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  • Open Access

    ARTICLE

    Linear and Non-Linear Dynamics of Inertial Waves in a Rotating Cylinder with Antiparallel Inclined Ends

    Mariya Shiryaeva1, Mariya Subbotina2, Stanislav Subbotin1,*

    FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.4, pp. 787-802, 2024, DOI:10.32604/fdmp.2024.048165

    Abstract This work is devoted to the experimental study of inertial wave regimes in a non-uniform rotating cylinder with antiparallel inclined ends. In this setting, the cross-section of the cylinder is divided into two regions where the fluid depth increases or decreases with radius. Three different regimes are found: inertial wave attractor, global oscillations (the cavity’s resonant modes) and regime of symmetric reflection of wave beams. In linear wave regimes, a steady single vortex elongated along the rotation axis is generated. The location of the wave’s interaction with the sloping ends determines the vortex position and the vorticity sign. In non-linear… More >

  • Open Access

    ARTICLE

    Influence of Bottom Inclination on the Flow Structure in a Rotating Convective Layer

    Andrei Vasiliev, Andrei Sukhanovskii*, Elena Popova

    FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.4, pp. 739-748, 2024, DOI:10.32604/fdmp.2024.048092

    Abstract The formation of convective flows in a rotating cylindrical layer with an inclined bottom and free surface is studied. Convection is driven by localized cooling at the center of the upper free surface and by rim heating at the bottom near the sidewall. The horizontal temperature difference in a rotating layer leads to the formation of a convective flow with a complex structure. The mean meridional circulation, consisting of three cells, provides a strongly non-uniform differential rotation. As a result of the instability of the main cyclonic zonal flow, the train of baroclinic waves appears in the upper layer. The… More >

  • Open Access

    REVIEW

    Hydrodynamic Cavitation Enhanced SR-Aops Degradation of Organic Pollutants in Water: A Review

    Xiufeng Zhu1,2, Jingying Wang1,*

    FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.4, pp. 671-692, 2024, DOI:10.32604/fdmp.2023.045260

    Abstract

    SR-AOP (sulfate radical advanced oxidation process) is a novel water treatment method able to eliminate refractory organic pollutants. Hydrodynamic cavitation (HC) is a novel green technology, that can effectively produce strong oxidizing sulfate radicals. This paper presents a comprehensive review of the research advancements in these fields and a critical discussion of the principal factors influencing HC-enhanced SR-AOP and the mechanisms of synergistic degradation. Furthermore, some insights into the industrial application of HC/PS are also provided. Current research shows that this technology is feasible at the laboratory stage, but its application on larger scales requires further understanding and exploration. In… More > Graphic Abstract

    Hydrodynamic Cavitation Enhanced SR-Aops Degradation of Organic Pollutants in Water: A Review

  • Open Access

    ARTICLE

    Preparation and Analysis of Carbon Fiber-Silicon Carbide Thermally Conductive Asphalt Concrete

    Zhiyong Yang, Enjie Hu, Lei Xi, Zhi Chen*, Feng Xiong, Chuanhai Zhan

    FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.4, pp. 705-723, 2024, DOI:10.32604/fdmp.2023.044030

    Abstract An experimental investigation into the thermal conductivity of CF-SiC two-phase composite asphalt concrete is presented. The main objective of this study was to verify the possibility of using SiC powder instead of mineral powder as the thermal conductive filler to prepare a new type of asphalt concrete and improve the efficiency of electrothermal snow and ice melting systems accordingly. The thermal conductivity of asphalt concrete prepared with different thermally conductive fillers was tested by a transient plane source method, and the related performances were measured. Then the temperature rise rate and surface temperature were studied through field heating tests. Finally,… More >

  • Open Access

    ARTICLE

    The Turbulent Schmidt Number for Transient Contaminant Dispersion in a Large Ventilated Room Using a Realizable k-ε Model

    Fei Wang, Qinpeng Meng, Jinchi Zhao, Xin Wang, Yuhong Liu, Qianru Zhang*

    FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.4, pp. 829-846, 2024, DOI:10.32604/fdmp.2023.026917

    Abstract Buildings with large open spaces in which chemicals are handled are often exposed to the risk of explosions. Computational fluid dynamics is a useful and convenient way to investigate contaminant dispersion in such large spaces. The turbulent Schmidt number (Sct) concept has typically been used in this regard, and most studies have adopted a default value. We studied the concentration distribution for sulfur hexafluoride (SF6) assuming different emission rates and considering the effect of Sct. Then we examined the same problem for a light gas by assuming hydrogen gas (H2) as the contaminant. When SF6 was considered as the contaminant… More >

  • Open Access

    ARTICLE

    Assessment of Particle Matter Pollution during Post-Earthquake Debris Removal in Adiyaman City

    Ercan Vural*

    Revue Internationale de Géomatique, Vol.33, pp. 37-50, 2024, DOI:10.32604/rig.2024.047908

    Abstract Severe earthquakes in the world and in Turkey can cause great loss of life and property, environmental problems and health problems. In addition to the loss of life and property, earthquakes are closely related to ecosystems, air, water, and soil pollution. Particularly in post-earthquake debris removal, very large amounts of particulate matter are released and may have negative effects on the health of the local population. This study aimed to detect two types of particle matter pollution during debris removal in 25 different locations in Adiyaman City using a CEM DT 9880 particle matter measuring device in May and August… More >

  • Open Access

    ARTICLE

    A Hybrid and Lightweight Device-to-Server Authentication Technique for the Internet of Things

    Shaha Al-Otaibi1, Rahim Khan2,*, Hashim Ali2, Aftab Ahmed Khan2, Amir Saeed3, Jehad Ali4,*

    CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3805-3823, 2024, DOI:10.32604/cmc.2024.049017

    Abstract The Internet of Things (IoT) is a smart networking infrastructure of physical devices, i.e., things, that are embedded with sensors, actuators, software, and other technologies, to connect and share data with the respective server module. Although IoTs are cornerstones in different application domains, the device’s authenticity, i.e., of server(s) and ordinary devices, is the most crucial issue and must be resolved on a priority basis. Therefore, various field-proven methodologies were presented to streamline the verification process of the communicating devices; however, location-aware authentication has not been reported as per our knowledge, which is a crucial metric, especially in scenarios where… More >

  • Open Access

    ARTICLE

    BCCLR: A Skeleton-Based Action Recognition with Graph Convolutional Network Combining Behavior Dependence and Context Clues

    Yunhe Wang1, Yuxin Xia2, Shuai Liu2,*

    CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 4489-4507, 2024, DOI:10.32604/cmc.2024.048813

    Abstract In recent years, skeleton-based action recognition has made great achievements in Computer Vision. A graph convolutional network (GCN) is effective for action recognition, modelling the human skeleton as a spatio-temporal graph. Most GCNs define the graph topology by physical relations of the human joints. However, this predefined graph ignores the spatial relationship between non-adjacent joint pairs in special actions and the behavior dependence between joint pairs, resulting in a low recognition rate for specific actions with implicit correlation between joint pairs. In addition, existing methods ignore the trend correlation between adjacent frames within an action and context clues, leading to… More >

  • Open Access

    ARTICLE

    Aspect-Level Sentiment Analysis Based on Deep Learning

    Mengqi Zhang1, Jiazhao Chai2, Jianxiang Cao3, Jialing Ji3, Tong Yi4,*

    CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3743-3762, 2024, DOI:10.32604/cmc.2024.048486

    Abstract In recent years, deep learning methods have developed rapidly and found application in many fields, including natural language processing. In the field of aspect-level sentiment analysis, deep learning methods can also greatly improve the performance of models. However, previous studies did not take into account the relationship between user feature extraction and contextual terms. To address this issue, we use data feature extraction and deep learning combined to develop an aspect-level sentiment analysis method. To be specific, we design user comment feature extraction (UCFE) to distill salient features from users’ historical comments and transform them into representative user feature vectors.… More >

  • Open Access

    ARTICLE

    Applying an Improved Dung Beetle Optimizer Algorithm to Network Traffic Identification

    Qinyue Wu, Hui Xu*, Mengran Liu

    CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 4091-4107, 2024, DOI:10.32604/cmc.2024.048461

    Abstract Network traffic identification is critical for maintaining network security and further meeting various demands of network applications. However, network traffic data typically possesses high dimensionality and complexity, leading to practical problems in traffic identification data analytics. Since the original Dung Beetle Optimizer (DBO) algorithm, Grey Wolf Optimization (GWO) algorithm, Whale Optimization Algorithm (WOA), and Particle Swarm Optimization (PSO) algorithm have the shortcomings of slow convergence and easily fall into the local optimal solution, an Improved Dung Beetle Optimizer (IDBO) algorithm is proposed for network traffic identification. Firstly, the Sobol sequence is utilized to initialize the dung beetle population, laying the… More >

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