscale thermal–chemical–mechanical process model, developed explicitly for the pultrusion process. In our process model, the constitutive material behavior was defined locally with respect to the corresponding fiber volume fraction value in different-sized representative volume elements. The effect of nonuniformity on the temperature and cure degree evolution, and residual stress was analyzed in depth. The results show that the nonuniformity in fiber volume fraction across the cross-section increased the absolute magnitude of the predicted residual stress, leading to a more scattered residual stress distribution. The observed V f gradient promotes tensile residual stress at the core and compressive residual stress at the outer regions. Consequently, it is concluded that it is essential to take the effects of nonuniformity in fiber distribution into account for residual stress estimations, and the proposed numerical framework was found to be an efficient tool to study this aspect. [ABSTRACT FROM AUTHOR]