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  • Open Access

    PROCEEDINGS

    Fragment Penetration Damage Characteristics of Typical Composite Armor

    Yuan Li1,3,*, Zhiqiang Fan1,2, Tao Suo1,3

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.30, No.3, pp. 1-2, 2024, DOI:10.32604/icces.2024.013336

    Abstract Light armored vehicles, as the primary means of force transport on contemporary battlefields, require not only high mobility but also better protection to meet the complex battlefield environment and mission requirements. Composite armor is widely used in the design of light armored vehicles due to its lightweight and excellent defensible performance. In this paper, the damage law of the composite armor of an infantry fighting vehicle, when penetrated by fragment-simulated projectiles (FSP), is studied by numerical simulation, and the homogeneous equivalent targets surrogating a combination of local protective armor and vulnerable parts are constructed based More >

  • Open Access

    ARTICLE

    A Discrete Multi-Objective Squirrel Search Algorithm for Energy-Efficient Distributed Heterogeneous Permutation Flowshop with Variable Processing Speed

    Liang Zeng1,2,3, Ziyang Ding1, Junyang Shi1, Shanshan Wang1,2,3,*

    CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 1757-1787, 2024, DOI:10.32604/cmc.2024.055574 - 15 October 2024

    Abstract In the manufacturing industry, reasonable scheduling can greatly improve production efficiency, while excessive resource consumption highlights the growing significance of energy conservation in production. This paper studies the problem of energy-efficient distributed heterogeneous permutation flowshop problem with variable processing speed (DHPFSP-VPS), considering both the minimum makespan and total energy consumption (TEC) as objectives. A discrete multi-objective squirrel search algorithm (DMSSA) is proposed to solve the DHPFSP-VPS. DMSSA makes four improvements based on the squirrel search algorithm. Firstly, in terms of the population initialization strategy, four hybrid initialization methods targeting different objectives are proposed to enhance… More >

  • Open Access

    PROCEEDINGS

    The Utilization of Neutron Diffraction and Imaging Characterization Techniques in Engineering Materials

    Lixia Yang1,*, Danqi Huang1, Zongxin Liu2, Lei Zhao1, Xuejing Shen1, Haizhou Wang1

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.29, No.4, pp. 1-2, 2024, DOI:10.32604/icces.2024.012690

    Abstract Neutrons possess unique advantages in the study of element and component distribution, internal damage defects, crystal structure, and multi-scale stress field evolution of engineering materials due to their strong penetrating ability, sensitivity to light elements, and non-destructive properties. This study introduces the application of neutron diffraction technology for characterizing residual stress in full-size high-speed iron wheels and neutron imaging technology for three-dimensional characterization of hydrogen distribution in titanium alloys treated with hot hydrogen.
    Residual stress plays a critical role in the design, manufacturing, assembly, and service life cycle of wheel structures. It is a significant factor… More >

  • Open Access

    ARTICLE

    Numerical Simulations of Snow Accumulation in the Bogie Region of a Train Considering Snow Particle Rotation

    Hong Lan1,3, Jiye Zhang1,*, Yao Zhang1, Lu Cai2

    FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.10, pp. 2337-2352, 2024, DOI:10.32604/fdmp.2024.052609 - 23 September 2024

    Abstract To investigate the influence of snow particle rotational motion on the accumulation of snow in the bogie region of high-speed trains, an Euler‒Lagrange numerical approach is adopted. The study examines the effects of snow particle diameter and train speed on the ensuing dynamics. It is shown that considering snow particle rotational motion causes significant deviation in the particle trajectories with respect to non-rotating particles. Such a deviation increases with larger snow particle diameters and higher train speeds. The snow accumulation on the overall surface of the bogie increases, and the amount of snow on the More >

  • Open Access

    ARTICLE

    Improving the Effectiveness of Image Classification Structural Methods by Compressing the Description According to the Information Content Criterion

    Yousef Ibrahim Daradkeh1,*, Volodymyr Gorokhovatskyi2, Iryna Tvoroshenko2,*, Medien Zeghid1,3

    CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 3085-3106, 2024, DOI:10.32604/cmc.2024.051709 - 15 August 2024

    Abstract The research aims to improve the performance of image recognition methods based on a description in the form of a set of keypoint descriptors. The main focus is on increasing the speed of establishing the relevance of object and etalon descriptions while maintaining the required level of classification efficiency. The class to be recognized is represented by an infinite set of images obtained from the etalon by applying arbitrary geometric transformations. It is proposed to reduce the descriptions for the etalon database by selecting the most significant descriptor components according to the information content criterion.… More >

  • Open Access

    ARTICLE

    Analysis of Snow Distribution and Displacement in the Bogie Region of a High-Speed Train

    Zhihui Du1, Mengge Yu1,*, Jiali Liu2, Xiulong Yao1

    FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.7, pp. 1687-1701, 2024, DOI:10.32604/fdmp.2024.047315 - 23 July 2024

    Abstract Snow interacting with a high-speed train can cause the formation of ice in the train bogie region and affect its safety. In this study, a wind-snow multiphase numerical approach is introduced for high-speed train bogies on the basis of the Euler-Lagrange discrete phase model. A particle-wall impact criterion is implemented to account for the presence of snow particles on the surface. Subsequently, numerical simulations are conducted, considering various snow particle diameter distributions and densities. The research results indicate that when the particle diameter is relatively small, the distribution of snow particles in the bogie cavity More >

  • Open Access

    ARTICLE

    A New Speed Limit Recognition Methodology Based on Ensemble Learning: Hardware Validation

    Mohamed Karray1,*, Nesrine Triki2,*, Mohamed Ksantini2

    CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 119-138, 2024, DOI:10.32604/cmc.2024.051562 - 18 July 2024

    Abstract Advanced Driver Assistance Systems (ADAS) technologies can assist drivers or be part of automatic driving systems to support the driving process and improve the level of safety and comfort on the road. Traffic Sign Recognition System (TSRS) is one of the most important components of ADAS. Among the challenges with TSRS is being able to recognize road signs with the highest accuracy and the shortest processing time. Accordingly, this paper introduces a new real time methodology recognizing Speed Limit Signs based on a trio of developed modules. Firstly, the Speed Limit Detection (SLD) module uses… More >

  • Open Access

    ARTICLE

    Optimal Design of High-Speed Partial Flow Pumps using Orthogonal Tests and Numerical Simulations

    Jiaqiong Wang1,2, Tao Yang1, Chen Hu1, Yu Zhang3,*, Ling Zhou1,2

    FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.6, pp. 1203-1218, 2024, DOI:10.32604/fdmp.2023.045825 - 27 June 2024

    Abstract To investigate the influence of structural parameters on the performances and internal flow characteristics of partial flow pumps at a low specific speed of 10000 rpm, special attention was paid to the first and second stage impeller guide vanes. Moreover, the impeller blade outlet width, impeller inlet diameter, blade inclination angle, and number of blades were considered for orthogonal tests. Accordingly, nine groups of design solutions were formed, and then used as a basis for the execution of numerical simulations (CFD) aimed at obtaining the efficiency values and heads for each design solution group. The More >

  • Open Access

    ARTICLE

    Aerodynamic Analysis and Optimization of Pantograph Streamline Fairing for High-Speed Trains

    Xiang Kan1, Yan Li2, Tian Li1,*, Jiye Zhang1

    FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.5, pp. 1075-1091, 2024, DOI:10.32604/fdmp.2023.044050 - 07 June 2024

    Abstract A pantograph serves as a vital device for the collection of electricity in trains. However, its aerodynamic resistance can limit the train’s running speed. As installing fairings around the pantograph is known to effectively reduce the resistance, in this study, different fairing lengths are considered and the related aerodynamic performances of pantograph are assessed. In particular, this is accomplished through numerical simulations based on the k-ω Shear Stress Transport (SST) two-equation turbulence model. The results indicate that the fairing diminishes the direct impact of high-speed airflow on the pantograph, thereby reducing its aerodynamic resistance. However, it More >

  • Open Access

    ARTICLE

    Complementary-Label Adversarial Domain Adaptation Fault Diagnosis Network under Time-Varying Rotational Speed and Weakly-Supervised Conditions

    Siyuan Liu1,*, Jinying Huang2, Jiancheng Ma1, Licheng Jing2, Yuxuan Wang2

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 761-777, 2024, DOI:10.32604/cmc.2024.049484 - 25 April 2024

    Abstract Recent research in cross-domain intelligence fault diagnosis of machinery still has some problems, such as relatively ideal speed conditions and sample conditions. In engineering practice, the rotational speed of the machine is often transient and time-varying, which makes the sample annotation increasingly expensive. Meanwhile, the number of samples collected from different health states is often unbalanced. To deal with the above challenges, a complementary-label (CL) adversarial domain adaptation fault diagnosis network (CLADAN) is proposed under time-varying rotational speed and weakly-supervised conditions. In the weakly supervised learning condition, machine prior information is used for sample annotation More >

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