bluuebunny/crossref_metadata_2025 huggingface dataset:
Cross polarization from dipolar-order under magic angle spinning: The ADRF-CPMAS NMR experiment
Authors: Wolf Tamar , Jayanthi Sundaresan , Lupulescu Adonis , Frydman Lucio
Published: December 2023

Techniques for enhancing the signals arising from low-γ, insensitive (I) nuclei are central to solid-state nuclear magnetic resonance. One of the leading and best-established methods to sensitize these unreceptive species is Hartmann–Hahn cross polarization (HH-CP), a polarization transfer mechanism often executed under MAS. Herein, we explore the possibility of utilizing the 1H dipolar order created via adiabatic demagnetization in the rotating frame (ADRF), to enhance the unreceptive spins under MAS. It is found that an efficient polarization transfer via ADRF-CPMAS is not only possible but can exceed, at least in some instances involving plastic crystals, the efficiency of an optimized HH-CPMAS transfer. The experiment requires low radiofrequency nutation fields on both the 1H- and the I-spin channels, and displays unusual matching conditions that are reminiscent of the zero- and double-quantum matching conditions arising under CPMAS, albeit centered at zero frequency and demanding the simultaneous involvement of several spins. The origin of these multi-spin transfer processes is analytically derived and numerically simulated in predictions that compare well with experimental 13C and 15N results collected on model compounds at different spinning speeds. These derivations start from descriptions that depart from traditional thermodynamic arguments, and treat instead the ADRF processes in static and spinning solids on the basis of coherent evolutions. The predictions of these analytical derivations are corroborated by numerical simulations. The effects of additional factors, including chemical shift anisotropies, J-couplings, and radiofrequency inhomogeneities, are also theoretically and experimentally explored.
Numerical simulation for axis switching of pulsating jet issued from rectangular nozzle at low Reynolds number
Authors: Yanaoka Hideki , Hatakeyama Yoshitomo
Published: December 2023

Axis switching of a jet ejected from a rectangular nozzle affects flow mixing characteristics. To elucidate such a mixing mechanism, the axis switching and vortex structure deformation should be investigated in detail. This study performed a numerical analysis of the axis switching of a pulsating jet ejected from a rectangular nozzle at a low Reynolds number. At all aspect ratios, a rectangular vortex ring similar to the shape of the nozzle cross-section is periodically shed downstream, and the side of the vortex ring deforms into a hairpin shape downstream. A vortex pair is generated inside the vortex ring downstream of the nozzle corner. When the aspect ratio is AR = 1.0, the vortex pair consists of symmetrical vortices, while as AR increases, the asymmetry of the vortex pair enlarges. At AR = 1.0, regeneration of a vortex ring occurs downstream. For AR = 2.0, alternately on the long and short sides of the nozzle, an upstream vortex ring overtakes a downstream vortex ring. Regardless of AR, downstream near the nozzle, as the vortex pair existing inside the vortex ring distorts the vortex ring, the positions of the side and corner of the vortex ring exchange, resulting in a 45° axis switching. For AR > 1.0, further downstream, the hairpin part of the vortex ring on the long side develops away from the jet center compared to the short side, causing a 90° axis switching. As a result, high turbulence occurs over a wide area, strengthening the mixing action. As AR increases, intensive interference between the vortex rings on the upstream and downstream sides diffuses the vortices downstream. Then, as turbulence by the diffused vortices widely occurs, the mixing effect is further strengthened.
Quantum computing perspective for electromagnetic wave propagation in cold magnetized plasmas
Authors: Koukoutsis Efstratios , Hizanidis Kyriakos , Vahala George , Soe Min , Vahala Linda , Ram Abhay K.
Published: December 2023

Electromagnetic waves are an inherent part of all plasmas—laboratory fusion plasmas or astrophysical plasmas. The conventional methods for studying properties of electromagnetic waves rely on discretization of Maxwell equations suitable for implementing on classical, present day, computers. The traditional methodology is not efficient for quantum computing implementation—a future computational source offering a tantalizing possibility of enormous speed up and a significant reduction in computational cost. This paper addresses two topics relevant to implementing Maxwell equations on a quantum computer. The first is on formulating a quantum Schrödinger representation of Maxwell equations for wave propagation in a cold, inhomogeneous, and magnetized plasma. This representation admits unitary, energy preserving, evolution and conveniently lends itself to appropriate discretization for a quantum computer. Riding on the coattails of these results, the second topic is on developing a sequence of unitary operators which form the basis for a qubit lattice algorithm (QLA). The QLA, suitable for quantum computers, can be implemented and tested on existing classical computers for accuracy as well as scaling of computational time with the number of available processors. In order to illustrate the QLA for Maxwell equations, results are presented from a time evolving, full wave simulation of propagation and scattering of an electromagnetic wave packet by non-dispersive dielectric medium localized in space.
Assessing the dynamics of CO adsorption on Cu(110) using the vdW-DF2 functional and artificial neural networks
Authors: Gonzalez Federico J. , Seminara Giulia N. , López Miranda I. , Lombardi Juan M. , Ramos Maximiliano , Tachino Carmen A. , Martínez Alejandra E. , Busnengo H. Fabio
Published: December 2023

In this work, we revisit the dynamics of carbon monoxide molecular chemisorption on Cu(110) by using quasi-classical trajectory calculations. The molecule–surface interaction is described through an atomistic neural network approach based on Density Functional Theory calculations using a nonlocal exchange–correlation (XC) functional that includes the effect of long-range dispersion forces: vdW-DF2 [Lee et al. Phys. Rev. B, 82, 081101 (2010)]. With this approach, we significantly improve the agreement with experiments with respect to a similar previous study based on a semi-local XC functional. In particular, we obtain excellent agreement with molecular beam experimental data concerning the dependence of the initial sticking probability on surface temperature and impact energy at normal incidence. For off-normal incidence, our results also reproduce two trends observed experimentally: (i) the preferential sticking for molecules impinging parallel to the [1̄10] direction compared to [001] and (ii) the change from positive to negative scaling as the impact energy increases. Nevertheless, understanding the origin of some remaining quantitative discrepancies with experiments requires further investigations.
XAF1 promotes colorectal cancer metastasis via VCP–RNF114–JUP axis
Authors: Xia Ji , Ma Ning , Shi Qian , Liu Qin-Cheng , Zhang Wei , Cao Hui-Jun , Wang Yi-Kang , Zheng Qian-Wen , Ni Qian-Zhi , Xu Sheng , Zhu Bing , Qiu Xiao-Song , Ding Kai , Huang Jing-Yi , Liang Xin , Chen Yu , Xiang Yan-Jun , Zhang Xi-Ran , Qiu Lin , Chen Wei , Xie Dong , Wang Xiang , Long Lingyun , Li Jing-Jing
Published: December 2023

Metastasis is the main cause of colorectal cancer (CRC)-related death, and the 5-year relative survival rate for CRC patients with distant metastasis is only 14%. X-linked inhibitor of apoptosis (XIAP)-associated factor 1 (XAF1) is a zinc-rich protein belonging to the interferon (IFN)-induced gene family. Here, we report a metastasis-promoting role of XAF1 in CRC by acting as a novel adaptor of valosin-containing protein (VCP). XAF1 facilitates VCP-mediated deubiquitination of the E3 ligase RING finger protein 114 (RNF114), which promotes K48-linked ubiquitination and subsequent degradation of junction plakoglobin (JUP). The XAF1–VCP–RNF114–JUP axis is critical for the migration and metastasis of CRC cells. Moreover, we observe correlations between the protein levels of XAF1, RNF114, and JUP in clinical samples. Collectively, our findings reveal an oncogenic function of XAF1 in mCRC and suggest that the XAF1–VCP–RNF114–JUP axis is a potential therapeutic target for CRC treatment.
Significant thermal rectification induced by phonon mismatch of functional groups in a single-molecule junction
Authors: Hua Renjie , Jiang Yunlei , Shi Lei , Liang Suxia , Zhang Chi , Song Yingru , Dong Ruo-Yu , Dong Yuan
Published: December 2023

Single-molecule junctions (SMJs) may bring exotic physical effects. In this work, a significant thermal rectification effect is observed in a cross-dimensional system, comprising a diamond, a single-molecule junction, and a carbon nanotube (CNT). The molecular dynamics simulations indicate that the interfacial thermal resistance varies with the direction of heat flow, the orientation of the crystal planes of the diamond, and the length of the CNT. We find that the thermal rectification ratio escalates with the length of the CNT, achieving a peak value of 730% with the CNT length of 200 nm. A detailed analysis of phonon vibrations suggests that the primary cause of thermal rectification is the mismatched vibrations between the biphenyl and carbonyl groups. This discovery may offer theoretical insights for both the experimental exploration and practical application of SMJs in efficient thermal management strategy for high power and highly integrated chips.
Surface defect detection of sawn timbers based on efficient multilevel feature integration
Authors: Zhu Yuhang , Xu Zhezhuang , Lin Ye , Chen Dan , Zheng Kunxin , Yuan Yazhou
Published: December 2023

Surface defect detection of sawn timber is a critical task to ensure the quality of wooden products. Current methods have challenges in considering detection accuracy and speed simultaneously, due to the complexity of defects and the massive length of sawn timbers. Specifically, there are scale variation, large intraclass difference and high interclass similarity in the defects, which reduce the detection accuracy. To overcome these challenges, we propose an efficient multilevel-feature integration network (EMINet) based on YOLOv5s. To obtain discriminative features of defects, the cross fusion module (CFM) is proposed to fully integrate the multilevel features of backbone. In the CFM, the local information aggregation is designed to enrich the detailed information of high-level features, and the global information aggregation is designed to enhance the semantic information of low-level features. Experimental results demonstrate that the proposed EMINet achieves better accuracy with fast speed compared with the state-of-the-art methods.
Unsupervised rolling bearing fault diagnosis method across working conditions based on multiscale convolutional neural network
Authors: Fu Haiyue , Yu Di , Zhan Changshu , Zhu Xiangzhen , Xie Zhijie
Published: December 2023

In practical engineering, the features of rolling bearing vibration signals often vary in distribution under different working conditions, and obtaining sample labels for target working conditions can be challenging. Therefore, a multi-scale depth subdomain adaptive convolutional neural network (MS-DSACNN) fault diagnosis method is proposed. The MS-DSACNN method is based on a multi-scale feature extraction method combined with an improved 1D-ConvNeXt architecture, which fuses low- and high-level features into multi-scale fault features. A channel attention mechanism is also introduced to adaptively assign weights to the fused multi-scale features. The local maximum mean discrepancy is constructed by extracting features and their corresponding source and pseudo-label inputs for the source and target working conditions, respectively, to construct the loss function for backpropagation. The MS-DSACNN model was evaluated in experiments with two different loads and one variable speed dataset. The experimental results indicate that MS-DSACNN has higher feature extraction capability and diagnostic accuracy than other unsupervised cross-condition fault diagnosis techniques. Additionally, the scenario where the signal captured by the sensor contains a considerable amount of noise in actual working conditions is considered.
A non-local total generalized variation regularization reconstruction method for sparse-view x-ray CT
Authors: Min Jiang , Tao Hongwei , Liu Xinglong , Cheng Kai
Published: December 2023

Sparse-view x-ray computed tomography (CT) reconstruction, employing total generalized variation (TGV), effectively mitigates the stepwise artifacts associated with total variation (TV) regularization while preserving structural features within transitional regions of the reconstructed image. Despite TGV surpassing TV in reconstruction quality, it neglects the non-local self-similarity prior, recognized for its efficacy in restoring details during CT reconstruction. This study introduces a non-local TGV (NLTGV) to address the limitation of TGV regularization method. Specifically, we propose an NLTGV-regularized method for sparse-view CT reconstruction, utilizing non-local high-order derivative information to maintain image features and non-local self-similarity for detail recovery. Owing to the non-differentiability of the NLTGV regularized, we employ an alternating direction method of multipliers optimization method, facilitating an efficient solution by decomposing the reconstruction model into sub-problems. The proposed method undergoes evaluation using both simulated and real-world projection data. Simulation and experimental results demonstrate the efficacy of the proposed approach in enhancing the quality of reconstructed images compared to other competitive variational reconstruction methods. In conclusion, the simultaneous incorporation of sparsity priors of high-order TV and non-local similarity proves advantageous for structural detail recovery in sparse-view CT reconstruction.
Study on the surface microtexture microscopic friction and wear characteristics of 304 stainless steel
Authors: Sun Jingting , Yuan Zewei , Tang Meiling , Zheng Peng , He Yan , Wang Ying
Published: December 2023

In order to reveal the friction behaviour and wear mechanism of nanoscale textures on the friction pair of 304 stainless steel, molecular dynamics simulations were firstly used to investigate the effects of smooth and textured surfaces on the tribological properties of the stainless steel substrate, and then focus on the effects of sliding velocity and depth on the surface morphology, mechanical force, friction coefficient, anisotropy, stress, temperature and dislocations of the textured substrate. The results show that the temperature, friction, stress, and dislocation line length of the textured surface are relatively smaller than those of the non-textured surface, and the textured surface has a smaller and more stable friction factor, which ultimately leads to a reduction of the friction factor by about 0.090. When the sliding distance is 120 Å, the number of defective atoms in the textured substrate is reduced by 12.9%, and its anisotropy is more stable. At the same indentation depth, the average friction coefficient, temperature and anisotropy increase significantly with increasing sliding velocity. The average friction coefficient is maximum when the sliding velocity is increased to 400 m s−1, with a value of about 0.833. The sliding friction, friction coefficient, dislocation line length, number of defect atoms, number of stacked atoms, stress, temperature and anisotropy factor increase with increasing depth of abrasive indentation. The average friction coefficient is minimum at a sliding depth of 4 Å, with a value of about 0.556, and the number of defective atoms is reduced by 83.2%. This indicates that textured surface treatment of 304 stainless steel and selection of appropriate sliding parameters can effectively reduce the wear during the friction process and improve the wear resistance of the substrate.
A denoising method based on deep learning for proton radiograph using energy resolved dose function
Authors: Sheng Cong , Ding Yu , Qi Yaping , Hu Man , Zhang Jianguang , Cui Xiangli , Zhang Yingying , Huo Wanli
Published: December 2023

Objective. Proton radiograph has been broadly applied in proton radiotherapy which is affected by scattered protons which result in the lower spatial resolution of proton radiographs than that of x-ray images. Traditional image denoising method may lead to the change of water equivalent path length (WEPL) resulting in the lower WEPL measurement accuracy. In this study, we proposed a new denoising method of proton radiographs based on energy resolved dose function curves. Approach. Firstly, the corresponding relationship between the distortion of WEPL characteristic curve, and energy and proportion of scattered protons was established. Then, to improve the accuracy of proton radiographs, deep learning technique was used to remove scattered protons and correct deviated WEPL values. Experiments on a calibration phantom to prove the effectiveness and feasibility of this method were performed. In addition, an anthropomorphic head phantom was selected to demonstrate the clinical relevance of this technology and the denoising effect was analyzed. Main results. The curves of WEPL profiles of proton radiographs became smoother and deviated WEPL values were corrected. For the calibration phantom proton radiograph, the average absolute error of WEPL values decreased from 2.23 to 1.72, the mean percentage difference of all materials of relative stopping power decreased from 1.24 to 0.39, and the average relative WEPL corrected due to the denoising process was 1.06%. In addition, WEPL values correcting were also observed on the proton radiograph for anthropomorphic head phantom due to this denoising process. Significance. The experiments showed that this new method was effective for proton radiograph denoising and had greater advantages than end-to-end image denoising methods, laying the foundation for the implementation of precise proton radiotherapy.
First-principles calculation of the structural, electronic and mechanical properties of β′ phase in Mg-RE binary systems
Authors: Fu Xuanran , Song Xiaolin , Zeng Ying , Peng Jinfang
Published: December 2023

Rare-earth magnesium alloys (Mg-RE) are gaining growing prominence across multiple industries due to their superior mechanical properties and enhanced formability compared to conventional magnesium alloys. β′ phase of Mg-RE alloys exhibits remarkable behavior in strengthening and enhancing corrosion resistance. However, the mechanical behaviors of some β′ phases themselves remain unexplored. Therefore, our objective is to identify the mechanical and thermomechanical properties of β′ phases. Herein, a theoretical study to investigate the structural, electronic, elastic and anisotropic properties of β′–Mg7RE phase from first-principle calculations is described. Besides, the melting temperature and Debye temperature of these intermetallic compounds are also predicted. The calculated results confirm the thermodynamic and mechanical stability of all β′–Mg7RE phases. Additionally, the calculated value of bulk modulus for all β′–Mg7RE phase exhibit similarity, with an approximate value of 38 GPa. The degree of anisotropy in the bulk modulus of the β′–Mg7RE phase is relatively lower compared to the shear and Young’s moduli. Among the β′ phase, β′–Mg7Lu exhibits the most pronounced anisotropy. Furthermore, the highest degree of Young’s and shear moduli anisotropy for all β′ phases are observed in the (001) plane. The value of the electron localization function between Mg and RE atoms ranges from 0.48 to 0.56. In more detail, the density of states (DOS) reveals that hybridization arises from strong interaction between the Mg–p states and RE–d states below the Fermi level. Indeed, the results will offer valuable insights into the influential factors on the mechanical properties of the β′ phase, contributing to a more comprehensive understanding of its performance and potential applications.
Influence of Tsallis q-entropy on occurrence scattering time in a nonextensive plasma
Authors: Lee Myoung-Jae , Ashikawa Naoko , Jung Young-Dae
Published: December 2023

The essence of Tsallis q-entropy on the occurrence scattering time (OST) process is derived for a nonextensive plasma. The semiclassical eikonal dissection and the nonextensive q-distribution function are used to derive the OST with variables of projectile energy, scattering angle, electron entropic index, ion entropic index, and impact parameter. Our calculations find that the OST advance in a nonextensive plasma decreases with the entropic index. We have seen that the Tsallis q-entropy on the OST advance grows up fast as the scattering angle increases. We also obtained that the nature of Tsallis q-entropy on the OST advance diminishes in forward scattering direction in a nonextensive plasma. Moreover, the authority of the electron q-entropy is found to be greater than the that of ion q-entropy in the cold electron plasma, i.e., when the electron temperature is lower than the ion temperature. However, if the ion temperature is lower than the electron temperature, the authority of the ion q-entropy is more momentous than that of the electron q-entropy.
An equation of state based on the scaling properties of vibrational spectra at high pressure
Authors: Roy Umesh C
Published: December 2023

Inter-atomic forces control vibrational properties and elastic moduli of a solid material. Based on first-principle calculations, it has been reported that, for elemental solids, the Debye frequency scales linearly with density to high accuracy. Combining this with other scaling properties of vibrational frequencies at high pressure, a new equation of state is presented. The proposed equation of state is tested against available experimental data for various kinds of solids at high pressure and room temperature. The quality of description of the compressional behavior of solids by our proposed equation of state is, for many cases, comparable to or better than that with the Vinet EOS.
Finite dimensional irreducible representations of Lie superalgebra D (2, 1; α)
Authors: Chen 陈 Xi 曦 , Yang 杨 Wen-Li 文力 , Ding 丁 Xiang-Mao 祥茂 , Zhang 张 Yao-Zhong 耀中
Published: December 2023

This paper focuses on the finite dimensional irreducible representations of Lie superalgebra D(2, 1; α). We explicitly construct the finite dimensional representations of the superalgebra D(2, 1; α) by using the shift operator and differential operator representations. Unlike ordinary Lie algebra representation, there are typical and atypical representations for most superalgebras. Therefore, its typical and atypical representation conditions are also given. Our results are expected to be useful for the construction of primary fields of the corresponding current superalgebra of D(2, 1; α).
Research on the Relationship between Vibration Noise and Magnetic Saturation of Magnetic Saturated Controllable Reactor Based on COMSOL
Authors: Zhang Yuzhu , Tian Mingxing
Published: December 2023

This article is based on a 2.2 kVar small magnetically saturated controllable reactor (MSCR) prototype and builds a three-dimensional three-field coupling model of its electromagnetic structure acoustics in the finite element simulation software COMSOL. The time-domain sound field distribution of MSCR under electromagnetic force and magnetostrictive effect is obtained through simulation, and DC bias is linearly added. The trend of changes in magnetic saturation and MSCR maximum sound pressure level are obtained, and finally, the relationship curve between MSCR maximum sound pressure level and its magnetic saturation is analyzed, which is similar to the magnetization curve. Taking the half-load working state as the knee point, this study provides a research idea for the design and monitoring of reactors based on the relationship between MSCR acoustics and the working state.
Transmission Line Fault Diagnosis Method Based on SDA-ISSA-XGBoost under Meteorological Factors
Authors: Zhang Kun
Published: December 2023

Transmission lines are directly exposed to the natural environment and are prone to failure due to meteorological factors. A novel approach for diagnosing transmission line faults under various meteorological conditions has been introduced. This method, known as SDA-ISSA-XGBoost, combines the power of Stacked Denoising Autoencoder (SDA), an improved Sparrow Search Algorithm (ISSA) enhanced with chaotic mapping sequences, adaptive weights, improved iterative local search, and a random differential mutation strategy, and eXtreme Gradient Boosting (XGBoost). The process begins with SDA, which extracts essential features from the initial meteorological data. Subsequently, ISSA is applied to optimize the parameters of the XGBoost model. This results in the ISSA-XGBoost fault diagnosis model. The performance of this model is compared to PSO-XGBoost and SSA-XGBoost. The experimental findings demonstrate that the ISSA-XGBoost model achieves an impressive fault diagnosis accuracy of 94.39%, surpassing both PSO-XGBoost and SSA-XGBoost by 6.54% and 3.74%, respectively.
Electromagnetic Wind-induced Vibration Energy Harvester with a Resonant Cavity
Authors: Xiong Lei , Gao Shiqiao , Jin Lei , Sun Yaoqiang
Published: December 2023

Wind energy, as the most widely distributed form of renewable energy, holds great significance in addressing the energy supply issue for micro-power electronic equipment. Therefore, this paper proposes an electromagnetic wind-induced vibration energy harvester with a resonant cavity (EWVEH). When the wind blows through the resonant cavity, the pressure inside the cavity increases, causing a change in the pressure distribution. The pressure on the lower surface of the elastic beam exceeds the pressure on the upper surface, leading to a pressure difference. When the pressure difference exceeds the damping force of the elastic beam, it will cause the beam to move, and then the vibration energy will be converted into electrical energy through electromagnetic conversion. The installation angle of the elastic beam and the size and position of the resonant cavity outlet will affect the fluid distribution in the resonant cavity and the vibration characteristics of the elastic beam. This, in turn, will change the output characteristics of the EWVEH. The simulation analysis and experimental research demonstrate that a smaller installation angle for the cantilever and a smaller outlet for the resonant cavity is advantageous for the EWVEH to obtain higher output power. Furthermore, the position of the air outlet also impacts the efficiency of the EWVEH. At a wind velocity of 14 m/s, the load voltage and power of the EWVEH are 39 mV and 101.4 μW, respectively.
Transformer-customer Relationship and Phase Identification Method of Low-voltage Distribution Networks Based on Critical Time Segments
Authors: Liu Jianfeng , Zang Wei , Lu Yan , Zhang Yu , Cong Rili
Published: December 2023

Accurate topology identification of low-voltage distribution networks is of great significance for intelligent and refined management of power grids. Currently, manual inspection is costly and inefficient. This paper proposes an automatic method for identifying the transformer-customer relationships and phase in low-voltage distribution networks based on voltage similarity and grey correlation degree of critical time segments. Firstly, the principle of identifying transformer-customer relationships based on voltage time series similarity is presented. Secondly, the criteria for judging similarity by using grey correlation are provided, as well as the method for processing long time series through critical time segments. Finally, the effectiveness and accuracy of the proposed method are verified through a practical case study in a certain area.
Failure Analysis of Electronic Current Transformer Air Chamber Basin Insulator Cracking in a 330 kV Substation
Authors: Zhang Zhaoyu , Zhou Yanke , Jiang Fei , Zhao Chaoyou , Zhou Yunfei
Published: December 2023

In operation, the combined electrical appliances in the substation leak, and the insulation basin breaks when the old insulation basin is replaced. By using the methods of macroscopic inspection, penetration detection, material analysis, and scanning electron microscopy, the failure analysis of the broken basin insulator of the combined electric apparatus is complete, and the process of crack generation and expansion is analyzed. The analysis results show that the reason for the fracture of the basin-type insulator is uneven force during fastening or disassembling, subjected to shear and bending stress. The crack source starts at the stress concentration part, that is, the root of the groove of the inner ring seal ring, and continues to expand, resulting in the final fracture of the basin-type insulator. The next step is to strengthen the daily control of the transportation process and installation process of the basin insulator.
Analysis of the Causes of Glass Insulator Self Explosion in ± 800 kV Transmission Lines
Authors: Zhang Suhui , Xie Jinpeng , Zhao Tongkun , Jiang Fei , Lv Yanting , Wu Jinhua
Published: December 2023

To study the self-explosion problem of a ± 800 kV glass insulator and conduct experimental detection on the self-explosion glass insulator, the reasons for the self-explosion were analyzed. Through macroscopic inspection, eccentricity calculation, microscopic morphology inspection, and other methods, it can be concluded that there are micro-cracks and stress concentration phenomena in the internal pores of the cement adhesive in the glass insulator, and there is an eccentricity phenomenon in the cement adhesive, glass, and steel cap in the glass insulator. Through simulation analysis under the coupling field of stress and temperature, it can be concluded that the overall stress concentration exists at the junction of the inner cement and steel foot adhesive. During operation, various stress concentrations cause glass insulators to self-explode. Finally, suggestions for improving the manufacturing process of insulators in operation in response to such faults are proposed to prevent similar faults from happening again and ensure the safe operation of the power grid.
Research on distribution network operation status evaluation technology based on new sensing measurement method
Authors: Dang Junpeng , Jiang Bo , Liu Chao , Li Bo , Wan Hongqiang , Pan Zaijin
Published: December 2023

The access to distributed power supply and large-scale load increases the complexity of the distribution network, resulting in the decline of traditional monitoring accuracy and the difficulty of distribution network operation status assessment. This paper proposes a distribution network operation status assessment technology based on a new sensing measurement method to provide a foundation for the stable operation of the distribution network. The operating state evaluation system is constructed by the operating standard of the distribution network, including 6 types of upper indicators and 14 bottom indicators. The analytic hierarchy process (AHP) was used to calculate the weight factor of the evaluation index. Fuzzy mathematics is used to evaluate the operating state of the distribution network, a fuzzy matrix is established, and the evaluation results are calculated according to the principle of maximum membership degree. Finally, the validity and rationality of the proposed method are verified by the sensing measurement data.
Selection of wavelet generating function in voltage interruption detection
Authors: Gong Jing , Zhong Siyu
Published: December 2023

When using wavelet for voltage interruption detection, improper selection can lead to detection failure due to the differences in wavelet characteristics and the diversity of the generating function. Based on the analysis of wavelet characteristics, the modulus maximum principle is used to compare the detail coefficients after wavelet decomposition, and a method that should be followed for selecting the generating function is proposed. Here are four important points to consider: First, choose orthogonal wavelets that can decrease redundancy. Second, symmetry does not have a major effect. Third, higher-order vanishing moments and longer support lengths result in better singularity detection. Finally, the order of vanishing moments is more important than the support length. We establish a disturbance signal model with interruption occurring at the time of voltage zero crossing and select six types of wavelets: db1, db3, db6, db8, coif2, and coif3 for four-scale wavelet decomposition. The experimental results demonstrate the accuracy of the proposed method in this paper.
A Method for Source Location of Harmonic Instability in Renewable Power Plants Considering the Feeder Distributed Parameters
Authors: Chen Chao , Gong Liwu , Tang Xin , Zhang Wei , Lu Yuguo
Published: December 2023

The current analysis of harmonic instability in existing renewable energy substations mostly relies on the lumped parameter model of the power system, which fails to adequately describe the port characteristics of the system in a wide frequency range. However, considering the distributed parameter model of the transmission lines, the frequency domain network matrix becomes a transcendental equation, making it difficult to directly solve for the system’s inherent modes and leading to challenges in harmonic instability analysis and the accurate identification of unstable sources. Therefore, this paper proposes a new modal analysis method of harmonic stability in the frequency domain based on Pade approximation and line distribution parameters. The proposed method can not only accurately assess the stability of the system, but also locate the dominant instability source of the system.
Electric Field in Metal Stress Cone of Cable Quick Repair/Test Joint
Authors: Sun Haofei , Zhang Juning , Zhao Xuefeng , Wang Hanfeng , Wang Chong , Pu Lu , Ju Zeli , Duan Wei
Published: December 2023

In order to expedite power restoration after cable failures, a plug-in GIS (Gas Insulated Switchgear) intermediate joint is designed for cable quick repair/test. During the electric field simulation of this intermediate joint, significant electric field distortions were observed at the metal stress cones and the cable’s semi-conductive layer discontinuity, indicating potential weak points in insulation. To mitigate the electric field distortions within the joint, investigations were conducted on the impact of factors such as the gap width between the metal stress cones and the XLPE cable, the relative position of the semi-conductive layer discontinuity, the stress cone, and the winding length of high dielectric constant tape. The design and installation scheme of the metal stress cone wasa obtained through simulation, which provides a basis for the design and manufacture of the GIS quick repair/test joint.
Lightweight model of remote sensing ship classification based on YOLOv7-tiny improvement
Authors: Cheng Jinwei , Yuan Jie , Hu Xiaoning , Xie Baorong , Zhang Man
Published: December 2023

A lightweight ship classification and detection approach based on modified YOLOv7-tiny is presented to address the issue that the classification and detection of ships in optical remote sensing images is prone to mistakes and missed detection due to the complicated background in the offshore. Due to the uneven distribution of data set samples, this method applies a lightweight feature extraction module E_DSC to the backbone network to reduce the number of parameters and calculations of the feature extraction network and improve network reliability. On the other hand, the MPDIoU loss function is introduced to improve the network prediction box coverage and improve the network prediction accuracy. On a dataset of remote sensing images of ships, this strategy has been tested. The findings reveal that it improves the network’s average accuracy of ship recognition and classification by 3.3%. The amount of parameters and calculation is also better than YOLOv7-tiny with a 3% reduction in parameters and a 22% reduction in the calculation.
Theoretical Analysis of a Simple Hyperbolic Metamaterial Wave Splitter
Authors: Zhao Xiangfeng , Huang Hui
Published: December 2023

Wave splitter for TE and TM wave is critical components in the integrated optics. Current technologies mainly rely on two types of designs to separate TE and TM waves: directional coupler type and branch type, but these designs are generally complex. By exploring the transmission behavior of the waves in the hyperbolic metamaterial and the distinct dispersion relationships of TE and TM waves in these materials, we have designed a wave splitter with a simple structure. Under different parameter conditions, we can get the pure TE wave or pure TM wave in the transmission region. Furthermore, if the specific condition is satisfied, we can even get the pure TE wave in the reflection or transmission region and the pure TM wave in the other region at the same time. All theoretical analysis results have been verified by using COMSOL Multiphysics simulation software.
Research on 3D Equipment Modeling Technology of 500 KV Substation
Authors: Tong Donghui , Zhang Lisha , Jin Honghan
Published: December 2023

A three-dimensional simulation system for a flexible wire layout of a 500 KV substation is developed by using a hierarchical design method in this work. Firstly, the scenario model and device model for the 500 KV substation are established as the physical models. Then, the data model, flexible wire mathematical model, and connection model are established to form the rule models for the 500 KV substation. Finally, the three-dimensional simulation diagram of the 500 KV substation soft wire layout is generated by system integration. The system can quickly and accurately generate the three-dimensional simulation drawing of 500 KV substation soft wire by only seven structural parameter setting modules, achieving the purpose of programmable design. The simulation system software is proved to be feasible and correct by the data of several 500 KV substations.
Modeling of nonlinear characteristics of switched reluctance motor based on optimized RBF neuron network
Authors: Li Yiqian , Ma Qishuang , Xu Ping
Published: December 2023

The strong nonlinearity of switched reluctance motor (SRM) makes it difficult to establish an accurate mathematical model of its electromagnetic characteristics. In this paper, an artificial neural network modeling method is adopted to estimate the nonlinear flux linkage characteristics of a four-phase SRM. Based on the samples obtained by experimental measurement, a radial basis function neural network is trained and further optimized using the K-Means algorithm. The modeling accuracy of the optimized flux linkage model is analyzed in detail and also verified by dynamic simulation of a direct instantaneous torque control system of the motor.
Intelligent anomaly detection method for power and electricity data based on cubic exponential smoothing model
Authors: Yang Jing , Liu Kunpeng , Deng Zhidong , Zhang Mingjie , Gong Lihua
Published: December 2023

During the operation of the power system, abnormal electricity data are inevitably generated. How to efficiently detect and identify these abnormal data is a crucial component of power system state estimation, and it is also the foundation for the safety and stability of power system operation. Traditional anomaly detection methods only focus on specific power system characteristics, and there are problems with high computational complexity and low accuracy. To address the shortcomings of traditional methods for anomaly detection in power and electricity data, a smart anomaly detection method for power and electricity data based on a cubic exponential smoothing model is proposed. The cubic exponential smoothing model uses historical data to predict the current regional electricity consumption and then subtracts the predicted value from the true value to obtain the residual term. Finally, the DBSCAN density clustering algorithm is used to cluster the residual term, achieving the recognition of abnormal electricity data. We conduct an experimental comparison of regional electricity consumption data of a certain power grid. The results indicate that the proposed method has achieved good results in both detection rate and false alarm rate indicators in the intelligent detection of abnormal data in power and electricity consumption.
Frequency Offset Methods for Large-Scale Deployment of LoRa: A New Strategy to Reduce Data Retransmission
Authors: Nian Yongyao , Wang Haili , Zhang Junqin
Published: December 2023

LoRa technology, renowned for its extensive range and robust anti-interference capabilities, has emerged as a linchpin for myriad IoT applications, ranging from agricultural intelligence to smart metering. Yet, its potential for large-scale deployment remains stymied by significant packet conflict issues at the gateway, particularly pronounced in extensive networks involving thousands of endpoints. Such conflicts, exacerbated during network reboots, instigate a domino effect of retransmissions, power consumption, and channel resource wastage, culminating in severely impeded communication efficiency. A pivotal challenge arises from the concurrent data uploads by numerous terminals, coupled with the restrictive uplink channel choices due to limited carrier frequencies and spreading factors. While existing solutions like phase, power, and inherent frequency offsets offer avenues for distinguishing between packet conflicts, they are riddled with practical constraints. This paper introduces a novel approach, leveraging a controlled frequency offset for LoRa symbols. Grounded in the fundamentals of LoRa demodulation, this innovative strategy promises to tackle large-scale congestion without adding system intricacy.
Detection Model of Substation Personnel Safety Protection Tools Based on Improved YOLOv5
Authors: Peng Shiyi , Liao Haoshuang , Zhong Weichun , Tong Zhipeng , Li Changdong , Qiu Zhibin
Published: December 2023

Substation operation and maintenance personnel face the hazards of high voltage and strong current in their work. Therefore, it is crucial to accurately and promptly detect the condition of safety protection tools for these personnel. This paper proposes a detection model that enhances YOLOv5‘s substation personnel safety protection tool detection capabilities. The CBAM attention mechanism was integrated into the YOLOv5 model using this approach, while the feature fusion network PANet was replaced with the CB-BiFPN structure. Finally, DIoU was used instead of GIoU loss function to improve the convergence speed and detection accuracy of the model. Experimental results demonstrate that our improved YOLOv5 model achieves high accuracy and fast processing speed with a mean average precision (mAP) of 89.23% at 32 frames per second (FPS). Our proposed method outperforms other related object detection models such as Faster RCNN, SSD, and YOLOv5 in terms of performance metrics. This study improves safety protection tool detection accuracy and provides valuable insights for real-time safety management and control in substations.
Voltage Sag Data Generation Based on the Probabilistic Diffusion Model
Authors: Zhong Jun , Zhang Hongzhao , Hu Ziheng , Zhang Huaying , Sun Ruichen , Dong Kun , Wang Zitong , Zhao Jianfeng
Published: December 2023

To effectively analyze and mitigate voltage sag phenomena using deep learning techniques, a diverse and representative dataset of voltage sag events is essential. However, the available voltage sag dataset obtained from monitoring systems is often limited in quantity and lacks comprehensive coverage of various sag types. In this paper, the achievement of generating high-quality voltage sag waveforms that closely resemble real-world scenarios is accomplished by leveraging the diffusion model’s ability to capture complex data distributions. Our study focuses on modifying the diffusion model to capture the specific characteristics of voltage sag waveforms. The results demonstrate the effectiveness of the proposed approach in generating realistic voltage sag datasets, highlighting its potential for various applications in power system analysis and planning.
Design and evaluation of EMPIX2, a 100 kfps, high dynamic range pixel detector readout ASIC for electron microscopy
Authors: Wei T. , Yang H. , Deng Z. , Xue T. , Wang X.
Published: December 2023

EMPIX2 is a novel hybrid pixel detector readout ASIC for electron microscopy with a
maximum frame rate of 100 kfps and a very large dynamic range (5 × 105:1). It
features 128 × 128 square pixels at a pitch of 150 μm. Adaptive gain switching and
charge pump technology are applied to enhance the dynamic range. The pixels can operate in two
modes: pulse mode and continuous mode. In pulse mode, ultra-fast gain switching enables a rapid
response to pulsed electron sources, making it highly suitable for UEM applications. In continuous
mode, the power consumption and dynamic range are optimized for STEM applications. The readout is
frame-based, and digital image data is output by 64 pairs of LVDS drivers working in DDR mode at a
clock frequency of 400 MHz. A dedicated data acquisition system was developed for the transmission
and processing of the image data. Preliminary verification of the readout chip was performed using
an on-chip calibration source.
Oxygen self-supplied nanoparticle for enhanced chemiexcited photodynamic therapy
Authors: Liang Liman , Wang Yueying , Zhang Chensa , Chang Yulu , Wang Yuzi , Xue Jinyan , Wang Lu , Zhang Fan , Niu Kui
Published: December 2023

Photodynamic therapy (PDT) is a promising strategy for effective cancer treatment. However, it still faces severe challenges, including poor laser penetration and insufficient oxygen (O2) in solid tumors. Here, we constructed intelligent O2 self-supplied nanoparticles (NPs) for tumor hypoxia relief as well as effective chemiexcited PDT. Oxygen-carrying NPs (BSA@TCPO NPs) were obtained via the self-assembly of bovine serum albumin (BSA), bis[3,4,6-trichloro2-(pentyloxycarbonyl)phenyl]oxalate (TCPO), perfluorohexane (PFH), and chlorin e6 (Ce6). In H2O2-overexpressed tumor cells, TCPO in the NPs reacted with H2O2, releasing energy to activate the photosensitizer Ce6 and generate cytotoxic singlet oxygen (1O2) to kill tumor cells in a laser irradiation-independent manner. Moreover, the O2 carried by PFH not only reduced therapeutic resistance by alleviating tumor hypoxia but also increased 1O2 generation for enhanced chemiexcited PDT. The remarkable cytotoxicity to various cancer cell lines and A549 tumors demonstrated the advantage of BTPC in alleviating the hypoxic status and inhibiting tumor growth. Our results demonstrate that BTPC is a promising nanoplatform for cancer therapy.
Generalised quantum speed limit for arbitrary time-continuous evolution
Authors: Thakuria Dimpi , Srivastav Abhay , Mohan Brij , Kumari Asmita , Pati Arun Kumar
Published: December 2023

The quantum speed limit describes how quickly a quantum system can evolve in time from an initial state to a final state under a given dynamics. Here, we derive a generalised quantum speed limit (GQSL) for arbitrary time-continuous evolution using the geometrical approach of quantum mechanics. The GQSL is applicable for quantum systems undergoing unitary, non-unitary, completely positive, non-completely positive and relativistic quantum dynamics. This reduces to the well known standard quantum speed limit (QSL), i.e. the Mandelstam-Tamm bound when the quantum system undergoes unitary time evolution. Using our formalism, we then obtain a quantum speed limit for non-Hermitian quantum systems. To illustrate our findings, we have estimated the quantum speed limit for a time-independent non-Hermitian system as well as for a time-dependent non-Hermitian system namely the Bethe-Lamb Hamiltonian for general two-level system.