bluuebunny/crossref_metadata_2025_split huggingface dataset:
Laser cladding of inconel 718 coating on stainless steel surface
Authors: Du Fengming , Zhang Yuhong , Mi Zetian , Shen Yan , Wang Jingsi , Wang Jinlong , Yang Yuxing , Liu Yu 
Published: February 2025

Abstract
An Inconel 718 coating was applied to the surface of 316L stainless steel to enhance its wear resistance. The coating’s phase composition, element distribution, microstructure, hardness, and wear resistance were analyzed. The results revealed that the Inconel 718 coating comprised the γ∼(Fe, Ni) solid solution, Ni3Nb, (Nb0.03Ti0.97)Ni3, and MCX (M = Cr, Nb, Mo). The coating achieved a maximum hardness of 640.2 HV0.2, which is more than three times that of the substrate. The main wear mechanisms of the coating are adhesive and abrasive wear, with a wear rate of 2.97 × 10−5 mm3 · N−1 · min−1. In the coating bonding zone, relatively coarse cellular and columnar crystals grew perpendicular to the planar crystals. The central region was predominantly composed of dendritic crystals, while a small amount of equiaxed crystals formed in the upper region. This work can provide guidance for surface strengthening of stainless steel.
Coaxial transition with very large diameter ratio of inner conductor using equal amplitude in-phase feeding
Authors: Qin Feng , Zhu Yuping , Geng Hui , Feng Jinghao , Wu Qiuyi 
Published: February 2025

Abstract
This paper presents a novel design for a broadband coaxial transition featuring a large inner conductor radius ratio. To establish the equivalence between a two-port matching network and the even mode of a symmetrical power splitting network, an equivalent circuit model of an ideal Tee junction is proposed. Subsequently, a highly integrated impedance transition model is developed by employing a double splitting strategy. Subsequently, a highly integrated impedance transition model is developed by employing a double splitting strategy. By adopting a symmetrical, in-phase, and equal-amplitude feeding strategy, the challenges associated with impedance matching and spurious mode suppression are effectively addressed. Furthermore, a symmetrical and equal amplitude in phase feeding strategy are introduced to the great challenges of impedance matching and spurious suppression can be overcome. In addition, the design complexity is alleviated by using the equivalence between the wrapped waveguide and a coaxial to reduce the numerical burden. A typical design example with the radius ratio of the inner conductor up to 1:25 is designed and fabricated. The simulated and measured results have proven the feasibility of the proposed method. It can be applied to broadband rotary joints that demand large hollow space through the center.
An analytic approximate solution for nonlinear drift-diffusion equation
Authors: Shweta S , Khurana Karizma , Kumar Rajesh 
Published: February 2025

Abstract
The drift-diffusion equation is a fundamental model used for modeling phenomena in physics, finance, biology, and engineering. Its applications span particle dynamics, molecular diffusion, asset pricing, population dynamics, and noise control systems. The wide range of its applications motivated us to address the non-linear problem semi-analytically via two advanced schemes: the Accelerated Homotopy Perturbation Elzaki Transformation Method (AHPETM) and the Optimized Decomposition Method (ODM). AHPETM combines the accelerated homotopy perturbation method with the Elzaki transform, while ODM employs linear approximations and Adomian polynomials. Through diverse test cases in 1-, 2- and 3-dimensions, we demonstrate AHPETM’s superior accuracy, computational efficiency, and capability to provide closed-form solutions as compared to the ODM and the well-established semi-analytical schemes, i.e., variational iteration as well as Temimi and Ansari methods. Furthermore, rigorous convergence analysis and derivation of worst-case error bounds validate the reliability of the proposed methods, establishing AHPETM as a robust and versatile tool for tackling complex nonlinear systems
A generalization of cell survival models via fractional approach
Authors: Şen Mürsel , Çalık Abdullah Engin , Senturk Ibrahim , Şirin Hüseyin 
Published: February 2025

Abstract
This study investigates the relationship between radiation dose and the number of surviving cells as a result of radiation treatment by revisiting and extending linear, quadratic, and linear-quadratic cell survival models using fractional calculus. The generalized version of these models, called as fractional cell survival model, offers a deeper insight into the mechanisms underlying cell survival. This model shows a good harmony with the experimental findings, and it is also generalized the standard models when the fractional derivative orders are equal to 1. This new approach not only makes cell survival predictions more accurate, but also gives us a better understanding of how radiation affects cells and how they respond.
Federated learning-based defect localization on metal surfaces using ensembled pretrained deep neural networks with feature fusion
Authors: Kansal Isha , Popli Renu , Khanna Divya , Sharma Vikas , Sharma Ashutosh , Kumar Rajeev , Khullar Vikas 
Published: February 2025

Abstract
This work proposes an effective approach towards effective classification of metallic surface defects by using feature extraction, feature reduction, deep neural networks and federated learning. The process starts with using the GC10-DET dataset which consists of 3,570 grayscale images of ten different types of defects on steel sheet namely punching, weld line, and oil spot among others. Firstly, the images are preprocessed and normalized where the dimensions of the images are resized to a certain size and also the images may be augmented to have similar format. The feature extraction is done by five Efficients models—B0 to B4, and this results in extracting 7,296 features for each image. Linear Discriminant Analysis (LDA) is then used, which projects feature space into nine significant features to enhance its readiness for classification. Classification is being performed through Deep Neural Network (DNN), Long Short Term Memory (LSTM), and Bi-directional LSTM (Bi-LSTM). Among these, EfficientNetB2 combined with LDA demonstrates superior performance, achieving a validation accuracy of 88.7446%, precision of 90.4545%, and recall of 86.1472%. Federated learning is employed to preserve data privacy while enabling collaborative model training across four clients, representing different data holders. The system shows impressive performance in both Independent and Identically Distributed (IID) and Non-IID data scenarios, with clients achieving up to 100% accuracy, precision, and recall under IID conditions, and rapid convergence to near-perfect accuracy under Non-IID conditions. These results highlight the methodology’s effectiveness in real-world industrial applications, where high accuracy and data privacy are paramount.
Probability density functions covering stretched exponential and stretched Cauchy distributions
Authors: Duan Lingjie , Duan Junsheng 
Published: February 2025

Abstract
A class of probability density functions with three parameters in terms of Mittag-Leffler functions is presented. The proposed distributions include stretched exponential and stretched Cauchy distributions as special cases, and stretched exponential distributions cover Gaussian and Laplace distributions. Heavy-tailed distributions are clarified as a subclass of the proposed distribution. For heavy-tailed distributions, a variance does not exist, nor does even a mean. Instead of the variance and kurtosis defined for stretched exponential distributions, a class of light-tailed distributions, we present two characteristic numbers, fractional order moment and centrality, applicable for heavy-tailed distributions to describe degree of variation of the corresponding random variable. The fractional order moment is defined as an absolute central moment of fractional power while the centrality is prescribed as the product of the full width at the half maximum and the peak value of the probability density function. Numerical simulations show the effectiveness of the proposed perspective and methods.
Fusion magnet quench risk increase with irradiation damage
Authors: John Jacob Maxwell , Gilbert Mark R , Hardie Chris D. 
Published: February 2025

Abstract
Superconducting material enables fusion reactor magnet concepts to operate with current densities that would melt materials with non-zero resistance. The application of superconducting material is considered essential for net-positive power machines. Catastrophic damage can occur when superconductivity is lost and the current generates heat. This scenario is called a quench. Stabilizer material carries the magnet current (typically copper) during a quench and is the focus of this work.&#xD;&#xD;Irradiation-induced defects store energy in the Cu crystalline lattice. The presence of defects reduces thermal conductivity (thermally insulating the superconductor), electrical conductivity (increasing temperature ramp rate during a quench), and specific heat capacity (increasing thermodynamic instability). The release of stored energy in the magnet materials, in combination with the magnet material property changes, has the potential to cause extreme off-normal events in superconducting magnets that worsen with fluence.&#xD;&#xD;Stored energy can be released causing local heating and increasing the risk of a quench. For example, following irradiation at 4.6K and a fluence of 0.45*10^18 n/cm^2, an energy release of 0.023 J/g was measured from Cu when increased in temperature from 10K to 18K, which would have been enough energy to create the same temperature increase spontaneously.&#xD;&#xD;Extrapolations of experimental data are used to estimate when spontaneous heating can occur due to the release of energy stored in irradiation-induced defects. Critical fluence values are estimated between 1.74*10^18 n/cm^2 and 2.85*10^19 n/cm^2 for neutron irradiation of Cu at a temperature of 20K.&#xD;&#xD;In-situ cryogenic calorimetry experiments, operated at high-temperature-ramp rates on irradiated magnet materials, could offer certainty for fusion magnet system designers. Periodic annealing of defects through controlled temperature cycling will be essential in fusion power plants to manage the increasing risk of quench as the superconducting magnets accumulate dose. The ideal frequency and dynamics of these maintenance temperature cycles will be established with further experimental examination. &#xD;
Numerical simulation of the heat release process of a novel aluminum-silicon phase change energy storage device
Authors: Dong Yuming , Fan Yi , Shi Zhengrong 
Published: February 2025

Abstract
High-temperature thermal energy storage technologies are important for addressing the energy supply-demand imbalance. For better using the aluminum-silicon PCM, a novel shell-tube heat storage and exchange device has been designed. In this paper, numerical simulations were conducted on the heat release process of the proposed device. We regard the inlet velocity and tube arrangement as influential parameters in the heat release process and analyze the performance of the device. The results show that increasing the inlet velocity effectively reduced the solidification time of the PCM within the device but also decreased the device’s utilization rate. Initially, the thermal release power was positively correlated with the velocity, but it later showed a negative correlation trend. Studies have indicated that the arrangement of PCM within a device has a significant impact on its performance, hence two PCM configurations have been proposed: triple-row and five-row arrangements. Compared to the triple-row arrangement, the five-row configuration exhibits a more complex airflow pattern, characterized by a wavy configuration at the inlet and an extended flow path. The utilization rate for the triple-row arrangement is 75.3%, while for the five-row arrangement, it is 78.6%, representing an improvement of 3.3%. The five-row arrangement significantly enhances the system’s utilization rate and heat transfer performance. These findings contribute significantly to the understanding of TES and can inform the direction of future advancements in this field.
Analysis of the impact of different inflow conditions on the wake and aerodynamic noise of wind turbines
Authors: Yang Hua , Liu Liguo , Wang Xiaofeng , Zhang Keming , Zhang Yigong , Chen Jian , Qin Jin , Ma Ran 
Published: February 2025

Abstract
This paper studies the aerodynamic performance and noise characteristics of a 6 MW horizontal axis wind turbine based on CFD fluid simulation and acoustic analogy method. The influence of different flow velocities on wind turbine wake and aerodynamic noise are compared. The result shows that: The main load source of the wind turbine is the shaft flow; the airflow through the engine room and the tower, the blade, and the tower will make the airflow speed through the wind turbine change, and form a large range of low-speed area in the rear of the wind wheel; the maximum axial velocity loss of wind turbine wakes at different sections under different flow speeds is located at the hub; the wake behind the wind turbine under high turbulence intensity obtains significantly higher energy than the low turbulence intensity during development; under different inflow velocity, the higher inflow velocity increases the aerodynamic noise, which is mainly affected by the tip vortex; under low turbulent intensity, different turbulence intensity has less influence on the wind turbine aerodynamic performance and aerodynamic noise.
Thermal analysis of novel polar thermal energy generating equipment
Authors: Cao Zhizheng , Ge Yunzheng , Liu Weimin , Chen Fengyun 
Published: February 2025

Abstract
To address the power supply needs of small scientific expedition equipment in the Arctic region, a 100W polar thermal energy generating equipment is proposed. This equipment harnesses the temperature difference between the cold polar air (averaging −34°C) and the seawater under the ice layer (averaging 0.12±0.18°C) to generate electricity. This paper provides a detailed explanation of the thermal cycle principles and the selection of working fluids, along with a thermal analysis of the equipment. The analysis reveals that the thermal efficiency of the system and the output work per unit of working fluid flow initially increase and then decrease as the turbine inlet pressure rises, with the inflection point occurring near the saturation pressure of the working fluid. The circulating thermal efficiency and output work per kilogram of working fluid flow are unaffected by the turbine inlet temperature but decrease significantly with rising condensing temperature. Under the same working conditions, R134a outperforms R227ea and R1234yf.
Mechanical mechanism of stress wave dissociation of flake graphite under micro-jet impact
Authors: Dong Xing , Jiang Yun , Guo Chenhao , Qu Fang , Chen Jifeng 
Published: February 2025

Abstract
Using a cavitating water jet to dissociate non-metallic minerals is a new method for processing non-metallic minerals. In this paper, to investigate the mechanical principles underlying the dissociation of flake graphite via micro-jet impacts generated by a cavitation water jet, the process of dissociating flake graphite by the cavitation water jet is analyzed using the water hammer principle and stress wave theory. It has been found that upon impacting on the flake graphite, the micro-jet produces hydraulic shock on its surface, initiates the propagation of stress waves within the flake graphite, and causes reflections and transmissions of stress waves at the interface between the flake graphite and water. Moreover, the stress direction of the reflected wave is opposite to that of the incident wave, which causes tensile stress inside the flake graphite; it is found that when the water hammer pressure exceeds the compressive strength of flake graphite and the tensile stress reaches the dynamic crack strength of the flake graphite, the dissociation of the flake graphite will be achieved. The reflection of the stress wave causes the flake graphite to undergo layer cracks, corner cracks, and core cracks. Under the combined action of these three cracking types, the flake graphite’s stress wave reflection dissociation is achieved. This research outcome further solidifies the mechanical foundation underlying the dissociation of flake graphite via a cavitation water jet.
SOH estimation of lithium-ion battery under complex operating conditions based on BP neural network
Authors: Xu Zuming , Li Yikai 
Published: February 2025

Abstract
The precise state of health (SOH) estimation and monitoring of lithium-ion batteries are extremely important for future BMS (intelligent battery management system). However, there is a lack of SOH estimation methods for complex on-board conditions in the existing research results. This research suggests a battery SOH estimate technique based on the battery’s CCCV (constant voltage and constant current) charging curve and BP neural network in order to solve this issue. Firstly, multiple health indicators are extracted and screened by analyzing the correlation between battery CCCV charging curve characteristics and battery SOH. Then, the lithium-ion battery data under complex operating conditions are corrected by the empirical capacity model, and the SOH estimation model of lithium-ion battery is constructed by using the BP neural network. In conclusion, this study trains and validates the model using battery aging experimental data from NASA (National Aeronautics and Space Administration). The results demonstrate that the model’s error is less than 5%, confirming the model’s efficacy.
Machine learning for real-time processing of ATLAS liquid argon calorimeter signals with FPGAs
Authors: Voigt Johann Christoph ,   the ATLAS Liquid Argon Calorimeter group
Published: February 2025

Abstract
To deal with the higher pileup after the high-luminosity upgrade of the LHC, the ATLAS
liquid argon calorimeter readout electronics will be replaced. 556 Intel Agilex-7 FPGAs will be
installed as part of the off-detector electronics, enabling a more sophisticated digital energy
reconstruction. Instead of using a linear optimal filter like the current readout, we evaluated
the use of recurrent and convolutional neural networks. These artificial neural networks are
trained on signal-enriched simulated detector pulses for a set of representative cells. The
network size is limited to approximately 500 multiply-accumulate operations per detector
cell. They show improvements in energy reconstruction especially for the case of overlapping
signal pulses, as they will appear more often under high-luminosity conditions. An FPGA prototype
firmware has been developed for both RNNs and CNNs, that supports processing the required number
of 384 detector cells on one FPGA. This uses a low-level VHDL approach to minimize the resource
usage. The ANN architecture is fixed at compile time, but the weights are configurable per
cell. The compilation results show that such a neural network based readout is feasible with the
available hardware. This is possible through the use of time multiplexing, i.e. by running the
FPGA at a multiple of the 40 MHz input data frequency.
Decline of antarctic circumpolar current due to polar ocean freshening
Authors: Sohail Taimoor , Gayen Bishakhdatta , Klocker Andreas 
Published: February 2025

Abstract
The Antarctic Circumpolar Current is the world’s strongest ocean current and plays a disproportionate role in the climate system due to its role as a conduit for major ocean basins. This current system is linked to the ocean’s vertical overturning circulation, and is thus pivotal to the uptake of heat and CO2 in the ocean. The strength of the Antarctic Circumpolar Current has varied substantially across warm and cold climates in Earth’s past, but the exact dynamical drivers of this change remain elusive. This is in part because ocean models have historically been unable to adequately resolve the small-scale processes that control current strength. Here, we assess a global ocean model simulation which resolves such processes to diagnose the impact of changing thermal, haline and wind conditions on the strength of the Antarctic Circumpolar Current. Our results show that, by 2050, the strength of the Antarctic Circumpolar Current declines by~20% for a high-emissions scenario. This decline is driven by meltwater from ice shelves around Antarctica, which is exported to lower latitudes via the Antarctic Intermediate Water. This process weakens the zonal density stratification historically supported by surface temperature gradients, resulting in a slowdown of sub-surface zonal currents. Such a decline in transport, if realised, would have major implications on the global ocean circulation.
The topography of Taiwan Island mitigates the damage of tropical cyclone disasters in southeastern China
Authors: Wu Jingwen , Zhang Yinchi , Zhu Laiyin , Yang Ruyuan , Su Tonghua , Wang Lan , Gao Lu 
Published: February 2025

Abstract
The intensity, structure, and path of tropical cyclones (TCs) are altered when they cross Taiwan Island, and this directly affects the severity of disasters in the southeastern coastal region of China, especially Fujian Province. Therefore, the extent of mitigating effect of Taiwan Island on Fujian Province-bound TCs requires investigation. Here, we classified 71 Fujian Province-bound TCs from 1984 to 2023 into two categories based on their track: Taiwan Island-crossing TCs (TCTs) and non-TCTs (nTCTs). We discovered that the duration of nTCTs was longer than TCTs, and nTCTs landing positions are more inclined to the southern Fujian Province with greater intensity as compared with TCTs. Due to the obstruction of Taiwan Island, the intensity of nTCTs with Fujian landfall was greater than that of TCTs cases. The disaster losses caused by nTCTs were significantly greater than those caused by TCTs. The number of victims, including deaths and missing people, as well as collapsed buildings, caused by nTCTs were three and two times greater than that caused by TCTs, respectively. Whether it is TCT or nTCT, the landing track and specific location determine the severity of the disaster. The damage caused by TCTs with southern tracks was more serious than that caused by TCTs with other tracks. The south -tracks caused more severe damage than north-tracks in the nTCTs category.
A micro-lung chip with macrophages for targeted anti-fibrotic therapy
Authors: Xia Jingjing , Dong Ruming , Fang Yongcong , Guo Jiabin , Xiong Zhuo , Zhang Ting , Sun Wei 
Published: February 2025

Abstract
Idiopathic pulmonary fibrosis (IPF) is a lethal lung disease of unknown etiology. Macrophages are implicated in the fibrotic process, but exhibit remarkable plasticity in the activated immune environment in vivo, presenting significant challenges as therapeutic targets. To explore the influence of macrophages on IPF and develop macrophage-targeted therapies, we engineered a micro-lung chip with a lung epithelium–interstitium tissue unit to establish a controlled immune environment containing only macrophages. We discovered that macrophages exacerbated inflammation and fibrosis by comparing microchips treated with bleomycin (BLM) in the presence and absence of macrophages. Based on the duration of BLM treatment, we established pathological models corresponding to inflammation and fibrosis stages. Transcriptome analysis revealed that activation of the PI3K-AKT signalling pathway facilitates the transition from inflammation to fibrosis. However, LY294002, a PI3K inhibitor, not only suppressed fibrosis and decreased the accumulation of M2 macrophages but also intensified the severity of inflammation. These findings suggest that macrophages play a pivotal role in the potential development at the tissue level. The micro-lung chip co-cultured with macrophages holds significant potential for exploring the pathological progression of IPF and elucidating the mechanisms of anti-fibrotic drugs.