bluuebunny/crossref_metadata_2025_split huggingface dataset:
Bending and torsional coupling study of rolling-piston compressor valves
Authors: Gao Wenzhao , Zhang Chaolei , Chen Debiao 
Published: January 2024

Abstract
In this paper, a model of a rolling compressor valve with one end fixed horizontally is presented and simulated using the flow-solid coupling (FSI) method for rolling rotor type compressors. Optimisation of the diagonally cut section can effectively reduce the pressure pulsation of the compressor. The results show that the valve blade generates coupled vibrations of bending and torsion, and the slant-cut structure improves the frequency of pressure pulsations, increases the stability of the compressor valve blade, optimises the compressor structure and reduces the pressure pulsations of the compressor.
Design and strength simulation of hub mechanism of variable pitch propeller
Authors: Ning Huizi , Zhong Bowen , Sun Lubin , Yu Zhiming , Zeng Chujing 
Published: January 2024

Abstract
The hub mechanism is an important force bearing mechanism of variable pitch propellers and an important actuator of variable pitch control in tilting ducted propeller UAV. To solve the problem of the connection between the blades and the fuselage of the tilting ducted propeller UAV, according to the parameters of the blades, the force of the hub mechanism is analyzed, and the design parameters of the hub mechanism are obtained by using the theoretical calculation method, such as the power density method. The strength of the parts is analyzed by using the finite element method. A variable-pitch propeller hub mechanism was developed for tilting ducted unmanned aerial vehicles. A design flow of the hub mechanism is formed, including the design of the parts of the hub mechanism and the strength check. This will facilitate the design and development of ducted UAVs.
Virtual maintenance simulation technology in civil aircraft engineering
Authors: Xia Jian 
Published: January 2024

Abstract
Based on the requirements and characteristics of civil aircraft maintainability design, virtual simulation technology is introduced into aircraft maintainability design, analysis, and verification. This paper presents the flow of virtual maintenance simulation through visual analysis, physical accessibility analysis, and operational space analysis. A method of virtual maintenance simulation accessibility analysis is presented. The evaluation of virtual simulation design is realized. In the design stage, through the virtual maintenance simulation analysis, the design factors affecting maintenance and potential maintenance hazards are found in advance. A timely improvement is made to improve the level of aircraft maintainability design and reduce later maintenance costs.
Design and numerical simulation analysis of a miniature Mixed-flow compressor
Authors: Li Zilin , Song Danlu , Wang Linsheng 
Published: January 2024

Abstract
This paper completed the pneumatic design of a mixed-flow compressor, adopted RANS turbulence model, and chose Spalart-Allmaras model to complete the numerical simulation of the flow field of the S1 flow surface, meridian flow surface, and impeller surface, and then analyzed the working performance at 90%, 100%, and 110% design speed to explore whether the mixed-flow compressor technology suitable for micro turbojet engines as well as the internal flow field flow state and loss mechanism. The results indicate that the shock wave at the front edge of the main blade and the low energy gas gathered at the tail edge of the main blade and the shunt blade, which causes serious flow blockage, are the main causes of the instability of the mixed-flow compressor at the design point. At 100% design speed, the compressor has higher reliability, stronger adaptability, and the best working performance for its working margin, isentropic efficiency, and pressure ratio with lower loss. The results may provide some references for the further optimization design of the current compressor.
Manufacturing process and raw materials of bearing windshield
Authors: Ma Yinglong 
Published: January 2024

Abstract
The windshield is an important part of the aircraft structure. In addition to providing a clear driving vision for the driver, it also needs to have certain strength and stiffness performance to meet the pressurization static load and impact dynamic load. At the same time, the windshield glass also needs to have a certain function of heating, anti-icing, and defogging. According to the application scenarios, the windshield can be divided into two types: bearing windshield and non-bearing windshield. Due to the requirement of weight, appearance, and security of the bearing windshield, it will become the mainstream design trend in the future. However, bearing windshield is composed of a wide variety of raw materials with different performances, the manufacturing process is complex, and the research and development verification tests are difficult. This paper introduces and summarizes the main difficulties and index requirements of the bearing windshield in terms of structural design, manufacturing process, and raw materials, and provides guidance and support for the subsequent airworthiness compliance verification of the bearing windshield.
Increasing gross primary productivity under soil warming and wetting on the Tibetan Plateau
Authors: Peng Qing , Jia Binghao , Lai Xin , Wang Longhuan , Huang Qifeng 
Published: January 2024

Abstract
The soil freeze-thaw process has undergone significant changes on the Tibetan Plateau (TP) in the context of global change, resulting in the changes of soil physical and chemical properties, thereby affecting the vegetation phenology and photosynthesis through affecting the utilization capacity of CO2 and light by vegetation. However, little is known about how soil temperature (ST) and soil moisture (SM) affect the gross primary productivity (GPP) on the TP at different seasons and elevations. In this study, the spatiotemporal variation patterns of GPP, ST, and SM were analyzed based on the Community Land Model version 5.0 (CLM5.0) simulations in order to illustrate the impacts of ST and SM in surface (0–10 cm) and root zone soil (0–100 cm) on GPP between 1979 and 2020. The results showed that the CLM5.0-based GPP and ST were in good agreement with in situ observations. ST, SM and GPP increased at the rates of 0.04 °C a−1, 2.4 × 10−4mm3 mm−3 a−1, and 5.36 g C m−2 a−2, respectively. SM dominated the variations of GPP in winter (64.3%), while ST almost was the dominant factor in other periods, especially spring (99.9%) and autumn (94.7%). The explanatory power of ST and SM for GPP increased with elevation, especially for ST. The relative contributions of ST and SM to GPP at different time scales in root zone soil were similar to those in surface soil. This study provided a new understanding of how soil freeze-thaw affected GPP changes on the TP in the context of the intensification of warming and humidification.
Quantum holographic surface anomalies
Authors: Drukker Nadav , Shahpo Omar , Trépanier Maxime 
Published: January 2024

Abstract
Expectation values of surface operators suffer from logarithmic divergences reflecting a conformal anomaly. In a holographic setting, where surface operators can be computed by a minimal surface in AdS, the leading contribution to the anomaly comes from a divergence in the classical action (or area) of the minimal surface. We study the subleading correction to it due to quantum fluctuations of the minimal surface. In the same way that the divergence in the area does not require a global solution but only a near-boundary analysis, the same holds for the quantum corrections. We study the asymptotic form of the fluctuation determinant and show how to use the heat kernel to calculate the quantum anomaly. In the case of M2-branes describing surface operators in the

N

=
(
2
,
0
)

theory in 6d, our calculation of the one-loop determinant reproduces expressions for the anomaly that have been found by less direct methods.
Estimation of cohesion for intact rock materials using regression and soft computing analyses
Authors: Köken E , Strzałkowski P , Kaźmierczak U 
Published: January 2024

Abstract
Abstract Shear strength parameters such as cohesion (c) and internal friction angle (ϕ) are among the most critical rock properties used in the geotechnical design of most engineering projects. However, the determination of these properties is laboring and requires special equipment. Therefore, this study introduces several predictive models based on regression and artificial intelligence methods to estimate the c of different rock types. For this purpose, a comprehensive literature survey is carried out to collect quantitative data on the shear strength properties of different rock types. Then, regression and soft computing analyses are performed to establish several predictive models based on the collected data. As a result of these analyses, five different predictive models (M1–M5) were established. Based on the performance of the established predictive models, the artificial neural network-based predictive model (model 5, M5) was the most suitable choice for evaluating the c for different rock types. In addition, mathematical expressions behind the M5 model are also presented in this study to allow users to implement it more efficiently. In this regard, the present study can be declared a case study showing the applicability of regression and soft computing analyses to evaluate the c of different rock types. However, the number of datasets used in this study should be increased to get more comprehensive predictive models in future studies.
Data-driven revision of coal spontaneous combustion risk classification for prevailing methods used in Australian mining industry
Authors: Zeng S , D’Hyon S , Widzyk-Capehart E 
Published: January 2024

Abstract
Spontaneous combustion poses persistent hazards in underground coal mining operations, threatening personnel and operations. To assess this risk, in Australia small-scale laboratory tests are being conducted using Adiabatic Oxidation (R70), Crossing Point (CPT) and Minimum Self-Heating Temperature (SHTmin) methods. The intrinsic spontaneous combustion propensity classification (ISCP) utilizes R70 results to establish a risk rating. This risk ranking provides guidance on the severity of spontaneous combustion ranging from low to extremely high, aiding in the implementation of preventive measures. However, The ISCP lacks supporting literature, and there is no existing literature on correlation between laboratory tests or risk matrix for CPT. This paper presents the results of a Spearman correlation study among R70, CPT and SHTmin based on a large historical database (n = 318) showing that only R70 and CPT can be used to reliably rank spontaneous combustion risk. It was found that CPT is strongly correlated with R70 (ρ = -0.8875), but SHTmin shows a weaker correlation with R70 (ρ = -0.7265). The hierarchical clustering analysis resulted in a revised risk ranking: Low (R70 < 0.4 °C/h, CPT > 156 °C), Medium (0.4 °C/h < R70 < 3 °C/h, 132 °C < CPT < 156 °C), High (3 °C/h < R70 < 11 °C/h, 102 °C < CPT < 132 °C), and Very High (R70 > 11 °C/h, CPT < 102 °C).
Identification of the oversized rock pieces in hydraulic hammer breaking process based on the scanner data geometry features analysis
Authors: Dąbek Przemysław , Kujawa Paulina , Wróblewski Adam 
Published: January 2024

Abstract
Due to the harsh conditions in the mining environment, it is difficult to fully automate some of the tasks carried out by mining machines and devices. As part of the technological process of extracting copper ore from Polish mines, the material is broken with a hammer to fit through the screen of a 40×40 cm square shape slot, after which it is loaded and conveyed for further processing. Usually, most of the material remaining on the screen cannot be considered oversized, additionally smaller particles can form blockages or rest on larger blocks. In this case, the crushing is not necessary, and only its movement may be sufficient. The focus of the presented research is on the identification of the particles that would be considered oversized, as it is a crucial task in the breaking hammer automation process. The authors propose a method based on the analysis of initially extracted 3D data copper ore blocks obtained from laser scanning at one of the transfer stations in KGHM Polska Miedź S.A., Polkowice-Sieroszowice mine. The difficulties of measurement are multiplied by the necessity of performing the scan from a single point of view, which was forced by safety concerns. Segmented but incomplete 3D data are processed, which results in finding the geometric features that prevent the material from going through the screen in an automatic manner.
Comparison of Hexcore and Poly-Hexcore computational meshes in the aspect of air flow modeling based on the actual geometry of mining excavations
Authors: Wróblewski Adam , Macek Arkadiusz , Bansiewicz Aleksandra , Wodecki Jacek 
Published: January 2024

Abstract
Discrete models are used in industry for many applications. In one of the most frequently used Finite Element Method (FEM) for Computational Fluid Dynamics (CFD) calculations, discrete models may be two-dimensional or three-dimensional. 2D models are used as a simplification to achieve satisfied results in the shortest computational time. 3D models, on the other hand, are used for more complex calculations. These models constitute a representation of real-world objects that have been appropriately simplified to make the calculations accurate and correct. The calculation time of a 3D model is significantly longer compared to a 2D model. For this reason, to reduce the calculation time, different types of simplifications and various types of discrete model meshes are used. In this paper, the authors made a comparison of two computational meshing technologies: Hexcore and Poly-Hexcore in the aspect of airflow modeling in mining excavations using CFD. The geometry considered in this case came from real-world excavations captured by laser scanning in the Gertruda Slant, Zloty Stok. Point cloud data was processed through feature extraction, which was subsequently utilized to create structured models of mining excavations. The results of the simulations show that taking into account such a diverse and complicated geometry and its significant lengths, reaching tens of kilometers, better results are obtained with the use of Poly-Hexcore mesh. This type of mesh allows simulations to be performed with similar accuracy in a shorter computation time. Utilizing a more modern type of mesh makes work more dynamic, which is of particular importance when conducting numerical simulations of air distribution in large and complex computational domains.
The influence of the void shape in the bearing capacity of rock mass with a superficial void
Authors: Alencar A , Galindo R , Dominguez-Quintans C 
Published: January 2024

Abstract
In this study is proposed a chart that allow estimating the reduction of bearing capacity due to the existence of a superficial void in a rock mass. It is contemplated the influence of different shapes and size of the void in relation to the foundation. The reduction of the bearing capacity is analyzed through the Finite Difference Method. In the numerical model, six possible cavity shapes are considered, with three different sizes and depths. Calculations are made considering eighteen types of rock masses, modelled by the H&B failure criterion. The results demonstrate that the critical depth where the cavity no longer influences the bearing capacity varies considerably depending on the geometric variables (size, shape and location of the void). In addition, it is observed that the relation between the bearing capacity obtained considering the rock mass with and without void is not affected by the geotechnical parameters of the H&B failure criterion. According to the results analyzed and graphic output, the variation in the stress distribution in the rock mass and the change of the failure mechanism under the different hypotheses studied can be observed. The results are presented in chart that facilitate to directly estimate the reduction of the bearing capacity of a rock mass with void based on geometric parameters.
Perturbative variational quantum algorithms for material simulations
Authors: Liu Jie , Li Zhenyu , Yang Jinlong 
Published: January 2024

Abstract
Reducing circuit depth is essential for implementing quantum simulations of electronic structure on near-term quantum devices. In this work, we propose a variational quantum eigensolver (VQE) based perturbation theory (PT) algorithm to accurately simulate electron correlation of periodic materials with shallow ansatz circuits, which are generated from adaptive derivative-assembled pseudo-trotter or qubit-excitation-based VQE calculations using a loose convergence criteria. Here, the major part of the electron correlation is described using the VQE ansatz circuit and the remaining correlation energy is described by either multireference or similarity transformation-based PT. Numerical results demonstrate that the new algorithms are able to accurately describe electron correlation of the LiH crystal with only one circuit parameter, in contrast with ~30 parameters required in the adaptive VQE to achieve the same accuracy. Meanwhile, for fixed-depth ansätze, e.g. unitary coupled cluster, we demonstrate that the VQE-based PT provides an appealing scheme to improve their accuracy.
Intercalation in Li-ion batteries: thermodynamics and its relation to non-ideal solid-state diffusion
Authors: Lagnoni Marco , Armiento Gaia , Nicolella Cristiano , Bertei Antonio 
Published: January 2024

Abstract
Intercalation is the key phenomenon taking place in lithium-ion batteries: while its thermodynamics sets the equilibrium voltage of active materials, solid-state diffusion of intercalated lithium determines the rate at which the battery can operate. This study revisits the thermodynamics of intercalation by treating the active material as a binary mixture of filled and empty sites, thus relating the equilibrium potential to the chemical potential difference of intercalated lithium. By setting a reference to unitary activity at half state-of-lithiation, the non-ideal behaviour of the active material is quantified via a revisited form of the thermodynamic enhancement factor, revealing that common solid-solution cathode materials as LiNi
x
Mn
y
Co1-x-y
O2, LiNi0.8Co0.15Al0.05O2, and LiCoO2 show strong super-ideal behaviour. The latter is related to the thermodynamic enhancement of the diffusion coefficient of intercalated lithium. A comprehensive overview of the functional forms of Li diffusion flux according to linear irreversible thermodynamics is provided and related to the chemical diffusion coefficient obtained by conventional characterisation techniques. A literature analysis made on solid-solution cathode active materials reveals that while the chemical diffusion coefficient varies significantly with state-of-lithiation, there exists a convenient functional form of diffusion flux according to linear irreversible thermodynamics that enables a fairly stable diffusion coefficient with state-of-lithiation. This has clear benefits from both modelling and experimental viewpoints and potentially sheds light on the mechanistic fundamentals of solid-state diffusion.
Treatment of acidic electroplating effluent from small scale industries using batch and continuous flow adsorption reactor
Authors: Anand A Mahesh , Jegathambal P , Jannet Sabitha , Mayilswami C 
Published: January 2024

Abstract
If electroplating effluent discharges aren’t properly treated, they have a detrimental effect on the aquatic ecology. The effluent characteristics comprise heavy metals that were toxic and causes carcinogenic effects. Among the conventional methods, adsorption being the most economically viable and technically straightforward. This study focuses on the removal of hexavalent chromium ion from the electroplating effluent using commercial activated carbon in both batch and continuous flow experiments. In column studies, various grades of commercial activated carbon were tested, with 80 × 200 mesh size yields complete Cr6+ removal. The batch study revealed that 83% removal was achieved at 5g of 80 × 200 mesh size activated carbon. The isotherm studies indicated a better fit with the Langmuir model and kinetics studies indicated pseudo-second order kinetics. Continuous flow experiments with an 80 × 200 mesh size activated carbon bed showed an upward trend in pH. However, Cr6+ removal efficiency decreased over time. UV–vis spectroscopy using the Diphenyl carbazide method confirmed Cr6+ concentrations. Morphological and elemental analyses were conducted using SEM and Edax, revealing significant changes before and after treatment. These findings underscore the effectiveness of activated carbon in mitigating the environmental impact of electroplating effluents, particularly in Cr6+ removal.
A boiler oxygen content and furnace temperature prediction model based on honey badger algorithm optimized neural network
Authors: Ji Zhaoyu , Tao Wenhua , Zhang Lingxiang 
Published: January 2024

Abstract
Aiming at the problem that it is difficult to accurately predict the oxygen content and furnace temperature during the combustion process inside the circulating fluidized bed boiler, this paper proposes a prediction model with a mixture of the convolutional neural network(CNN), bi-directional long-short term memory network(biLSTM), and honey badger algorithm(HBA). First, process variables related to furnace temperature and oxygen content were selected as input variables using actual test data from circulating fluidized bed boilers. Secondly, the parsed input variables are analyzed by CNN through an analytical mechanism to extract the data into smaller details and features, which are used as inputs to the biLSTM layer. The BiLSTM layer selectively memorizes the information of the input temporal data and learns the information dependence of the temporal data sequences, which then solves the temporal problem of the training of the irregular trend of the oxygen content and the furnace temperature. Finally, the HBA is utilized to continuously traverse and search the CNN-biLSTM model to find the optimal parameters of the model. The experimental results show: the CNN-biLSTM neural network model mixed with the HBA is able to accurately predict the oxygen content and furnace temperature. The experimental results show that the CNN-biLSTM neural network model with hybrid HBA is able to accurately predict the oxygen content and furnace temperature, and the average MAPE errors for the oxygen content are HBA-CNN-biLSTM (2.92E-03), CNN (7.96E-02), LSTM (5.13E-02), GRU (4.83E-02), RF (4.96E-02), RBF (8.41E-02), SVM (5.71E-02), RNN (5.53E-02), CNN-LSTM (4.79E-02).