bluuebunny/crossref_metadata_2025 huggingface dataset:
Investigation of Be, Mg, Ti–adsorbed boron-germanene nanoribbons for nano applications
Authors: Ngoc Hoang Van , Thuy Huynh Thi Phuong
Published: September 2024

One-dimensional systems are nanostructures of significant interest in research due to their numerous potential applications. This study focuses on the investigation of one-dimensional boron-germanene nanoribbons (BGeNRs) and BGeNRs doped with Be, Mg, and Ti. Density functional theory combined with the Vienna Ab initio Simulation Package forms the foundation of this research. The electromagnetic and optical properties of these structures are systematically examined. The findings reveal that all the studied structures exhibit metallic behaviour, with differences in their magnetic properties. The magnetic moments of the pristine and Be-doped structures are both zero, whereas the Mg and Ti-doped structures exhibit magnetic moments of 0.012 μ
B and 2.234 μ
B, respectively. Partial density of states (PDOS) analyses highlight the contributions of various elements and the complex multi-orbital hybridization among them. The optical properties are investigated through the real and imaginary parts of the dielectric function, along with the absorption coefficient and electron–hole density. This study indicates potential applications in adsorption sensors, the modulation of system magnetism via adsorption, and information transmission technologies.
Lattice dynamics and vibrational properties of scheelite-type alkali-metal perrhenates
Authors: Maddileti Sathani , Mukherjee Supratik , Muñoz Alfonso , Errandonea Daniel , Kennedy Brendan J , Vaitheeswaran G
Published: September 2024

The present work provides insight into the structural, vibrational, and elastic properties of scheelite-type alkali-metal perrhenates AReO4 (A = Na, K, Rb, and Cs) via first-principles calculations. Sodium, potassium, and rubidium perrhenates are isostructural and crystallize in a tetragonal structure, whereas cesium perrhenate crystallizes in an orthorhombic structure. All the phonon frequencies and their corresponding mode assignments were estimated through the linear response method within density-functional-perturbation theory. The phonon density of states highlights the participation of the oxygen anions and both the A-type and rhenium (Re) cations in the low-frequency range. In contrast, the oxygen and Re atoms make relatively high and moderate contributions to the remaining phonon frequency spectrum. Considerable splitting of the longitudinal and traverse optic modes was observed. Elastic constants and phonon dispersion calculations confirmed the mechanical and dynamic stability of the studied AReO4 compounds. A redshift was observed with the frequency of the phonons following the sequence Na→Cs. The low value calculated for the bulk modulus (ranging from 28.36 GPa to 14.15 GPa) and shear modulus indicates the perrhenates have a low resistance to deformation. The values of these moduli decrease in the order of Na→Cs, which correlates with an increase in an ionic radius of the cation. The response to pressure was found to be anisotropic. This characteristic and the ductile nature of the alkali-metal perrhenates were confirmed through elastic analysis.
Enhancement of tunneling electroresistance in metal/two-dimensional ferroelectric tunnel junctions: route for polarization-modulated interface transport
Authors: He Shiying , Zou Daifeng , Lei Chihou , He Zhijian , Liu Yunya
Published: September 2024

In fabricating ferroelectric tunnel junction (FTJ) devices, it is essential to employ low-resistance metals as electrodes interfacing with two-dimensional (2D) ferroelectric materials. For FTJs with a top contact configuration, two interfaces for charge transport are present, namely the vertical interface between the metal electrode and the 2D ferroelectric material, and the lateral interface between the electrode and the central scattering region. These interfaces significantly influence the tunneling electroresistance (TER) of FTJs. However, there exists a notable deficiency in comprehension concerning the physics of charge transport at the interface. In this work, we explore the interface transport properties in FTJs featuring a top contact configuration between metal and the typical α-In2Se3 monolayer. By employing the non-equilibrium Green’s function method, we observe a TER ratio of

1.15
×

10
5

% for the Pd top contact interfacing with an α-In2Se3 monolayer. The significant TER effect is attributed to polarization-controlled interface transport, which is further elucidated through an analysis of the transport mechanisms influenced by the out-of-plane polarization of α-In2Se3 at the vertical interface and the in-plane polarization at the lateral interface. This investigation of the fundamental physical mechanisms of polarization-controlled interface transport demonstrates significant potential for enhancing non-volatile memory devices.
An adaptive weighted magnetic anomaly detection based on full magnetic gradient orthonormal basis function
Authors: Yan Youyu , Liu Jianguo , Shen Siyuan , Yan Shenggang
Published: September 2024

Magnetic gradient tensor has enjoyed great popularity in magnetic anomaly detection recently. The detection method using the full magnetic gradient orthonormal basis function has been proven to be effective in extracting the target’s magnetic anomaly signal. However, the six energy components obtained by the FMG-OBF detector vary with true energy terms (influenced by the orientation of the target’s magnetic moment and the moving trajectories), noise energy terms and middle terms, which largely affects the performance of the total energy. In this paper, an adaptive weighting FMG-OBF method, which is based on the sigmoid function to assign appropriate weights to normalized energy components according to their detection performance, is proposed to tackle this concern. Experiments have demonstrated that the proposed method has a higher signal-to-noise ratio from the perspective of signal energy and is less affected by the OTMM compared with the original method.
A Hamilton–Jacobi approach to nonlocal kinetic equations
Authors: Loy Nadia , Perthame Benoît
Published: September 2024

Highly concentrated patterns have been observed in a spatially heterogeneous, nonlocal, kinetic model with BGK type operators implementing a velocity-jump process for cell migration, directed by the nonlocal sensing of either an external signal or the cell population density itself. We describe, in an asymptotic regime, the precise profile of these concentrations which, at the macroscale, are Dirac masses. Because Dirac concentrations look like Gaussian potentials, we use the Hopf–Cole transform to calculate the potential adapted to the problem. This potential, as in other similar situations, is obtained through the viscosity solutions of a Hamilton–Jacobi equation. We begin with the linear case, when the heterogeneous external signal is given, and we show that the concentration profile obtained after the diffusion approximation is not correct and is a simple eikonal approximation of the true H–J equation. Its heterogeneous nature leads us to develop a new analysis of the implicit equation defining the Hamiltonian and a new condition to circumvent the ‘dimensionality problem’. In the nonlinear case, when the signal occurs from the cell density itself, it is shown that the already observed linear instability (pattern formation) occurs when the Hamiltonian is convex-concave, a striking new feature of our approach.
Energy expenditure prediction in preschool children: a machine learning approach using accelerometry and external validation
Authors: Coyle-Asbil Hannah J , Burk Lukas , Brandes Mirko , Brandes Berit , Buck Christoph , Wright Marvin N , Vallis Lori Ann
Published: September 2024

Objective. This study aimed to develop convolutional neural networks (CNNs) models to predict the energy expenditure (EE) of children from raw accelerometer data. Additionally, this study sought to external validation of the CNN models in addition to the linear regression (LM), random forest (RF), and full connected neural network (FcNN) models published in Steenbock et al (2019 J. Meas. Phys. Behav.
2 94–102). Approach. Included in this study were 41 German children (3.0–6.99 years) for the training and internal validation who were equipped with GENEActiv, GT3X+, and activPAL accelerometers. The external validation dataset consisted of 39 Canadian children (3.0–5.99 years) that were equipped with OPAL, GT9X, GENEActiv, and GT3X+ accelerometers. EE was recorded simultaneously in both datasets using a portable metabolic unit. The protocols consisted of a semi-structured activities ranging from low to high intensities. The root mean square error (RMSE) values were calculated and used to evaluate model performances. Main results. (1) The CNNs outperformed the LM (13.17%–23.81% lower mean RMSE values), FcNN (8.13%–27.27% lower RMSE values) and the RF models (3.59%–18.84% lower RMSE values) in the internal dataset. (2) In contrast, it was found that when applied to the external Canadian dataset, the CNN models had consistently higher RMSE values compared to the LM, FcNN, and RF. Significance. Although CNNs can enhance EE prediction accuracy, their ability to generalize to new datasets and accelerometer brands/models, is more limited compared to LM, RF, and FcNN models.
Enhancing P-wave localization for accurate detection of second-degree and third-degree atrioventricular conduction blocks
Authors: Liu Wenjing , Yan Li , Huang Yangcheng , Yin Ziyi , Wang Mingjie , Cai Wenjie
Published: September 2024

Objective. This paper tackles the challenge of accurately detecting second-degree and third-degree atrioventricular block (AVB) in electrocardiogram (ECG) signals through automated algorithms. The inaccurate detection of P-waves poses a difficulty in this process. To address this limitation, we propose a reliable method that significantly improves the performances of AVB detection by precisely localizing P-waves. Approach. Our proposed P-WaveNet utilized an attention mechanism to extract spatial and temporal features, and employs a bidirectional long short-term memory module to capture inter-temporal dependencies within the ECG signal. To overcome the scarcity of data for second-degree and third-degree AVB (2AVB,3AVB), a mathematical approach was employed to synthesize pseudo-data. By combining P-wave positions identified by the P-WaveNet with key medical features such as RR interval rhythm and PR intervals, we established a classification rule enabling automatic AVB detection. Main results. The P-WaveNet achieved an F1 score of 93.62% and 91.42% for P-wave localization on the QT Dataset and Lobachevsky University dataset datasets, respectively. In the BUTPDB dataset, the F1 scores for P-wave localization in ECG signals with 2AVB and 3AVB were 98.29% and 62.65%, respectively. Across two independent datasets, the AVB detection algorithm achieved F1 scores of 83.33% and 84.15% for 2AVB and 3AVB, respectively. Significance. Our proposed P-WaveNet demonstrates accurate identification of P-waves in complex ECGs, significantly enhancing AVB detection efficacy. This paper’s contributions stem from the fusion of medical expertise with data augmentation techniques and ECG classification. The proposed P-WaveNet demonstrates potential clinical applicability.
Breakdown modes of capacitively coupled plasma: I. Transitions from glow discharge to multipactor
Authors: Wu Hao , An Ran , Zhong Dong , Jiang Wei , Zhang Ya
Published: September 2024

This paper is the first in a two-part series that simulates the breakdown modes of capacitively coupled plasmas (CCPs) across various pressures using an implicit particle-in-cell/Monte Carlo collision model. The study identifies several discharge modes in the lower pressure region, including three self-sustained discharges: glow discharge, normal multipactor, and abnormal multipactor, as well as various non-self-sustained discharges. This part focuses on the formation and transitions of self-sustained modes, specifically detailing how the glow discharge transitions into an abnormal multipactor below 2 mTorr, which then evolves into a normal multipactor within a narrow voltage range. The characteristics and formation processes of these self-sustained discharges are explored, emphasizing their reliance on higher electron emission rates and high-frequency RF power. The emergence of multipactor discharges in the 60 MHz range potentially expands the gas discharge theory and broadens the application scope of CCPs.
Experimental testing of additively manufactured embedded fiber optic smart devices for clean energy applications
Authors: Donlan Connor F , Cabral Arturo , Carasik Lane B , Boulanger Andrew J , Derek Rountree S
Published: September 2024

An additively manufactured prototype smart device was created to investigate in-flow temperature distributions using embedded high-definition fiber optic sensors within a component for clean energy systems. The devices were created using Ultrasonic Additive Manufacturing to create a unique embedded pathway within a flow conditioner for the high-definition fiber optic sensors to be placed within. The fibers used allowed for temperature measurements to be taken every 0.65 mm along the fiber. The high-resolution fibers were thermally calibrated enable the 2D reconstruction of the temperature profile in the flow path of the structure. This is due to the temperature-related strain response of the material and strain measurements of the fibers. Hot airflow testing of these devices showed the ability to identify localized temperature differences in the flow. The observed strain response within the smart device had higher strain concentrations in the thicker web regions than in the thinner web regions. These higher strain regions resulted in higher uncertainties for the temperature responses. Further calibration is needed to improve the accuracy of the smart devices, specifically within the inner web structures of a flow straightening component. Further investigations of the devices within flow showed the temperature sensing to be independent of the effects of flow velocity. The devices were able to distinguish temperature differences within single and two-phase flow and showed local sensitivity to the temperature changes with the identification of hot and cold spots. The presented results showed the viability of the smart device for obtaining detailed temperature distributions using common industrial components. Eventually, the goal for these smart devices will be to withstand higher temperature and pressure environments such as those experienced in nuclear, fusion, and concentrated solar energy systems.
Topological coindices and QSPR analysis for some potential drugs used in lung cancer treatment via CoM and CoNM-polynomials
Authors: Sağlam Özkan Yeşim , Kara Yeliz
Published: September 2024

Topological indices are used to convert a chemical structure into a real number, usually to study the physicochemical and biological properties of molecules. The groundwork is prepared for the interpretation of the obtained data by processing with Quantitative Structure Property/Activity Relationship (QSPR/QSAR). In this study, the drugs lorlatinib, gefitinib, sotorasib, pralsetinib, crizotinib, adagrasib, alectinib, brigatinib, dacomitinib and entrectinib, which are potential to be used in the treatment of lung cancer, are discussed. Topological coindices are calculated with the help of CoM and CoNM polynomials obtained with the graph structures of these drugs. The relationship between topological coindices and physicochemical properties such as evaporation enthalpy, flash point, molar refraction, polarisation, surface tension, molar volume are investigated by QSPR analysis. At this stage, linear, logarithmic and quadratic regression methods have been used. The results show that the values of these topological indices are highly correlated with certain physicochemical properties of the used some drugs in the treatment of lung cancer. In addition, using comparative analysis, the actual values and the values calculated with the help of topological indices have been examined in terms of predictive ability. The findings of this search demonstrate topological indices’ potential as tools for cancer drug discovery and design.
Bipartite quantum features influenced by pure and mixed disorders
Authors: Noman Muhammad , Kenfack Lionel Tenemeza , Cui Wei
Published: September 2024

This study explores quantum features, namely negativity, quantum-memory entropic uncertainty, entropic coherence, and linear entropy in a two-qubit mixture system comprising two Bell states under various classical environments. Furthermore, we assume including pure noise (colored pink, colored brown, Gaussian) and mixed noise (brown-Gaussian, pink-Gaussian) characterizing the classical environments. The influence of the purity parameter of the system along with the inclusive noise parameters is systematically analyzed. The entropic coherence and negativity functions remain sensitive to the noise showing larger revivals compared to the quantum-memory and coherence functions. The interplay between different types of noise leads to interesting dynamics, such as the suppression of Gaussian noise’s Markovian behavior by non-Markovian brown noise. Interestingly, the non-Markovian traits of pink noise are highly suppressed when combined with Gaussian noise. Besides, in mixed noise scenarios, non-regular fluctuations contrast with regular revivals in pure noise cases. The brown-Gaussian mixed noise case reveals the suppression of Gaussian noise’s Markovian behavior by non-Markovian brown noise, influencing overall dynamics. Notably, this scenario shows slight entanglement generation, unusual under classical environments, highlighting unique dynamics in mixed noise scenarios.
Rogue waves of the Nizhnik-Novikov-Veselov equation via self-mapping transformation
Authors: Zhang Jie-Fang , Jin Mei-Zhen , Zhang Zhao
Published: September 2024

This paper introduces a new two-dimensional self-mapping transformation applied to the Nizhnik-Novikov-Veselov equation, resulting in the generation of numerous rogue wave solutions. We discover that temporal-localized and spatiotemporal-localized two-dimensional rogue waves respectively. Notably, these rogue waves emerge from a zero background and subsequently exhibit both algebraic and exponential decay patterns. The proposed technique offers a potential tool for constructing rogue-like waves within (2+1)-dimensional nonlinear wave frameworks. The findings presented here serve as a robust mathematical foundation for advancing both theoretical understanding and practical applications of rogue waves.
Dynamically tunable highly sensitive sensor based on graphene and black phosphorus composite metamaterial
Authors: Xu Yiping , Wang Ziyi , Yang Yang , Huang Xin , Zeng Xiaodong , Cheng Shubo , Yi Zao , Yao Shunyu , Liu Lian , Zhou Jiayi , Duan Yunxuan
Published: September 2024

Focusing on the realization of multiple-detection-point sensors in the mid-infrared band, a dynamically tunable high-sensitive index refraction sensor based on graphene and black phosphorus (BP) composite metamaterial is proposed. By adjusting the height of the grating, the strength of the structural plasmon-induced absorption (PIA) can be enhanced within a certain range. The energy transfer mechanism of the system is analyzed by the coupled mode theory (CMT), the theoretical data of CMT fit well with the FDTD simulation results, which proves that the analysis of the system using the CMT model is correct. The resonant wavelengths of the PIA can be efficiently modulated by changing the Fermi level of graphene and the carrier density of BP. It is worth mentioning that under different environmental refractive indexes, our proposed system has excellent sensing characteristics in the mid-infrared band. The maximum sensitivity and the maximum figure of merit (FOM) are up to 5.174 μm/RIU and 26.449, respectively. This research could play an important role in mid-infrared optical sensors.
Broadband low-loss polarization-insensitive graphene-integrated photonic crystal fiber modulators in the near-infrared range
Authors: Ye Longfang , Su Siyi , Zhang Yong , Zhu Chunhui , Zhuo Jianliang , Liu Qing Huo
Published: September 2024

The amplitude modulator with the function of converting electric signal to optical amplitude modulation is a key component in high-speed optical communication links. In this paper, we demonstrate a variety of two-dimensional graphene-integrated photonic crystal fiber modulators for efficient near-infrared amplitude modulation with ultra-low insertion loss. Taking the advantages of the perfect total internal reflection of the porous photonic crystal fiber and flexible tunability of the graphene conductivity, the modulation depth of 0.075 dB μm−1 with a low optical loss of 2.13 × 10−4 dB μm−1, a long propagation length of ∼20 mm and polarization-insensitive characteristics in a wide wavelength of 1.3 to 1.8 μm can be achieved. This high-performance modulator may have great potential applications in various high-speed telecommunication, interconnection, and graphene-based integrated photonic systems.
Electromagnetic modeling and analysis based on multilayer domain structure for GMI behavior in high frequency
Authors: Wang Y F , Feng T F , Li Y L , Makhnovskiy D P , Eggers T , Phan M H , Qin F X
Published: September 2024

Existing theoretical models on the frequency dependence of the magnetoimpedance (MI) in ferromagnetic microwires primarily describe the MI phenomenon at the limiting cases of lower MHz (several GHz) ranges. However, in the intermediate region between these two ranges, known as the transition region, MI curves undergo complex transformations. These transformations have been documented in the literature, but their underlying causes remain poorly understood. Unambiguous knowledge of the domain structure and its correlation with MI properties is essential for elucidating this behavior. In this study, we have, for the first time, observed the inner core magnetic structure of Co-based microwires and revealed its relationship with the high-frequency MI effect. A distinct magnetic structure comprising longitudinal domains in the inner core (IC), circular domains in the outer shell (OS), and a transition region (TR) has been identified. This structure originates from compositional gradients and residual stresses during microwire fabrication. The IC/TR/OS structure manifests in the complex transformations of the MI behavior, exhibiting a turning point at GHz frequencies before the characteristic double MI peak. We developed a multilayer planar model that considers this more realistic magnetic structure, including the TR layer. This model successfully reproduces the key features of the MI curves and provides deeper insights into the high-frequency MI phenomenon. Our findings pave the way for optimizing the sensing capabilities of Co-based ferromagnetic microwires and demonstrate the potential of using high-frequency MI measurements to map their magnetic microstructures.
Synthesis and characterization of ZnO nanoparticles prepared by green routes: controlling morphologies by maintaining pH
Authors: Sharma Surabhi , Singh Archana Kumari , Singh Satya Pal , Singh Rajnish Kumar
Published: September 2024

The synthesis of metal oxide semiconductor nanoparticles has attracted much attention in recent past. Nanoparticles are broadly used in solar energy conversion, catalysis, varistors, gas sensors, and non-linear optics, etc. Due to their wide band gap properties, zinc oxide nanoparticles are widely used in numerous applications. Zinc oxide nanoparticles have a wide band gap of approximately 3.3 eV. In this work, we have reported synthesis and characterization of ZnO nanoparticles having rod-like, spherical and flower-like structures. We have used zinc acetate dehydrate [Zn(CH3COO)2. 2H2O] and aqueous extract of Dahlia Pinnata leaves and deionized water. Dahlia Pinnata leaves extract has not been previously used to prepare ZnO NPs. It serves as a reducing and capping agent. We have analyzed the presence of chemicals in the extract using FTIR, Raman and NMR spectroscopy techniques. It is found that the unique morphology of ZnO NPs flower-like structures, enhances it's sensing properties in comparison to the spherical ones. We have used UV–vis-nir spectroscopy, x-ray diffraction (XRD), Fourier Transform Infrared Microscopy(FTIR), and Scanning Electron Microscope (SEM) analysis and have explored the opto-electronic properties of ZnO nanoparticles and have correlated with their structural and morphological properties.
A well production prediction method based on blending heterogeneous ensemble learning optimized by OOA
Authors: Zhang Zhanquan
Published: September 2024

Oil well production prediction is an important research content in oilfield development, and constructing a scientific and good prediction model is a key issue. In this paper, a blending ensemble learning oil well production prediction model combining Random Forest, LGBM, and TCN is established and optimized by the Osprey optimization algorithm. Firstly, ANOVA and Pearson’s correlation coefficient is used to filter the relevant features affecting the well yield prediction, the autocorrelation coefficient is used to determine the lag order of the well yield prediction, and RF, LGBM, and TCN networks with good performance are selected as the base learners. Linear regression is used as the meta-learning to form the blending ensemble learning model, and the Osprey optimization algorithm is used to optimize the whole blending ensemble learning model. The Osprey optimization algorithm is used to optimize the whole blending model, and the optimal hyperparameters are derived and brought into the ensemble learning prediction model. After the experiment, it is shown that the ensemble oil well production prediction model can reduce the MAE by about 12.75% compared with the single prediction model, and can effectively predict the future production of oil wells.
Modeling of biomass gasification polygeneration
Authors: Liu Jiang , Dai Pengrui , Jiang Weiting
Published: September 2024

A single biomass gasification technology often struggles to simultaneously meet the requirements of efficiency, economy, and environmental sustainability. Hence, this paper establishes a biomass gasification polygeneration model, integrating biomass gasification with the subsequent utilization of syngas. The system comprises parallel chemical and power units, enabling polygeneration activities such as methane production and electricity generation through syngas derived from gasification units. Within the system, syngas are split: a portion is directed to the methane synthesis unit for methane production, while the remainder is sent to the combined cycle unit for electricity generation. Concurrently, the tail gas produced after methane synthesis enters the combined cycle unit. Throughout this process, by-product steam is utilized for grade matching in each section of the chemical synthesis side, with any excess steam utilized for steam turbine power generation. Using the established polygeneration model, this study examines the influence of gasification temperature on the performance of the polygeneration system.
Stability study of a two-DOF piezoelectric energy harvester
Authors: Li Yuanhua , Han Minglei
Published: September 2024

Self-adaptive or self-adjusting vibration energy harvesting has the advantage of high-power density in multi-directional vibration excitations and has entered the vision of researchers. Due to the presence of a two-DOF cantilever beam, there is potential instability in the self-adaptive or self-adjusting vibration energy harvesting system. This paper takes a direction self-adaptive vibration energy harvester (DSVEH) as an example to study the influence of system parameters on stability. It is found that the larger the centroid offset distance, the more stable the system is; The greater the resistance torque, the more stable the system is. In practical applications, system parameters should be matched reasonably. This study can be used for relevant parameters optimization of direction self-adaptive vibration energy harvesting systems.
Study on the deviation of outlet air velocity of powder feeding duct in power plant based on sudden tube expansion
Authors: Sun Kang , Cheng Zhihai , Lou Zhongfa , Wang Zhiwu
Published: September 2024

The existence of the deviation of the outlet air velocity of the powder feeding pipeline in a power plant affects the depth of the primary air injection and the degree of diffusion of the combustion flame, leading to the skewed combustion flame. It affects the ignition and steady combustion of pulverized fuel in the boiler chamber, leading to the slagging of the locally heated surface, and thus affecting the safety and flexibility of the boiler operation. In this paper, taking the powder-feeding pipelines corresponding to six coal mills in the direct-blowing pulverizing system of a power plant as the research object, numerical simulation technology is used to study the influence of the addition of a sudden expanding pipe on the deviation of the outlet wind speed of the powder feeding pipeline. Numerical simulation results show that the installation of a surge pipe in the horizontal straight section of the powder feed pipe with a large outlet wind speed can effectively reduce the outlet wind speed of the powder feed pipe, which in turn reduces the deviation of the outlet wind speed of each powder feed pipe. After the installation of the surge pipe, the maximum deviation of the wind speed of the powder feed pipe is reduced from 1.15 to 1.07.
Simulation analysis of the influence law of high-voltage discharge-breaking rock
Authors: Na Xueshuo , Li Hongda , Zheng Haowen
Published: September 2024

In order to study the influence of the high-voltage discharge rock-breaking process, in this paper, the simulation model of needle electrode structure is established by COMSOL simulation software, simulating the distribution of the electric field strength by different rocks under the factors of voltage, electrode spacing, and insulating medium. The results show that the larger the permittivity of the rock, the larger the field strength inside the rock; the strength of the electric field inside the rock increases linearly with increasing voltage; the strength of the rock’s electric field gradually decreases as the electrode spacing increases; the insulating medium affects the efficiency of the rock breaking, and the smaller the permittivity is, the easier the rock is to be broken through.
Lithium battery SOH prediction based on multi-indicator optimal weight fusion
Authors: Yan Xi , Li Qi , Yan Ran
Published: September 2024

To improve the prediction accuracy of battery health state, this study proposes a prediction method combining health indicator polynomial (HIP) and Improved Grasshopper Optimization Algorithm (IGOA). Based on Support Vector Regression (SVR), three representative health indicators (HI) were selected, and a polynomial model integrating multiple HI was constructed by using weighted fusion. Considering that the value of the weight coefficient of the feature, the penalty coefficient of SVR and the kernel parameter have a great influence on the prediction accuracy, the improved grasshopper optimization algorithm is used to jointly optimize the weight coefficient and related hyperparameters in the model. The simulation results on the University of Maryland battery data set show that the proposed prediction method has higher prediction accuracy, and the prediction error is basically maintained within 0.03.
Design and analysis of inertial fatigue loading device for bidirectional wind turbine blades
Authors: Liu Weicheng , Liao Gaohua , Lai Guibing
Published: September 2024

In order to improve testing efficiency and reduce testing costs, the two-degree-of-freedom (two-DOF) fatigue loading is an effective testing method for wind turbine blades. An electrically driven inertial excitation device based on a crank-slider structure was designed, and the energy method was used to calculate the energy consumption and power parameters to construct a bidirectional resonance-type wind turbine blade fatigue test system. The LaGrange’s Equation method was used to establish the dynamic model of bidirectional fatigue loading of wind blade, and combined with the equation of state of the three-phase permanent magnet synchronous motor in the d-q coordinate system, the electromechanical coupling equations of the system were jointly constructed. The simulation model was established by using MATLAB software to carry out the numerical simulation analysis, and the fundamental law of the system’s coupled vibration process was obtained, offering insights into the design of the blade fatigue test system and control algorithm.
Substation secondary equipment fault detection based on the Llama2 model
Authors: Zhang Haili , Mu Juntao , Li Yongbin , Wang Xin , Chen Bin , Cui Min
Published: September 2024

In the field of power systems, this paper proposes a novel method to detect and diagnose faults in secondary equipment in substations. Using the latest large-scale language model Llama2, a deep learning analysis of online monitoring information of substation secondary equipment was carried out to automatically detect and classify potential faults. The powerful semantic understanding and text analysis capabilities of the Llama2 model enable us to learn and identify failure modes from a large amount of historical data. When data annotation is limited, self-supervised learning technology is used to enable the model to learn and extract valuable features for fault detection from unlabeled data. Through a series of experiments and comparative analysis, our method not only improves the accuracy of fault detection but also reduces false alarms.
Transmission line fault diagnosis based on SENet-ResNext-LSTM
Authors: Li Ge , Tang Di , Tang Shun
Published: September 2024

A proposed model for diagnosing faults in transmission lines, integrating attention mechanisms, the ResNext network, and the Long Short-Term Memory (LSTM) network addresses issues such as diminished precision, constrained adaptability, and reliance on conventional manual fault detection methods. Initially, waveforms captured from transmission line faults undergo wavelet transformation filtration. These waveforms are subsequently partitioned into two segments for feature extraction. One segment undergoes processing by the ResNext module, equipped with an attention mechanism, thereby reducing computational complexity. In contrast, the other segment is input to the LSTM network to ascertain the dependence on fault data sequences. Ultimately, features derived from both branches are combined and input to the Softmax layer for fault classification. Experimental results indicate that our proposed approach surpasses existing deep learning methods in accuracy metrics for diagnosing faults in transmission lines.
ANSYS Simulation-based analysis of cable insulation faults
Authors: Wan Qingzhu , Min Xianjuan
Published: September 2024

Insulation degradation of cables is the core factor of its shortened life, and the current operation and inspection departments are unable to effectively analyse cable insulation defects from multiple perspectives. To address this problem, ANSYS simulation was used to extract the characterization of cable insulation faults. Firstly, the fundamentals of defective insulation in cables were introduced. Then, a finite element model of a 10kV Cross-Linked Polyethylene (XLPE) cable was established by using ANSYS simulation software. Finally, simulations and analyses of bubbles, bulges, and cable insulation exhibiting water-tree defects were carried out to derive changes in the cable’s magnetic field strength due to different defects. The results indicate that as the degree of cable insulation defects continues to increase, the cable’s magnetic field strength also undergoes distortion.
Non-intrusive load monitoring based on equipment operation state
Authors: Zhang Xiao , Cheng Sijin , Wang Yi , Wang Shenzheng , Li Xinyi , Gu Yang
Published: September 2024

Energy disaggregation, known as Non-Intrusive Load Monitoring (NILM), is a practical approach to providing device-level electrical information and can be applied to enhance various scenarios in smart grids. In recent years, with the emergence of large-scale energy consumption datasets, a growing multitude of deep learning methods have been employed to address energy disaggregation problems. However, these methods face challenges in resolving the disaggregation of multi-state devices and devices with overlapping operation cycles, especially during startup and shutdown periods. This paper addresses these challenges by proposing a load disaggregation framework based on equipment operation state. Diverging from existing methods, the load disaggregation task in this paper is divided into two stages. The first stage primarily employs load recognition methods to detect and identify the state transition information of the target appliance. The second stage, based on the identified information from target appliance events, utilizes power filling and power correction methods to achieve load disaggregation. Additionally, a data augmentation method is introduced to alleviate the issue of insufficient sample quantity in the dataset, which hinders model training. Experimental comparisons are conducted on widely used public datasets in the NILM field, namely REDD, and UKDALE, against various state-of-the-art methods. The proposed method achieves an average Mean Absolute Error (MAE) of 3.331 for disaggregating multiple appliances, reducing approximately 38% compared to existing methods. These results robustly validate the advancement of the proposed approach in this paper.
Simulation analysis on the influence of airflow channel shape on the thermal storage and release performance of solid heat storage device
Authors: Chen Mengdong , Kang Wei , Tan Hui , Deng Zhanfeng , Lv Hongkun , Ding Liwei , Guo Xutao
Published: September 2024

A simulation analysis of the effect of airflow channel shape on the heat storage and release performance of solid heat storage devices was conducted. A mathematical model for a heat storage device with thermal energy bricks and circular and elliptical holes as airflow channels were developed, and the model’s correctness was verified. Results showed that when the cross-sectional area was the same, the heat transfer performance of bricks with circular holes was 20% lower than that of bricks with elliptical holes. The direction of the elliptical hole had no effect on heat transfer performance. The structure of the flow channel shape affected the distribution of air mass flow rate, which would further affect the heat storage and release performance of the heat storage device.
Simulation study of modular independent cooling systems for servers
Authors: Jia Deyi , He Wei , Xu Chenchen , Guo Tao
Published: September 2024

With the development of information technology, IT equipment within data centers is becoming increasingly dense, leading to a continuous increase in heat flux density. In order to significantly enhance the cooling efficiency of servers, this study proposes a server-level modular independent cooling system, which integrates the cooling system’s end devices completely within the servers. Compared to traditional room-level air conditioning cooling schemes, this approach avoids unnecessary cooling during the cooling transfer process, thereby improving energy usage efficiency and data center space utilization. Additionally, it allows for independent adjustment based on the actual load and temperature requirements of each server. This research provides new insights for optimizing server design.
Research on large-scale microchannel heat exchangers in domestic heat pump air conditioning applications
Authors: Dou Jie , Wen Xueying
Published: September 2024

Air source heat pumps are widely used and indispensable in the field of household air conditioning. However, in the low-temperature environment of northern regions in winter, the problem of frosting on heat exchangers is more severe, which restricts the development of the entire heat pump market in the north. This article conducts a simulation study on large-sized microchannel heat exchangers that can be applied to household air source heat pump air conditioners, establishes corresponding three-dimensional models of fins and heat exchange tubes, simulates the frosting situation around the louvered vertical fin and heat exchange tubes under different temperatures and wind speeds, and draws corresponding conclusions based on the simulation results. This provides a basis for further optimizing and improving microchannel heat exchangers and further supports the expansion of the use of household air source heat pump air conditioners.
Simulation application of support vector machine feedforward control in gas turbine load control
Authors: Li Da , Zhang Jian , Zhuang Yifei , Zhen Cheng , Zhang Jiawei
Published: September 2024

To address the challenges of excessive overshoot, prolonged settling time, and complex PID parameter tuning in gas turbine load control, this study investigates a gas turbine load control system utilizing support vector machine feedforward control. Firstly, the load control loop is decomposed, and the existing model structure is integrated with the load control section. Subsequently, the gas turbine load loop is modeled based on field test data. Following this, a gas turbine load control system incorporating a support vector machine feedforward loop is constructed in the MATLAB/Simulink environment. Finally, the entire loop undergoes simulation experiments. The simulation results demonstrate that the system exhibits rapid response to load step changes, enhances the stability of the load control loop, and effectively fulfills the requirements of grid-source coordination in modern power systems.
Simulation study of a flue gas waste heat and water co-recovery system
Authors: Deng Yu
Published: September 2024

To improve the economy and safety of the power plant, the waste heat and water co-recovery system with two-stage flue gas coolers (FGC) was put forward. Two-stage FGCs were equipped between the induced draft fan (IDF) and the wet limestone flue gas desulfurization (WFGD), the WFGD and the wet stack. To ensure safety, Each stage flue gas cooler consisted of two independent heat exchangers (hot end heat exchanger named FGC-H, cold end heat exchanger named FGC-C) with a coupling fluid which is circulated by a pump, and this method named fluid coupled indirect heat exchange (FCHE) technology. Due to the temperature of flue gas through two FGC-Hs being below the acid and/or water vapor dew points, two FGC-Hs adopted the plastic heat exchanger to prevent the sulfur attack. Then, the impact of the waste heat and water co-recovery system on the dynamic behavior and the economic performance of the studied power plant have been verified by simulation tests on the full-scale simulator of the studied 330 MW coal-fired power plant. The results show that the waste heat and water co-recovery system could effectively improve the economy and environmental performance of the studied power plant. It is an effective way to realize further flue gas waste heat utilization.
Research on reserve auxiliary service clearance models based on elastic price curves
Authors: Chen Mingyuan , Li Ling , Zheng Wenbin , Liang Yanjie , He Yini , Fang Xuelian , Xuan Peizheng , Cheng Lanfen , Peng Chaoyi
Published: September 2024

When there is a large forecast error or a sudden change in the power system load, there will be a significant power generation gap, which needs to be supported by reserve auxiliary services to ensure power balance. Meanwhile, with the gradual increase of renewable energy penetration rate, reserve auxiliary services can also be used to cope with the variability and intermittency of renewable generation. Therefore, the significance of reserve auxiliary services for the security and stability of the grid operation is increasingly prominent. For reserve ancillary services, this study aims to propose three clearance models based on the elastic price curves, compare their clearance mechanisms, and analyze their advantages and disadvantages by using an example simulation with Matlab. Simultaneously, applicability analysis is conducted to assess the applicability of these models to different power market development scenarios. The results of this study contribute to the understanding of the clearance mechanisms of reserve auxiliary services and provide a reference for the construction and decision-making of power markets.
Experimental study on flexible PV/T system under different working conditions
Authors: Wang Jikai , Zhu Qunzhi
Published: September 2024

In the overall life cycle energy consumption of China’s construction sector, building energy usage constitutes a significant portion, and the process of China’s dual carbon goals can be greatly accelerated by reducing building operation energy consumption. Solar energy, as a kind of renewable energy, is increasingly mature in construction applications. PV/T comprehensive utilization technology has attracted much attention in using solar energy. The flexible PV/T system can fit on the facade of various bending angles. This paper conducts indoor variable working conditions (irradiance and volume flow) and flexible PV/T and flexible PV contrast experiments on the existing flexible PV/T system. Observations reveal a direct correlation between irradiance, volume flow rate, electric power enhancement, and thermal efficiency in the flexible PV/T system. Flexible PV/T systems can produce more electricity than flexible PV systems at the same irradiance.
Air energy heating system for crude oil based on photovoltaic green electricity
Authors: Liu Shizhen , Liu Cheng , Xu Zengjin , Zheng Haixin , Miao Wenhao , Zhang Shennan
Published: September 2024

In the traditional oil production process, the crude oil and oil-water mixture extracted from the wellhead need to be heated before being transported to the combined station to reduce the system’s resistance loss along the way, and the heating is usually carried out by natural gas and gas furnaces. To achieve the double carbon goal of energy 3060 in China, this paper proposes the solution of heating crude oil with a photovoltaic green electric air heat source pump: When there is light, the photovoltaic provides green electricity to the air heat source pump for heating crude oil; When there is no green electricity, the original natural gas heating furnace is automatically started to supplement the lack of green electricity. The program not only reduces the consumption of petrochemical energy and environmental pollution, but also makes full use of the renewable energy of solar energy and gives full play to the energy-saving effect of air heat source pumps. The scheme has been demonstrated in part of the oil production field in Qinghai Oilfield, and shortly, with the continuous advancement of the solar thermal project, the crude oil heating system will achieve full coverage of green electricity.