bluuebunny/crossref_metadata_2025_split huggingface dataset:
Real-time improvement method of turbo-shaft engine component-level model based on dimensional reduction of residual iterative equation
Authors: Li Guochang , Zhou Wenxiang , Huang Xinsheng , Peng Wenhui , Shan Xiaoming 
Published: May 2024

Abstract
This paper explores a method to improve the real-time computation performance of turbo-shaft engine component-level model by reducing the dimensionality of residual equations set. For turbo-shaft engine, nozzle typically operates in a subcritical working state, assuming that the gas total temperature and pressure parameters of power turbine inlet are the same, and by assuming the gas flow balance between gas generator outlet and nozzle inlet, the iterative solution of the pressure drop of nozzle can be obtained. Then the pressure ratio of power turbine is naturally obtained, thereby achieving the objective of dimensionality reduction of the residual equations set. The component-level model’s steady-state and transient performance were simulated on a desktop computer with a clock frequency of 2.6 GHz. Simulation results show that, with a 2% margin of error, the steady state computation time for the component-level model was reduced by 54.8%, while the transient performance computation time was reduced by 18.6%. This represents a noticeable improvement in real-time performance. Simulation results on the P2020 embedded processor platform with an 800MHz clock frequency indicate a 22.3% reduction in single-step maximum transient performance computation time of the reduced dimensional model, compared to the original model. This demonstrates the effectiveness of dimensionality reduction of the residual equations set in enhancing the model real-time computation performance.
Simulation study on the breakup process of kerosene Gel Jet in transverse airflow
Authors: Zhou Ziqi , Wang Dong , Wang Yong , Xia Zhenjuan 
Published: May 2024

Abstract
The gel propellant not only inherits the characteristics of liquid propellants, such as high specific impulse, multiple ignition capabilities, and adjustable thrust, but also offers an advantage type of solid propellants, including reduced risk of leakage, long-term storage feasibility, and ease of maintenance. In this study, numerical simulations were conducted to investigate the atomization and mixing process of kerosene gel jets in high-speed crossflows. The study reveals that the jet breakup process primarily involves two forms of breakup: columnar breakup dominated by Rayleigh Taylor’s unstable wave and surface breakup dominated by Kelvin Helmholtz’s unstable wave. These two forms coexist, complement each other, and interact with each other. The numerical simulation of the kerosene gel breakup process provides favorable support for studying its combustion characteristics in the rotating detonation engine.
Simulated annealing-particle swarm optimization initial orbit determination method for too-short-arcs
Authors: Li Xinyang , Xie Chunlei , Zhang Qi , Xu Wuxin , Chen Zhihong 
Published: May 2024

Abstract
The initial orbit determination (IOD) of a non-cooperative satellite through space-based optical angle-only measurement data is a fundamental task. However, due to the lack of relative distance information of the targets, traditional methods have problems with poor accuracy and robustness in orbit determination results. The application of particle swarm optimization algorithm for IOD under optical too-short-arcs (TSA) measurement data has achieved good results. However, there is still a problem of convergence to local extremum. This article proposes a simulated annealing-particle swarm optimization (SA-PSO) hierarchical algorithm, which combines the efficient searchability of particle swarm optimization with the fine searchability of simulated annealing algorithm to achieve robust and precise optimization of non-cooperative targets orbit elements. The experimental results show the SA-PSO algorithm significantly improves the accuracy of orbit elements prediction compared to the particle swarm optimization algorithm and proves its effectiveness.
Obstacle avoidance motion planning for space redundant manipulator based on improved RRT algorithm
Authors: Ye Bin , Liu Chuankai , Han Fang , Hu Xiaodong , Chen Li 
Published: May 2024

Abstract
In addressing the challenge of obstacle-avoidance motion planning for space redundant manipulators operating in environments with obstacles, an improved method based on a rapidly exploring random tree (RRT) algorithm is proposed. The method first adopts a target probabilistic sampling strategy to enhance the target orientation. Secondly, an artificial potential field is constructed to steer the growth of the node tree in joint space. Subsequently, a collision detection model between the manipulator and obstacles is established based on the bounding capsule and bounding sphere in Cartesian space. Finally, the paths are pruned and smoothed with a cubic Bezier curve. The simulation results validate the method’s capacity to effectively plan a collision-free path for the space redundant manipulator and the joint motion trajectory is smooth.
Research on force-controlled polishing system for robotic arm based on compliance control
Authors: Xiao Jianming , Zhou Xinrui 
Published: May 2024

Abstract
This thesis enhances robotic arm control in intricate polishing environments by using impedance control for consistent force regulation between the arm and workpiece. An adaptive impedance control algorithm accommodates contact force variations, boosting system robustness. The PSO-BP variable impedance controller integrates particle swarm optimization and BP neural network for real-time optimization, overcoming limitations of fixed-parameter impedance control on surfaces with curvature changes. Experimental results show a significant reduction in polishing force fluctuations and improved force tracking. These findings support efficient robotic arm utilization in polishing tasks.
Research on longitudinal control technology in the transition section of tilt-rotor aircraft based on linear active disturbance rejection control
Authors: Xu Shaofeng , Chang Shaoping , Shi Pengfei , Wang Lin 
Published: May 2024

Abstract
To solve the problem of strong coupling and control redundancy in the transition section of the tilt-rotor, this paper presents a longitudinal control method based on linear active disturbance rejection control (LADRC), verified by simulation. Firstly, the nonlinear dynamics model of tilt-rotor aircraft based on the mechanism method is established, and the model’s accuracy is verified by comparing the trim result with the generic tilt-rotor aircraft simulation (GTRS) model verified by flight test in XV-15. Then, the control and redundant rudder surface assignment strategies for tilt-rotor aircraft are proposed. Then, the vertical and vertical control law of tilt-rotor aircraft is designed, the linear expansion state observer (LESO) model is analyzed and derived, and the linear active disturbance rejection controller suitable for attitude loop control of tilt-rotor is designed. The altitude and velocity loops are controlled. Finally, the proposed linear active disturbance rejection control (LADRC) controller is verified by simulation, and the whole process of tilting transition is simulated. The results show that the proposed control strategy and the controller designed in this paper have strong anti-disturbance ability, fast response speed, and high control precision and can be used in the transition section of tilt-rotor aircraft. The vertical direction shall be well controlled.
The research focuses on the interception guidance method during the boost phase
Authors: Xu Zhang , Peng Zeng , Xu Li , Heng Xue Jian , Rui Liu 
Published: May 2024

Abstract
To effectively intercept enemy ballistic missiles during the boost phase, the interceptor must possess high velocity and acceleration capabilities, necessitating a guidance mechanism capable of maneuvering precisely with the target. This paper analyzes the characteristics of booster phase interceptor missiles based on relevant research and establishes a trajectory simulation model. Considering the required guidance performance throughout the missile’s flight process, we design guidance laws for the initial, mid-course, and final stages to conduct trajectory simulations. The results demonstrate that the guidance law proposed in this paper outperforms the conventional guidance mechanism regarding miss distance, ballistic angle, and required overload. Moreover, it satisfies the interception accuracy requirements during the boost phase interception.
A forward design approach for fault thresholds in redundant flight control systems
Authors: Gao Xin , Zhang Junhong , Gong Lei 
Published: May 2024

Abstract
Modern fly-by-wire flight control systems use redundancy configurations to meet high safety requirements. The fault threshold value of the redundancy monitoring and voting algorithm affects the false alarm rate and missing alarm rate of the flight control system and the excessive false alarm rate and missing alarm rate reduce the reliability of the flight control system. Traditionally, the design of fault threshold is based on the empirical trial-and-error method, which suffers from the problem of unclear optimization direction. Forward design is needed to improve design efficiency and quality. In this paper, a forward design method for fault detection threshold is proposed to determine the upper limit value of the fault threshold by analyzing the effect of the voting signal change on the transient response of the aircraft when a channel fault occurs. The lower limit value of the fault threshold is determined by analyzing the channel history data. The effectiveness of the design method is demonstrated by digital simulation.
Trajectory tracking control of four-rotor UAV based on nonlinear extended state observer and model predictive control in wind disturbance environment
Authors: Chen Cen , Zhang Xiaoli , Peng Xiafu 
Published: May 2024

Abstract
In this paper, a novel hybrid controller utilizing a nonlinear extended state observer (NLESO) is introduced. According to the Newton-Euler equation, the four-rotor UAV is modeled and divided into the position subsystem and attitude subsystem. The position subsystem is controlled using the Model Predictive Control (MPC) algorithm. At the same time, the attitude controller utilizes the Sliding Mode Control (SMC) algorithm, which provides an enhanced level of responsiveness, resulting in reduced response times. The Nonlinear Extended State Observer (NLESO) is used in each controller in order to counteract the effects of disturbances. The findings obtained from the simulation experiments demonstrate that the controller design exhibits favorable tracking performance and robust resistance against external disturbances.
Modal frequency identification using the predictor subspace approach for a space solar power station
Authors: Ni Zhiyu , Wu Rui , Wu Chenchen 
Published: May 2024

Abstract
The system’s modal frequency parameters are determined by using a technique known as predictor-based subspace identification (PBSID), which is based on the dynamic properties of space solar power stations’ huge size and low frequency. First, the dynamic equation for the space solar power station with an Abacus configuration’s attitude-vibration coupling is developed. Additionally, the PBSID approach is used to build the relevant parameter matrix, and singular value decomposition (SVD) is chosen to evaluate the system’s structural frequency parameters. The right input signals are created via numerical simulation, and the best sensor placement technique yields the associated vibration response signals. The computing results then demonstrate that the modal frequency characteristics of the space solar power station may be successfully identified by the PBSID method, which is based on SVD. Additionally, the findings demonstrate the superior noise immunity capabilities of the PBSID algorithm when compared to the standard modal parameter identification approaches.
Low-thrust trajectory optimization of deep space exploration based on discrete pulse method
Authors: Qin Lin , Shang Haibin , Dong Yue , Zhao Zichen 
Published: May 2024

Abstract
Deep space exploration is gradually becoming the hot mission of human space activities, and this kind of mission has the characteristics of a long mission cycle, complex space environment, high fuel demand, and difficult telemetry track and command, etc. It is the future trend to carry out deep space exploration activities using low-thrust propulsion systems, and the trajectory optimization of interplanetary missions is one of the significant difficulties. Considering the characteristics and difficulties of interplanetary missions, a method of transfer orbit preliminary design in the multi-body system is proposed in this paper. The simulation results illustrate that the transfer orbit obtained by the method in this paper can provide a reliable initial guess for the optimization of high-precision orbit and decrease convergence sensitivity. The research results can provide a significant reference for the implementation of deep space exploration missions in China in the future.
Moderate Indian Ocean Dipole dominates spring fire weather conditions in southern Australia
Authors: Ren Xuya , Zhang Li , Cai Wenju , Wu Lixin 
Published: May 2024

Abstract
Patterns of the Indian Ocean Dipole (IOD) exhibit strong diversity, ranging from being dominated by the western tropical Indian ocean (WTIO) to by the eastern tropical Indian ocean. How the different types of the IOD variability patterns affect Australian fires differently is unknown, nor is it certain how the impacts may change under greenhouse warming. Here, we find that the moderate IOD, dominated by WTIO sea surface temperature (SST) variability, plays a primary role in affecting southern Australian fire weather conditions during austral spring. During a positive moderate IOD, broad-scaled warm SST anomalies in WTIO force an atmospheric stationary Rossby wave with a high-pressure anomaly over southern Australia. This elevated pressure and associated anomalous atmospheric conditions provide suitable fire weather with hot, dry, and windy conditions, raising fire risks in southern Australia. Such impact is distinctively different from that strong IOD-induced. As predicted by climate models, decreased moderate IOD variability in the future will result in weakened Australian fire weather responses.
Modulation of East Asian atmospheric rivers by the Pacific-Japan teleconnection pattern
Authors: Kwon Yeeun , Park Chanil , Son Seok-Woo , Kim Jinwon 
Published: May 2024

Abstract
Despite growing recognition that atmospheric rivers (ARs) play an important role in summer monsoon rainfall in East Asia, the AR variability related to low-frequency (LF) climate modes remains largely unknown. This study reports the significant control of the Pacific-Japan (PJ) teleconnection pattern on East Asian summer ARs. While Korea and central to eastern Japan experience more frequent, intense, and persistent ARs during the positive PJ, ARs in eastern China become more active during the negative PJ. Such AR activity changes are closely related to the PJ modulation of the western North Pacific subtropical high along which anomalous moisture transport organizes on the LF time scale. This finding suggests that the PJ pattern is an important source of East Asian summer AR variability and needs to be considered in medium-range forecasts of AR-related hydrological extremes.
Synthesis, mechanical and tribological behaviours of boron nitride reinforced AA7075 composites produced by stir casting technique
Authors: Kumar R Ranjith , Ravichandran M , Alagarsamy S V 
Published: May 2024

Abstract
This experimental investigation focused on synthesis of aluminium 7075-boron nitride (BN) composites (AA7075-BN), using stir casting technique. Four various proportions of BN of 0, 4, 8 and 12 wt% were used for the production of the composites. Scanning electron microscopy (SEM) was used to study the microstructure of the prepared composites. Using a pin-on-disc equipment, wear test was performed to analyse the tribological characteristics of the as-casted composites. The wear rate (WR) and the co-efficient of friction (COF) were determined by altering the input parameters, such as reinforcement (R), applied load (L), sliding velocity (V) and sliding distance (D). A grey relational technique (GRT) was applied to determine the appropriate conditions of parameters and showed low WR and COF for the composites. From the experimental results obtained, the least density of the composite was 2.70 g cm−3 for AA 7075–12 wt% BN. The mechanical properties of the composites were significantly improved. The highest tensile strength of 210 MPa was obtained from the same AA 7075–12 wt% BN. There was 26% of improvement in the tensile strength with 4 wt% of BN reinforcement in AA7075 matrix. Finally, the worn surface morphology confirmed plough and furrow formations on the AA 7075–4 wt% BN and AA 7075–8 wt% BN composites, respectively. Therefore, the applications of the various composites depend on their responses to the properties, as studied.
Model to identify comfortable cloth fabric for human body during thermal stress due to physical exercise
Authors: Patidar Neelam , Makrariya Akshara , Rasheed Rassol Hamed , Kumar Singh Nitish , Alsayah Ahmed Mohsin , Alshukri Mohammed J , Rathore Ram Krishna 
Published: May 2024

Abstract
Physical exercise enhances heat generation in human skin and subcutaneous tissues causing thermal stress. This thermal stress causes discomfort in the human body and deteriorates the physical performance of the human subjects. Appropriate choice of cloth for outer covering of human body is necessary to prevent this to provide comfort during the thermal stress. A mathematical model is proposed in this study to analyze the thermal stresses in human skin and subcutaneous tissues covered with various different cloth fabrics. The model considers four compartments namely cloth, epidermis, dermis, subcutaneous tissues. The bioheat equation along with appropriate boundary condition is employed in this model for one dimensional unsteady state case. The numerical simulation is performed using forward and central finite difference formulas. The findings have been utilized to examine how different types of fabric impact thermal stress experienced by the layers of human skin during physical activity. The polyester is found to be superior in comparison to cotton fabric as it shows less thermal stress and thus can be concluded to be more comfortable as a dress material.
Optimizing motor imagery BCI models with hard trials removal and model refinement
Authors: R Vishnupriya , Ramasubba Reddy MachiReddy 
Published: May 2024

Abstract
Deep learning models have demonstrated remarkable performance in the classification of motor imagery BCI systems. However, these models exhibit sensitivity to challenging trials, often called hard trials, leading to performance degradation. In this paper, we address this issue by proposing two novel methods for identifying and mitigating the impact of hard trials on model performance. The first method leverages model prediction scores to discern hard trials. The second approach employs a quantitative explainable artificial intelligence (XAI) approach, enabling a more transparent and interpretable means of hard trial identification. The identified hard trials are removed from the entire motor imagery training and validation dataset, and the deep learning model is further re-trained using the dataset without hard trials. To evaluate the efficacy of these proposed methods, experiments were conducted on the Open BMI dataset. The results for hold-out analysis show that the proposed quantitative XAI- based hard trial removal method has statistically improved the average classification accuracy of the baseline deep CNN model from 63.77% to 68.70%, with p-value =

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for the subject-specific MI classification. Additionally, analyzing the scalp map representing the average relevance scores of correctly classified trials compared to a misclassified trial provides a deeper insight into identifying hard trials. The results indicate that the proposed quantitaive-based XAI approach outperformes the prediction-score-based approach in hard trial identification.
Lung segment anything model (LuSAM): a decoupled prompt-integrated framework for automated lung segmentation on chest x-Ray images
Authors: Iytha Sridhar Rishika , Kamaleswaran Rishikesan 
Published: May 2024

Abstract
Accurate lung segmentation in chest x-ray images plays a pivotal role in early disease detection and clinical decision-making. In this study, we introduce an innovative approach to enhance the precision of lung segmentation using the Segment Anything Model (SAM). Despite its versatility, SAM faces the challenge of prompt decoupling, often resulting in misclassifications, especially with intricate structures like the clavicle. Our research focuses on the integration of spatial attention mechanisms within SAM. This approach enables the model to concentrate specifically on the lung region, fostering adaptability to image variations and reducing the likelihood of false positives. This work has the potential to significantly advance lung segmentation, improving the identification and quantification of lung anomalies across diverse clinical contexts.
Investigation on ultrasound images for detection of fetal congenital heart defects
Authors: S Satish , Rufus N Herald Anantha 
Published: May 2024

Abstract
Congenital heart defects (CHD) are one of the serious problems that arise during pregnancy. Early CHD detection reduces death rates and morbidity but is hampered by the relatively low detection rates (i.e., 60%) of current screening technology. The detection rate could be increased by supplementing ultrasound imaging with fetal ultrasound image evaluation (FUSI) using deep learning techniques. As a result, the non-invasive foetal ultrasound image has clear potential in the diagnosis of CHD and should be considered in addition to foetal echocardiography. This review paper highlights cutting-edge technologies for detecting CHD using ultrasound images, which involve pre-processing, localization, segmentation, and classification. Existing technique of preprocessing includes spatial domain filter, non-linear mean filter, transform domain filter, and denoising methods based on Convolutional Neural Network (CNN); segmentation includes thresholding-based techniques, region growing-based techniques, edge detection techniques, Artificial Neural Network (ANN) based segmentation methods, non-deep learning approaches and deep learning approaches. The paper also suggests future research directions for improving current methodologies.