bluuebunny/crossref_metadata_2025_split huggingface dataset:
An evaluation strategy for relay protection status based on the cloud model
Authors: Huang Menghua , Wu Kaiwu , Chen Tao , Ye Qing 
Published: March 2024

Abstract
After the relay protection secondary equipment is put into operation for a period of time, it will be affected by aging, faults, and other factors, resulting in the gradual decline of the health state of the equipment. Therefore, considering the uncertainty of the influencing factors of equipment aging fault, a relay protection state evaluation method based on the cloud model is proposed. The factors affecting the real-time health state of equipment were analysed, the evaluation indexes were selected, and the weights of each index were calculated. Considering the randomness and fuzziness of the influence factors, a comprehensive evaluation model was established based on boundary fuzzy processing and cloud parameter calculation. Finally, an example was given to verify the rationality and effectiveness of the proposed algorithm.
Analysis of AC filter detuning characteristics and improvement measures in converter station
Authors: Huang Menghua , Xiong Wenting , Wu Kaiwu 
Published: March 2024

Abstract
Shift of parameters of the double-tuned AC filter component and failure in prompt correction of detuning frequency may affect the filtering effect of the AC filter. Therefore, this paper studies impedance-frequency characteristics of the double-tuned AC filter according to detuned recording data of the A-typed double-tuned AC filter in the Congxi converter station. It analyzes the variation of the impedance-frequency characteristic curves and relative change rate of resonant frequency as there are deviations between actual values and rated values of each filter capacitance and inductance elements in different degrees, and concludes that variation of the parameter of each element in different degrees may cause different deviations of resonant points of the double-tuned AC filter. MATLAB simulation has proved it can reduce the detuning degree and improve the filtering performance of the filter by adjusting the parameters of the variable reactor to change in the opposite direction of the parameters of the resonant capacitor.
Research on resistance detection robot for UHV tension insulator string
Authors: Wang Zhenyu , Li Yunxiang , Li Jiang , Ai Yunfei , Mao Dun , Zou Jinzhou , Xu Yurong , Wu Yuze 
Published: March 2024

Abstract
Insulator inspection robots can realize automatic and rapid inspection of insulators of ultra-high voltage transmission lines, which is an important guarantee equipment for the continuous safe operation of the national power grid. Aiming at the needs of ultra-high voltage insulator string inspection, an insulator robot is designed to realize efficient and stable insulator string motion and insulator detection, and the main work includes proposing a new insulator string motion robot configuration and realizing its string motion and inspection functions in the form of a physical prototype. It has been proved that the robot has a large motion load and strong motion performance, and can be adapted to the complex working conditions consisting of a variety of insulators within a certain size range.
Influence of different test methods on the accuracy of high current busbar insulation resistance
Authors: Wang Yulong , Li Jiangxu , Li Lili , Xia Bin , Huang Qinfa , Wang Chunquan 
Published: March 2024

Abstract
Compared with the traditional cable, the high current busbar fully embodies its superiority in the process of current transmission, and thus its insulation performance test is of great significance to the safe operation of the line. In this paper, the insulation resistance of the high current busbar is measured by the basic test principle and the voltage injection test method respectively, and then the accuracy and precision of the two test methods are compared. The test results show that the relative error of insulation resistance of positive and negative busbar fluctuates in the range of 0.35%-4.20% and 0.10%-3.33%, respectively, while that of voltage injection test fluctuates in the range of 0.60%-2.80% and 1.10%-1.80%, respectively. Regardless of the basic test principle or voltage injection test, the relative error of insulation resistance in the high current busbar is less than 5%, and the voltage injection test method is more accurate. Compared with the basic test principle, the maximum relative error of Rn
and Rp
is reduced by 0.87% and 1.00% respectively.
CVT error prediction method based on improved attention mechanism transformer model
Authors: Jiang Hanshu , Yang Jianrong , Li Yutian , Wu Guanghao , Liu Zhu , Zheng Yongming , Yang Qiang , An Xinyang 
Published: March 2024

Abstract
In order to enhance the performance of capacitive voltage transformer (CVT) error prediction, we propose a transformer model (AM-transformer) error prediction method based on an improved attention mechanism. The method starts from both input data and model improvement, adopting Pearson’s correlation coefficient to calculate the environmental factors that have a greater impact on the CVT measurement error, and enhancing the ability of local learning of the attention mechanism by adding causal convolution and data segmentation operations. The experimental results show that the mean absolute error (MAE), mean absolute percentage error (MAPE) and root mean square error (RMSE) of the method reach 0.016, 4.21% and 0.021, respectively, realizing a high prediction accuracy.
Analysis of multi-objective cooperative optimization strategy for residential load under extreme weather
Authors: Yu Houzhi , Zhang Shuxin , Guo Kaiyuan , Zhu Yaxuan , Zhang Jiahui 
Published: March 2024

Abstract
In recent years, the problem of seasonal power supply shortages in extreme weather has frequently occurred across China, which has brought great inconvenience to people’s production and life. At the same time, with the advancement of the energy revolution, the proportion of electric energy in the terminal energy is increasing, which also poses a severe challenge to China’s energy security. Our research, by constructing a residential electricity consumption model and conducting multiple electricity price response experiments, has collected data that assesses various factors involved in user responses. It has also explored and inferred the impact of these factors on user-side responses. This study introduces new research directions aimed at alleviating electricity supply-demand imbalances during different periods, contributing to the optimization and enhancement of the national power system.
The measurement error prediction method of voltage transformer based on TCN-RBF
Authors: Gao Shuai , Jiang Zhenyu , Liu Ying , Zhao Lin , Bai Yicheng , Hou Xinyi , Wei Xuepeng , Zhang Yin 
Published: March 2024

Abstract
Accurate prediction of voltage transformer error is an important guarantee for the stable and economic operation of the power grid. This paper presents a measurement error prediction method for voltage transformers based on time convolution and radial basis neural networks (TCN-RBF). Firstly, the ensemble empirical mode decomposition is used to decompose the original error sequence into multiple components. Secondly, a TCN prediction model was established based on each component and historical error sequence to achieve error prediction. To further improve the prediction progress, the RBF model was used to further fit the predicted results with the environmental parameter data and confirm the final predicted value. The operation error of the transformer in a substation is tested. The test results show that compared with LSTM, SVM, BP, and other prediction models, this method has better performance in error prediction.
Radiation tolerance of the MUX64 for the High Granularity Timing Detector of ATLAS
Authors: Wang C. , Xu Z. , Huang X. , Zhang L. , Sha Q. , Ge Z. , Che Y. , Gong D. , Hou S. , Zhang J. , Liu T. , Liang Z. , Zhang L. , Ye J. , Qi M. 
Published: March 2024

Abstract
The MUX64 ASIC is a 64-to-1 analog multiplexer to accommodate 64 inputs, with one
addressed to output for ADC readout. It is developed for monitoring of the Low-Gain Avalanche
Detectors (LGAD) detector modules in the High Granularity Timing Detector (HGTD) of the ATLAS
Phase-II upgrade. The MUX64 chips will be used in the radiation field of high-luminosity pp
collisions at LHC to an integrated luminosity of 4000 fb-1. This work presents
the radiation tolerance study for the MUX64 being tested with 80 MeV protons and X-ray exposures
for damages caused by Non-Ionizing Energy Loss (NIEL) and Total Ionizing Dose (TID), respectively.
The irradiated samples demonstrated tolerance to the NIEL to a fluence of 3.21 × 1015
(Si, 1 MeV) neq/cm2, and the TID of 7.46 × 105 Gy (Si).
Molecular sieve vacuum swing adsorption purification and radon reduction system for gaseous dark matter and rare-event detectors
Authors: Marcelo Gregorio R.R. , Spooner N.J.C. , Dastgiri F. , Ezeribe A.C. , Lane G. , McLean A.G. , Miuchi K. , Ogawa H. 
Published: March 2024

Abstract
In the field of directional dark matter experiments SF6
has emerged as an ideal target gas. A critical challenge with this
gas, and with other proposed gases, is the effective removal of
contaminant gases. This includes radon which produce unwanted
background events, but also common pollutants such as water, oxygen
and nitrogen, which can capture ionisation electrons, resulting in
loss of detector gas gain over time. We present here a novel
molecular sieve (MS) based gas recycling system for the simultaneous
removal of both radon and common pollutants from SF6. The
apparatus has the additional benefit of minimising gas required in
experiments and utilises a Vacuum Swing Adsorption (VSA) technique
for continuous, long-term operation. The gas system's capabilities
were tested with a 100 L low-pressure SF6 Time Projection
Chamber (TPC) detector. For the first time, we present a newly
developed low-radioactive MS type 5 Å. This material
was found to emanate radon at 98% less per radon captured
compared to commercial counterparts, the lowest known MS emanation
at the time of writing. Consequently, the radon activity in the TPC
detector was reduced, with an upper limit of less than
7.2 mBq at a 95% confidence level
(C.L.). Incorporation of MS types 3 Å and
4 Å to absorb common pollutants was found successfully
to mitigate against gain deterioration while recycling the target
gas.
New techniques method for improving the performance of the ALPI Linac
Authors: Bellan L. , Carletto O. , Comunian M. , Fagotti E. , Giacchini M. , Montis M. , Ong Y.K. , Pisent A. 
Published: March 2024

Abstract
The superconductive quarter wave cavities hadron linac ALPI
is the final acceleration stage at the Legnaro National
Laboratories. It can accelerate heavy ions from carbon to uranium up
to 10 MeV/u for nuclear and applied physics experiments. It is also
planned to use it for re-acceleration of the radioactive ion beams
for the SPES (Selective Production of Exotic Species) project. In
this article, we will present the innovative results obtained with
swarm intelligence algorithms, in simulations and measurements. In
particular, the increment of the longitudinal acceptance for RIB
(Radioactive Ion Beams) acceleration, and beam orbit correction
without the beam first-order measurements will be discussed.
The disappearing Antilles Current dominates the weakening meridional heat transport in the North Atlantic Ocean under global warming
Authors: Cai Jinzhuo , Yang Haiyuan , Chen Zhaohui , Wu Lixin 
Published: March 2024

Abstract
The Antilles Current (AC) off the Bahamas Islands is an important component for both wind-driven and thermohaline circulation system in the North Atlantic. The evolution of AC intensity could exert substantial impacts on mid-latitude climate and surrounding environment. For instance, an anomalous weaker AC is found to decelerate the nutrient transport in the shelf regions, risking the deep-water corals. In addition, a weaker AC could reduce the poleward heat transport of the Gulf Stream and the North Atlantic Drift and further influence the climate in Western Europe. Based on nine high-resolution coupled climate models, we find a 3.8 Sv weakening of the AC, which is equivalent to 63% of its climatology transport during 1950–2050. The deceleration of AC introduces a −0.17 PW of heat transport decrement, dominating the total heat transport change across 26.5° N. Further analysis reveals that change of AC is mainly attributed to the evolution of thermohaline circulation in a changing climate and is partly influenced by wind stress curl in the North Atlantic. Our finding highlights the needs to establish a long-term monitoring network for the AC and a comprehensive understanding of associated impacts.
Analysis of blade noise with different root boundary conditions considering fluid-structure interaction effect
Authors: Zhu Penghui , Jiang Jinhui , Cui Wenxu , Yang Hongji , Wang Lihui 
Published: March 2024

Abstract
It is of certain importance for noise reduction to investigate the relationship between the aeroacoustic characteristics of blade and root boundary conditions when considering the fluid-structure interaction (FSI) effect. In this study, a set of precise dynamic models and two-way FSI calculation methods are developed to predict the dynamic load and response of blades more accurately. The natural frequency inaccuracy of the blade model is kept within 5% by comparing the results of the modal test using the ploy-reference time domain method and adopting the sensitivity analysis method with the blade beam stiffness as the modification parameter. Besides, based on the numerical results from the computational fluid dynamics method considering the FSI effect, the aeroacoustic characteristics of blades with different root boundary conditions are analyzed by adopting the Ffowcs Williams-Hawkings equations. The aeroacoustic characteristics of the NACA blade in hover are thoroughly discussed, with emphasis on the impact of different root boundary conditions on rotation noise. The result demonstrates that, the sound pressure level (SPL) difference of loading noise can reach 1.4 dB between blades with various root boundary conditions, while the SPL difference of thickness is only 0.4 dB.
Effects of electrical pulse on metal deformation behaviors
Authors: Huang Tao , Yang Fan , Xing Bing-Hui , Song Ke-Xing , Xiang Nan , Zhang Yan-Min , Chen Xue-Wen , Guo Jun-Qing 
Published: March 2024

Abstract
As a kind of special energy field assisted plastic forming, electric pulse assisted plastic forming combines multiple physical fields, such as thermal, electrical, magnetic and mechanical effects, has multiple effects on metal. It has a good industrial application prospect in the fields of directional microstructure regulation of materials and preparation of new materials. The flow stress of metal materials can be effectively reduced by electro-pulse assisted forming. The action mechanism of pulse current includes thermodynamics (Joule heating effect) and kinetic (pure electro-plastic effect or athermal effect). Thermodynamically, electric pulses can be used to provide the energy for dislocation migration and atomic diffusion, and aid in microstructure changes such as recrystallization, phase transition and microcrack healing of metals. In terms of dynamics, electric pulse has an effect on the speed and path of dislocation structure evolution. On this basis, a series of theoretical models for accurately predicting the flow stress of materials in electrically assisted forming process were formulated by combining the stress–strain constitutive relationship considering the temperature rise effect and the pure electro-plastic effect. The accuracy of the predicting model is greatly enhanced by the introduction of electrical parameters. The mechanism for electrically assisted forming was further revealed.
Investigation of the anisotropic thermal expansion of PbIn6Te10 crystal by high temperature x-ray diffraction measurements
Authors: Zhang S , Du Y , Wang J , Peng J , Jin Z , Tang G , Huang W , Chen B , He Z 
Published: March 2024

Abstract
The PbIn6Te10 crystal, an IR laser frequency conversion material, grown via the Bridgman method with dimensions ϕ35 mm × 90 mm in a four-zone furnace, was subject to the investigation of its thermal expansion behavior using high-temperature x-ray diffraction in the range of 25–450 °C. Based on the obtained data, the average thermal expansion coefficients of 15.21 × 10−6 K−1 for α

a
and 6.44 × 10−6 K−1 for α

c
were determined utilizing the least square method. The study revealed that the linear and volume thermal expansion coefficients of PbIn6Te10 crystals satisfy the relationships α

a
> α

c
> 0, α

V
= 2α

a
+ α

c
, and α

a
increased while α

c
decreased with increasing temperature, accentuating a substantial anisotropy in thermal expansion between the crystal’s principal axes. A detailed exploration pinpointed that the variations in the PbTe6 octahedron primarily governed the changes in the PbIn6Te10 unit cells, with further investigation uncovering its association with variations in the nearest neighboring bonds, which is mainly related to Pb-Te4 and Pb-Te2 bonds. Additionally, the determination of temperature-dependent anisotropic thermal expansion coefficient α was complemented by calculating Grüneisen parameter

γ

using Quasi-harmonic Debye model. Remarkably, these parameters also exhibited anisotropic behaviors (

γ

⊥

increases with temperature whereas

γ

/
/

decreases, α
⊥ > α
∥), contributing additional insights into the crystal thermal characteristics.
Laziness, barren plateau, and noises in machine learning
Authors: Liu Junyu , Lin Zexi , Jiang Liang 
Published: March 2024

Abstract
We define laziness to describe a large suppression of variational parameter updates for neural networks, classical or quantum. In the quantum case, the suppression is exponential in the number of qubits for randomized variational quantum circuits. We discuss the difference between laziness and barren plateau in quantum machine learning created by quantum physicists in McClean et al (2018 Nat. Commun.
9 1–6) for the flatness of the loss function landscape during gradient descent. We address a novel theoretical understanding of those two phenomena in light of the theory of neural tangent kernels. For noiseless quantum circuits, without the measurement noise, the loss function landscape is complicated in the overparametrized regime with a large number of trainable variational angles. Instead, around a random starting point in optimization, there are large numbers of local minima that are good enough and could minimize the mean square loss function, where we still have quantum laziness, but we do not have barren plateaus. However, the complicated landscape is not visible within a limited number of iterations, and low precision in quantum control and quantum sensing. Moreover, we look at the effect of noises during optimization by assuming intuitive noise models, and show that variational quantum algorithms are noise-resilient in the overparametrization regime. Our work precisely reformulates the quantum barren plateau statement towards a precision statement and justifies the statement in certain noise models, injects new hope toward near-term variational quantum algorithms, and provides theoretical connections toward classical machine learning. Our paper provides conceptual perspectives about quantum barren plateaus, together with discussions about the gradient descent dynamics in Liu et al (2023 Phys. Rev. Lett.
130 150601).
Integrating life cycle assessment into the building design process—a review
Authors: Prideaux Fabian , Allacker Karen , H Crawford Robert , Stephan André 
Published: March 2024

Abstract
The environmental effects associated with buildings are significant and include considerable contributions towards global greenhouse gas emissions, energy use, and waste generation. Until recently, mitigation efforts have concentrated on improving the operational energy efficiency of buildings, largely ignoring embodied environmental effects. However, focusing solely on increasing energy efficiency can inadvertently cause an rise in embodied effects. It is therefore critical that embodied effects are considered alongside operational effects and are actively integrated into design decisions throughout the building design process. Life cycle assessment (LCA) can be used to achieve this, however, it is often perceived as difficult to incorporate into design workflows, or requiring specialist knowledge. Additionally, it is not always clear how well aligned LCA approaches are with the building design process. To address this gap, this study aims to provide a detailed analysis of LCA approaches, to assess how well they align with building design stages, and to identify key characteristics, including LCA tools and environmental data used to conduct assessments. A review of academic and grey literature is conducted. Three primary approaches are identified for integrating LCA into the building design process: simplified, detailed and incremental LCA. Simplified LCA uses streamlined data inputs and typically targets a specific design stage. Detailed LCA follows a traditional approach with comprehensive user inputs and results. Incremental LCA progressively evolves the assessment based on design requirements and available building data at each design stage. An analysis of each approach is performed, and key user requirements are mapped against the early design, and detailed design stages. Results reveal that no single approach fully satisfies all design requirements. Findings also highlight a lack of incremental LCA approaches and challenges operationalising these techniques. These approaches often rely on complicated methods or tools not suitable for common design workflows, or they are in early development and require additional verification before implementation.
Demands for DfD data characteristics: a step towards enabling reuse of prefabricated concrete components
Authors: Uotila Ulrika , Saari Arto , Joensuu Tuomo 
Published: March 2024

Abstract
Adoption of the design for disassembly (DfD) concept is suggested as a promising strategy to cope with the climate targets and increase circular economy in the construction sector. Yet, the concept is little used partially due to technical challenges, including inadequate information about demolition and the characteristics of components. This study aims to investigate the demands for information linked to new concrete components with the purpose of reuse. In the building phase, concrete components cause the majority of emissions. Thus, these components also have the greatest potential for CO2 emissions savings. A comprehensive list of information related to DfD concrete components and their characteristics was gathered in a workshop with experts of DfD concrete elements. Furthermore, the stakeholders of DfD components data processing were considered. The results of this study may support the adoption of DfD with concrete components as it provides information for designers and builders to implement in early phases of building projects.