Search Results (27)

This work investigates the synthesis and characterization of Barium Titanate (BT) nanoparticles, which exhibit non-linear optical properties, with a focus on their potential application in biomedical imaging. BT nanoparticles are active in second harmonic generation (SHG), enabling deep tissue imaging with a high signal-to-noise ratio. A major objective of this study is to advance in the understanding of the interactions between these nanoparticles and model biological systems. To this end, monolayers of 1,2-dipalmitoyl-sn-glycerol-3-phosphocholine (DPPC) spread on aqueous sub-phase are employed as model bio-interfaces, and the effects of BT nanoparticles on their properties are investigated using physicochemical experimental techniques such as Langmuir trough and Dynamic Light Scattering, also in the presence of albumin, a representative serum protein. The results evidence nanoparticle incorporation into the lipid layer, affecting its phase behavior, as well as the spontaneous formation of protein coronas around NPs, which is further confirmed by super-resolution optical microscopy Full article

High-current-carrying capability with minimum thermal elongation is one of the key reasons for using high-temperature low-sag (HTLS) conductors in modern power systems. However, their higher operational temperature can significantly affect corona discharge characteristics. Corona is one of the key factors in transmission line design considerations. Corona discharge is the leading cause of audible noise, radio interference, and corona loss in power transmission systems. The influence of conductor temperature on corona discharge characteristics is investigated in this paper using experimental methods and computational simulations. A simulation framework has been developed in COMSOL Multiphysics using the physics of plasmas and electrostatics to simulate corona plasma dynamic behavior and electric field distribution. The results show that the conductor temperature enhances the ionization by electron impact, enhances the production of positive and negative ions, changes the electric field distribution, and increases the electron temperature. This analysis emphasizes that temperature-dependent conditions affect the inception and intensity of corona discharge. Additionally, an experimental model was developed to evaluate corona voltage–current characteristics under varying temperature conditions. The study presents both simulation results and a newly developed model for predicting corona current at high conductor temperatures. Full article

Cable termination is an important part of energy transmission in high-speed trains, and it is also a weak link in the insulation. It is important to determine the insulation status of cable terminals by the detection results of partial discharge signals, but the partial discharge signals in the field test circuit are mixed with a large amount of external corona interference, which affects the detection accuracy. This paper proposes a signal recognition model that incorporates Stockwell transform (ST) and 2DCNN, which in combination with wavelet noise reduction can achieve a high-precision classification effect for partial discharge and corona interference with an accuracy rate of up to 98.75%. By selecting the maximum energy moment in the ST matrix to correct the position of the time window during the recognition of long time series signals, the problem of corona interference being truncated by the time window and being misidentified as partial discharge is overcome, and the generalization ability of the model is enhanced. Experimental results show that the method has an excellent performance in separating partial discharge and corona interference in long time series signals. Full article

This work proposes a methodology for noise removal, separation, and classification of partial discharges in electrical system assets. Partial discharge analysis is an essential method for fault detection and evaluation of the operational conditions of high-voltage equipment. However, it faces several limitations in field measurements due to interference from radio signals, television transmissions, WiFi, corona signals, and multiple sources of partial discharges. To address these challenges, we propose the development of a clustering model to identify partial discharge sources and a classification model to identify the types of discharges. New features extracted from pulses are introduced to model the clustering and classification of discharge sources. The methodology is tested in the laboratory with controlled partial discharge sources, and field tests are conducted in substations to assess its practical applicability. The results of laboratory tests achieved an accuracy of 85% in classifying discharge sources. Field tests were performed in a substation of the Eletrobras group, allowing the identification of at least three potentially defective current transformers. Full article

Cable termination serves as a crucial carrier for high-speed train power transmission and a weak part of the cable insulation system. Partial discharge detection plays a significant role in evaluating insulation status. However, field testing signals are often contaminated by external corona interference, which affects detection accuracy. This paper proposes a classification model based on wavelet transform (WT) and deep belief network (DBN) to accurately and rapidly identify corona discharge in the partial discharge signals of vehicle-mounted cable terminals. The method utilizes wavelet transform for noise reduction, employing the sigmoid activation function and analyzing the impact of WT on DBN classification performance. Research indicates that this method can achieve an accuracy of over 89% even with limited training samples. Finally, the reliability of the proposed classification model is verified using measured mixed signals. Full article

The activity of the solar corona has a significant impact on all aspects of human life. People typically use images obtained from astronomical telescopes to observe coronal activities, among which the Atmospheric Imaging Assembly (AIA) of the Solar Dynamics Observatory (SDO) is particularly widely used. However, due to resolution limitations, we have begun to study the application of generative adversarial network super-resolution techniques to enhance the image data quality for a clearer observation of the fine structures and dynamic processes in the solar atmosphere, which improves the prediction accuracy of solar activities. We aligned SDO/AIA images with images from the High-Resolution Coronal Imager (Hi-C) to create a dataset. This research proposes a new super-resolution method named SAFCSRGAN, which includes a spatial attention module that incorporates channel information, allowing the network model to better capture the corona’s features. A Charbonnier loss function was introduced to enhance the perceptual quality of the super-resolution images. Compared to the original method using ESRGAN, our method achieved an 11.9% increase in Peak Signal-to-Noise Ratio (PSNR) and a 4.8% increase in Structural Similarity (SSIM). Additionally, we introduced two perceptual image quality assessment metrics, the Natural Image Quality Evaluator (NIQE) and Learned Perceptual Image Patch Similarity (LPIPS), which improved perceptual quality by 10.8% and 1.3%, respectively. Finally, our experiments demonstrated that our improved model surpasses other models in restoring the details of coronal images. Full article

Solar filaments are good tracers of space weather and magnetic flux ropes in the corona. Identifying and detecting filaments helps to forecast space weather and explore the solar magnetic field. Many automatic detection methods have been proposed to process the large number of observed images. Current methods face issues of unreliable dataset annotations and poor anti-interference capability. First, to address the issue of unreliable dataset annotations, we built a solar filament dataset using a manual annotation method. Second, we introduced Transformer into Convolutional Neural Networks. Transformer, with the ability to extract more global features, can help counter interference. In addition, there is large disparity in the size of solar filaments. Therefore, a multi-scale residual block is designed to extract features across various scales. Deformable large kernel attention and a res path are used to better integrate encoder and decoder information. Results show that this method outperforms the existing solar filament detection methods (improved U-Net and improved V-Net), achieving an F1 score of 91.19%. In particular, our results show lower interference by sunspots and background noise than existing methods. The ability to counter interference is improved. Full article

Measurement of lightning current plays a critical role in the field of atmospheric electricity. Traditionally, Rogowski coils or low-resistance shunts were employed for measuring lightning currents in the range from several amperes up to several hundreds of kilo-amperes, and high-value resistors were utilized for measuring corona discharge currents at sub-ampere levels. However, these approaches were not suitable for continuously recording the vast range of lightning currents. For this sake, we have developed a lightning current measurement system equipped with a shock-tolerant low-noise amplifier module. With the system installed on a tall tower, sub-ampere level currents just before the lightning initiation were observed for the first time. To confirm the authenticity of the recorded currents, the background noise of the measurement system and surrounding environment were identified, and a digital multi-frequency notch filter was proposed for de-noising. Results show that the system can achieve a current identification level of 50 mA even in complex electromagnetic environments, while having a measurement capability of 220 kA. Full article

The exploration of Uranus, a key archetype for ice giant planets and a gateway to understanding distant exoplanets, is acquiring increasing interest in recent years, especially after the Uranus Orbiter and Probe (UOP) mission has been prioritized in the Planetary Science Decadal Survey 2023–2032. This paper presents the results of numerical simulations aimed at providing experimental constraints on the parameterized post-Newtonian (PPN) parameter $\gamma$, a measure of space–time curvature in general relativity (GR), during the cruise phase of a spacecraft travelling to Uranus. Leveraging advanced radio tracking systems akin to those aboard the JUICE and BepiColombo missions, we explore the potential of solar conjunction experiments (SCEs) to refine current measurements of $\gamma$ by exploiting the spacecraft’s long journey in the outer Solar System. We discuss the anticipated enhancements over previous estimates, underscoring the prospect of detecting violations of GR. Our simulations predict that by using an advanced radio tracking system, it is possible to obtain an improvement in the estimation of $\gamma$ up to more than an order of magnitude with respect to the latest measurement performed by the Cassini–Huygens mission in 2002, contingent on the calibration capabilities against solar plasma noise. The results reveal that a number of SCEs during the mission can substantially strengthen the validation of GR. In tandem with fundamental physics tests, the use of radio links during SCEs presents a valuable opportunity to dissect the solar corona’s plasma dynamics, contributing to solar physics and space weather forecasting. This paper also enumerates methodologies to analyze electron density, localize plasma features, and deduce solar wind velocity, enriching the scientific yield of the experiments beyond the primary objective of testing GR during the cruise phase of a mission to Uranus. Full article

Quantifying an imaging modality’s ability to reproduce results is important for establishing its utility. In magnetic resonance spectroscopic imaging (MRSI), new acquisition protocols are regularly introduced which improve upon their precursors with respect to signal-to-noise ratio (SNR), total acquisition duration, and nominal voxel resolution. This study has quantified the within-subject and between-subject reproducibility of one such new protocol (reduced-field-of-view density-weighted concentric ring trajectory (rFOV-DW-CRT) MRSI) by calculating the coefficient of variance of data acquired from a test–retest experiment. The posterior cingulate cortex (PCC) and the right superior corona radiata (SCR) were selected as the regions of interest (ROIs) for grey matter (GM) and white matter (WM), respectively. CVs for between-subject and within-subject were consistently around or below 15% for Glx, tCho, and Myo-Ins, and below 5% for tNAA and tCr. Full article

Radio bursts provide important diagnostics of energetic phenomena of the Sun. In particular, bursts in decimetric and metric wavelengths probe the physical conditions and the energy release processes in the low corona as well as their association with heliospheric phenomena. The advent of spectral radio data with high time and high frequency resolution has provided a wealth of information on phenomena of short duration and narrow bandwidth. Of particular value are spectral data combined with imaging observations at specific frequencies. In this work we briefly review the results of a series of observations comprised from high-sensitivity, low-noise dynamic spectra obtained with the acousto-optic analyzer (SAO) of the ARTEMIS-IV/JLS solar radiospectrograph, in conjunction with high time-resolution images from the Nançay Radioheliograph (NRH). Our studies include fine structures embedded in type-IV burst continua (mostly narrow-band “spikes” and intermediate drift “fiber” bursts) and spike-like structures detected near the front of type-II bursts. The implications of the observational results to theoretical models are discussed. Full article

In recent years, the number of high-voltage transmission lines has sharply increased with the rapid development of modern industry. However, a corona discharge phenomenon often occurs on the exposed high-voltage transmission lines, leading to energy loss and noise pollution. Herein, we have proposed a facile spraying method to prepare a superhydrophobic and thermally conductive coating to restrain the corona discharge phenomenon of high-voltage transmission lines, with vinyl silicone oil and hydrogen silicone oil as the main materials and modified boron nitride (BN) as a thermal conductive filler. The obtained composite coating exhibited superhydrophobicity, with a high water contact angle of 162°. In addition, the coating also showed a good self-cleaning capability, non-adhesion capability, mechanical stability, and chemical stability. Owing to the construction of the thermally conductive pathways with BN, the thermal conductivity of the coating reached 1.05 W/m·K, which was beneficial to quickly dissipating the heat generated by the current heating effect. Moreover, the corona losses of the positive and negative electrodes under simulated rainy conditions were decreased by 7.43% and 8.05%, respectively. The findings of our work have provided a new strategy to effectively restrain the corona discharge phenomenon of transmission lines, showing great application potential in the field of high-voltage power networks. Full article

The audible noise generated by corona discharge has the N-type characteristic at the initial generation stage, and it is a typical shock wave. This shock wave usually only exists around the corona source with a tiny range, making it difficult to obtain its characteristics through experimental measurements. An electrosound-combined simulation of the corona discharge based on the shock wave theory was conducted, and the development process involving the corona discharge, shock wave, and sound wave was simulated. First, the corona was numerically simulated based on the 2D pin–plate axisymmetric hydrodynamic model. It was found that the plasma was mainly distributed near the axis of the corona field where the electric field changed violently, and the maximum value of the electric field appeared at the head of the discharge channel. Then, the plasma energy was equivalent to the explosive energy, and a plasma explosion shock model was established. It was found that the shock wave pressure had obvious positive and negative pressure zones, and the propagation velocity decays to the sound velocity gradually. Finally, the shock wave pressure derived by the explosion model was used as the acoustic source, and the acoustic wave propagation process was simulated. The simulated sound pressure waveform had the same characteristics as the relevant experimental measurement results, proving that the developed method possessed strong applicability and gave rise to a new angle for the simulation of corona-generated audible noise. Full article

The audible noise (AN) of DC transmission lines is a crucial factor affecting environmental assessment and electromagnetic design. In recent years, the public has paid increasing attention to the audible noise after the emergence of the HVDC technique. This paper emphatically reviewed the work investigating audible noise characteristics in both time and frequency domains, especially the correlation between sound and discharge. The proposed mechanisms of DC audible noise and the mitigating techniques are summarized, including the noise generation process, the physical models, the measurement method, and the mitigating technologies. It is found that the existing literature mainly focused on the prediction and characteristics of AN, the environmental factors which influence AN, and the methods to minimize AN emission. However, existing achievements still need to be improved to fully understand the mechanism of AN generation and solve the adaptability problem of AN prediction methods. The following aspects are valuable in future research: The correlation between audible noise and other corona effects will help solve the problem of difficulty in measuring audible noise in field condition; The corona discharge mechanism and weather resistance anti-corona coating when raindrops are attached to the surface of the transmission line, which will help guide the development and application of anti-corona coatings for the transmission line. Future research should also understand the mechanism of sound wave generation when considering the space charge effect. Full article

Audible noise (AN) has been the main concern in recent years when considering electromagnetic environmental impact in designing overhead lines (OHLs). Driven by the increased demand of high voltage direct current (HVDC) transmission lines, a novel corona cage experiment is built in association with an acoustic simulation using the finite element method (FEM). The characteristics of the acoustic wave propagation within the testing hall are analyzed using FEM, and the optimized locations for AN detection are determined. On the basis of complying with measurement standards, the location of the measurement is selected to be closer to the sound source and further away from the reflecting surface, to generate more accurate measurement results. In the designated test hall for this paper, the influence of refraction and reflection of sound waves is not obvious. The attenuation of sound waves below 4 kHz is negligible, while for higher frequencies such as 4 kHz and 8 kHz it is significant. Finally, FEM simulation is used to optimize the location for measurement microphones, and further experiments are carried out to verify its accuracy. Full article