bluuebunny/crossref_metadata_2025_split huggingface dataset:
Application of finite element analysis in wound sealing negative pressure drainage in the treatment of swelling
Authors: Han Jinying , Yin Zhimin , Luo Yi 
Published: October 2024

Abstract
Wound closure combined with negative pressure pump drainage technique is an emerging medical technology. This technique is widely used in various clinical fields and plays an important role in the treatment of various acute and chronic wounds. The fluid solid coupling porous elastic structure model is used to study the pressure distribution of negative pressure drainage wound when different negative pressure is applied. By using Abaqus software to construct the corresponding finite element model, the deformation of various types of negative pressure kits under different pressures, whether the pressure distribution is uniform, whether the drainage is smooth and so on are studied by computer calculation and analysis. The effects of different negative pressure on the internal pressure of the dressing are analyzed and compared, so as to find a way to drive and suck out an appropriate amount of residue. The improved finite element model provides theoretical basis and guidance for the design of negative pressure drainage device and an improved direction for the clinical application of this technology.
Analysis of static stress and vibration characteristics of the impeller in a tubular pump
Authors: Li Jian , Jin Yan , Song Xijie , Zhang Ye , Chen Hongcheng , Ni Debin 
Published: October 2024

Abstract
The tubular pump blade vibrates due to water flow excitation force and centrifugal force, which is susceptible to damage. This will lead to the abnormal operation of pump unit. To acquire the static stress and vibration characteristics of the impeller, a unidirectional fluid-structure coupling (FSC) method is adopted for static stress analysis and modal analysis. The results indicate that under different conditions, the static stress and displacement deformation law of the impeller are the same. The static stress increases as the radius decreases, with the maximum value occurring at the intersection of pressure surface and hub. The displacement deformation increases continuously with the expanding radius, and the highest value of deformation occurs near the shroud. The values of the maximum equivalent stress (MES) and maximum total deformation (MTD) of the impeller gradually decrease as the flow rate increases from 260L/s to 380 L/s. The natural frequency of the impeller is lower in wet mode compared to dry mode, and the additional mass of the water medium has different effects on each order. The research can be used as a reference for designing tubular pumps optimally and improving their stability.
Analysis of diversion ratio and study of sediment transport in the first canal station of an irrigation area based on Mike21 hydrodynamic model
Authors: Cui Yuna , Sun Yufeng , Wu Jinxin , Cheng Li 
Published: October 2024

Abstract
Based on MIKE21 hydrodynamic model, the change of diversion ratio and sediment transport at the first canal station in an irrigation area are analyzed. Two-dimensional numerical simulation is carried out by using MIKE21 FM hydrodynamic module, and the split ratio is studied. In the aspect of sediment transport, the transport path and deposition distribution of different sediment particle sizes are simulated by simulating sediment transport. The results show that under the lowest daily average water level, the diversion canal flow can meet the irrigation demand; The particle size of sediment has a great influence on the deposition distribution and thickness of the approach channel at the first station of the canal, and then affects the water diversion capacity of the pumping station.
Numerical investigation of the effect of the non-uniform intake flow on the unsteady flow and the excitation of the pump in a water-jet propulsion
Authors: Sun C , Dai Y X , Cai Y L , Wang Z L , Zhang H 
Published: October 2024

Abstract
Water-jet propulsions are widely used in high-performance ships. This study conducts numerical study on the unsteady flow of a complete water-jet propulsion. The internal flow field of the propulsion pump under the conditions of no installation of the shaft sleeve (and installation of the shaft sleeve. Spectrum analysis is used to compare the time-varying external characteristic and excitation characteristic under different conditions. Then, Dynamic Mode Decomposition technique is used to extract the high energy flow structures and corresponding frequencies. The results indicated that a large-scale vortex roll up above the driving shaft under the condition of rotational shaft, a pair of anti-rotation vortices appear behind the driving shaft under the condition of stationary shaft. These shaft induced vortices develop into unstable flow structures in the impeller region which moves relative to the impeller blades at rotational frequency. They further affect the unsteady flow in the guide vane region. The shedding vortices induced by the rotor-stator interaction are strengthened, while the passage vortices are weakened. Moreover, the dominant frequency of the passage vortex has decreased from 1.68 times the rotational frequency to 1.50 times the rotational frequency.
Optimum geometry of the Hydraulic Machinery impeller based on the response surface approximation surrogate model
Authors: Nguyen Duc-Anh , Kim Jin-Hyuk 
Published: October 2024

Abstract
Centrifugal pumps are known for their simplicity, reliability, and versatility, making them a preferred choice for a wide range of fluid transfer applications. Improving pump performance has an important meaning in saving energy and protecting the environment. Therefore, the impeller of the centrifugal pump in this study was optimized to improve efficiency at the best efficiency point based on the Response Surface Approximate surrogate model and Genetic Algorithm. To be able to capture the separation flow, numerical simulations are carried out using the Reynolds-averaged Navier-Stokes (RANS) equation and a Shear Stress Transport (SST k − ω) reattachment modification turbulence model with small y+ values at all wall surfaces. Experiments based on the base prototype are performed to confirm the reliability of the numerical simulation results. Two crucial parameters at the hub of the impeller are selected as design variables. The design points of these two design variables are initialized in the design space by Latin Hypercube Sampling method. Using a Genetic Algorithm, the optimum impeller model is identified with an efficiency increase of 1.445% and a power consumption decrease of 7.37% compared to the base model at the best efficiency point. After optimization, the elimination of separation flow at the leading edge of the impeller, arising from a mismatch between the impeller blade angle and flow angle, is obtained successfully resulting in the noteworthy reduction of the energy loss inside the impeller passage.
Study on the Internal Flow Characteristics of High Flowrate Emergency Drainage Series-parallel Pump
Authors: Tian Ding , Si Qiaorui , Liang Kang , Zhang Yong , Ju Yuanzhe , Yuan Jianping 
Published: October 2024

Abstract
Floods have become the main natural disaster threatening the safety of peoples lives and property. It is of great significance to develop high flow emergency drainage equipment. An innovative structure of pumps with high flow rate and multiple operating conditions is proposed in this paper to achieve series and parallel operation. It established an automatic optimization platform that integrates functions such as 3D modeling, mesh generation, computational fluid dynamics, and scheme optimization, and developed an efficient hydraulic model for a volute mixed flow pump combining flow field diagnostic techniques. The research results indicate that the inlet distortion of the secondary stage pump is the main cause of pump performance loss for both series and parallel operation condition. The third-generation vortex identification method was used to diagnose the internal flow of the pump under two operating conditions and control strategies were proposed. The final optimization scheme show that the pump can reach 1800 m3/h with a head of 9.6m and efficiency of 80% in parallel operation condition. In series operation condition, the pump can reach 900 m3/h with a head of 18.3m and an efficiency of 75.3%.
Optimization of Dual-Turbine Hydraulic Torque Converter Based on Meta-model of Optimal Prognosis
Authors: Zhou He-Jun , Zhu Geng-Hui , Yang Yi-Ming , Liu Quan-Zhong 
Published: October 2024

Abstract
The internal flow field of a specific model of hydraulic torque converter exhibits turbulence, resulting in suboptimal efficiency under the designed operating condition. This study aimed to improve the peak efficiency of the hydraulic torque converter by optimizing its design parameters. Computational fluid dynamics (CFD) analysis identified turbulence predominantly within the pump impeller region. Parameterized modeling of the pump blades was conducted, and an automatic optimization process was implemented. A Meta-model of Optimal Prognosis (MOP) was developed based on 250 sample points, and was then utilized to continuously optimize the blade parameters through evolutionary algorithm (EA). The results indicate an increase in the efficiency of the optimized torque converter from 82.2% to 84.34%, accompanied by a widening of the high-efficiency range (η≥75%) from 2.26 to 2.44. Furthermore, the torque coefficient of the impeller was enhanced.
Blade Airfoil Optimization and Its Impact on Vertical Axis Wind Turbine Performance
Authors: Zhang R Y , Li D Y , Wei X T , Chang H , Wang H J 
Published: October 2024

Abstract
Amidst the emergence of crises in petroleum prices and supply, the imperative for the development of clean energy has become increasingly apparent. Vertical axis wind turbines (VAWT), as a type of wind turbine, still grapple with challenges such as low wind energy utilization and sensitivity to dynamic wind speeds. This study focuses on optimizing the airfoil of a two-dimensional vertical axis wind turbine and analyzes the performance variations in a three-dimensional model. Following the optimization, the average power coefficients of the dual-blade two-dimensional VAWT increased by 7.9% and 4%, respectively, while those of the dual-blade three-dimensional model rose by 7.9% and 1.2%. However, the performance of the three-dimensional model was compromised due to the influence of tip vortices, resulting in inferior performance compared to the two-dimensional model. Both three-dimensional optimized blade designs exhibited a substantial reduction in the flow separation region downstream and improved pressure distribution fluctuations caused by the shedding of tip vortices, leading to decreased pressure differentials. Along the spanwise section, the power coefficient gradually decreased from the central segment to the tip segment. Notably, the power coefficient of the optimized blades at the tip segment increased significantly, accompanied by an augmented pressure differential between the upper and lower surfaces. This augmentation contributed to a significant enhancement in lift, thereby facilitating the rotation of the vertical axis wind turbine.
Failure analysis and treatment of sealing gland bolts for bulb turbine expansion joints
Authors: Liu Bo , Li Le , Zeng Zuopeng , Guan Peng , Liu Zhong , Yin Xinyuan 
Published: October 2024

Abstract
The sealing gland and sealing strip are the main means of waterproofing the expansion joint of the bulb turbine. Fracture Failure of the sealing gland bolts will lead to sealing failure, causing water leakage and even flooding of the plant accident. Aiming at the fracture failure of sealing gland bolts for bulb turbine expansion joints, samples were taken from the fracture A2-70 stainless steel bolts and 8.8 grade high-strength carbon steel bolts. Combined with physical and chemical inspection, vibration testing and finite element simulation analysis, the reasons for the fracture of sealing gland bolts were studied, and corresponding preventive measures were proposed. Research results show that bolt fracture failure is not caused by quality problems of the bolt itself, but by alternating unidirectional plane bending fatigue loads with low stress levels. The fracture failure of the gland bolts can be prevented by increasing the fatigue strength of the gland bolts, adjusting the on-cam relationship to reduce unit vibration, installing spherical washers, and adding sealing gland jack screw to reduce the impact of unit vibration on the sealing gland bolts. The research methods and results can provide scientific basis and reference for the operation and maintenance of connecting bolts of important components of hydroelectric projects, including expansion joint gland bolts.
Effects of temperature on Two-point statistical characteristics in turbulent jets
Authors: Li Hongru , Lai Huanxin 
Published: October 2024

Abstract
large eddy simulations are carried out for jets at Mach number 0.9, temperature ratio 2.0 and 3.4. Simulations are validated by comparing with experiments from literature. Two-point correlation- and coherence- functions are analyzed. Results show that the increment of jet temperature affects the decay rate of correlation functions. The correlation functions are analyzed both in space and time by employed a normalization method. The normalization coefficient is found changing with the temperature. Compared to spatial normalization coefficients, the time normalization coefficient is found more sensitive to the temperature. The coherence function is found asymmetric in the upstream and downstream of the reference point. The present attempt to construct an empirical model to normalize the coherence function, so as to provide reference for the study of acoustic field.
Investigation of cavitation with air injection using Eulerian-Lagrangian method
Authors: Li Linmin , Shen Bohan , Cheng Xiang , Zhu Zuchao 
Published: October 2024

Abstract
Air injection can be used to reduce the cavitation erosion in fluid machinery. However the inverse result that the injected air indeed increases the size of cavitation may be obtained. To find out the interaction between air injection and cavitation, the present work proposes a Eulerian-Lagrangian method to investigate the effect of air injection on the characteristics of cavitating flow. The Eulerian method is used to describe the liquid and vapor distribution, and the morphology of large cavities are tracked by the Volume of Fluid (VOF) method in the Eulerian frame. On the other side, the Lagrangian method is used to track both air and vapor bubbles in small scale. With the Eulerian-Lagrangian coupling, discrete micro bubbles in sub-grid scale as well as the large cavities can be well captured and simulated. This work takes two cavitation situations in different cavitation numbers of σ = 0.81 and 0.70 into account. The cavitation features in σ = 0.81 are mainly characterized by the intermittent shedding of small-scale cavities under re-entrant flow mechanism. For σ =0.70, the injected air flow plays an important part which enhances the scale of cavity. For both cases, simulated results of the cavity shapes and distribution of discrete bubbles anastomoses well with experimental results, which verifies the accuracy of the algorithm. The interaction between injected air and vapor is also analysed.
Study of Load-based Energy Saving for Multi-layer Networks on Base Station
Authors: Zhang Lili , Zhu Wenxin , Zhang Lichi 
Published: October 2024

Abstract
With the rapid deployment and widespread popularization of 5G technology, mobile networks have achieved wider frequency spectrum, more efficient data transmission, and larger capacity, providing users with unprecedented experiences. However, the multi-band technology applied by large urban base stations to meet the demand for high-speed internet experience has also led to a significant increase in energy consumption. It also receives a growing number of attentions from engineers and researchers, due to the increasing awareness of energy consumption issues. This paper proposes load-based energy-saving algorithm for multi-layer network on base stations. Through dividing cell into group based on the same coverage area and dynamically switch off and reactive cells strategies, the aim is to achieve a significant reduction in power consumption while ensuring network transmission efficiency.
Heart Failure Prediction Based on Broad Learning System
Authors: Ao Licheng , Cai Junyan , Lin Yifeng , Yang Yuer 
Published: October 2024

Abstract
Heart failure is a prevalent and serious cardiovascular condition characterized by the heart’s inability to pump blood to meet the body’s demands adequately. Current research on heart failure prediction primarily relies on conventional clinical assessment methods, traditional machine learning techniques, and traditional deep learning methods. Efficient and accurate heart failure prediction is a significant challenge due to its complex and multifactorial nature. In this study, we propose a heart failure prediction approach utilizing a broad learning system (BLS) that has the potential to capture intricate patterns in the data and enhance prediction accuracy. To evaluate our approach, we utilize an extensive dataset compiled from five previous independent datasets from the Cleveland, Hungary, Switzerland, Long Beach VA Hospital, and Stalog (heart) datasets. Experimental results demonstrate the effectiveness and efficiency of the BLS model, with a training time of 0.36 seconds and testing accuracy of 90%, precision of 88%, recall of 96%, and specificity of 82%, showcasing its potential performance for accurate heart failure prediction.
A Fetal Health Classification Approach Based on Broad Learning System
Authors: Li Mingxuan , Lin Yifeng , Yang Yuer 
Published: October 2024

Abstract
Fetal health problems are still a serious issue nowadays, affecting mothers and their children. The rate of mortality caused by fetal health problems is notably high in some areas of the earth, especially in lower-income countries. At present, besides the conventional clinical assessment, the methods of fetal health classification are mainly traditional machine learning and deep learning, such as KNN, SVM, Logistic Regression, and Naive Bayes, with the problems of low precision or long training time. In this study, we apply the broad learning system (BLS) to fetal health classification. The data set is sourced from the UCI ML repository database, which is made available by the Biomedical Engineering Institute and the University of Porto’s Faculty of Medicine. With the training accuracy of 92%, training time of 0.52s, and testing accuracy of 90%, the experimental results that highly satisfactory on BLS in the experiment.
UAV Position Optimization for Servicing Ground Users Based on Deep Reinforcement Learning
Authors: Gao Feiyu , Wang Zichen , Liu Xuan , Liu Shumei 
Published: October 2024

Abstract
A Deep Q-Network (DQN) algorithm is proposed for optimization of UAVs, which can increase the communication rate of multiple users within a certain area. The UAV is able to automatically adjust its position in 3D by means of the DQN Agent’s design and training, and then get the best UAV placement location. Furthermore, the Double Deep Q-Network (Double DQN) has been researched. It has been proved that this method has higher efficiency and higher convergence rate compared with traditional DQN for locating optimal UAV position. In this paper, we perform a complex simulation of a random distribution of users in a simulated region. The experimental results indicate that UAV is able to locate the optimal position with maximum mean transfer rate, and reduce the distance from central point to customer centre, thus increasing the communication quality. This study not only verifies the effectiveness of deep reinforcement learning in dynamic positioning optimization, but also provides new insights for the optimization design of future intelligent communication systems.
Spatio-temporal Evolution of Total Nitrogen in Xixi River Based on Sentinel-2 Remote Sensing Images
Authors: Wei Chenyan , Fu Haiyan , Zheng Yuanmao 
Published: October 2024

Abstract
Remote sensing technology holds significant advantages in the analysis of aquatic ecological environments, including rapid processing speed, abundant information, extensive spatial coverage, and high reliability. Total nitrogen, as a key indicator for assessing the eutrophication state of water bodies, has important application value in evaluating aquatic ecological environments and water quality monitoring. By analyzing the spatiotemporal changes in the concentration of total nitrogen, the dynamic changes in water quality can be effectively reflected. This study selected the Xixi River in Tong’an District, Xiamen City, as the research subject, using six Sentinel-2 satellite remote sensing image data from 2018 to 2023 to construct an empirical regression model for remote sensing inversion of the total nitrogen concentration in the study area. The spatiotemporal evolution of the research results was analyzed, to achieve real-time monitoring and assessment of water quality. The study results indicate that from 2018 to 2023, the total nitrogen concentration in the Xixi River showed a cyclical fluctuation pattern of first increasing, then decreasing and increasing again. The concentration reached its lowest in 2021, at 2.415 mg/L, and the research findings can provide important support for the sustainable development of the river.
Improving the UNet with channel attention mechanism for Taihu Lake water body recognition
Authors: Nie Shiliang , Zhao Limin , Jiang Mingyong , Li Zhiliang , Liu Shumin , Li Jiaguo , Wan Wei , Sun Yuan 
Published: October 2024

Abstract
Accurate recognition of surface water bodies is important for disaster management and resource planning. To explore a higher-precision water body recognition method, propose an improved channel attention mechanism UNet (ECA-UNet) water body recognition model based on Sentinel-2A remote sensing images. Utilizing ECA-UNet, UNet, PSPnet, and DeeplabV3, as well as the traditional normalized water body index (NDWI), recognize the water body in the Taihu Lake area. Through comparative analysis, the following main conclusions are drawn: (1) The recognition accuracy of the deep learning network model is better than the traditional NDWI method, among which the ECA-UNet network model has the highest accuracy of 98.67%, and the lowest recognition accuracy of NDWI is 89.06%. (2) The ECA-UNet network model can effectively extract water body recognition targets, has a better recognition effect on local features of water bodies, and can improve the water body extraction effect. The above results show that the improved channel attention mechanism ECA-UNet has the highest accuracy in water body recognition in Taihu Lake, which provides a reference for subsequent research and applications in this field.
A land parcel segmentation method for remote-sensing images based on an improved U-Net network
Authors: Wang Zitang 
Published: October 2024

Abstract
Land parcel segmentation in remote-sensing images aims to achieve pixel-level content analysis of the images, extracting and classifying categories of interest within the remote-sensing data. It holds significant practical value in areas such as urban and rural planning, flood control, and disaster relief, attracting widespread attention in the industry. With the continuous development of remote-sensing technology, deep learning has demonstrated substantial potential in the analysis of remote-sensing images. In this study, leveraging deep learning techniques to address the challenge of land parcel segmentation in remote-sensing images, we employed the U-Net architecture and further enhanced it by incorporating channel and spatial attention mechanisms. This improvement aims to enhance the model’s ability to identify complex land parcel boundaries and structures, ultimately achieving more accurate land parcel segmentation.