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  • Open Access

    ARTICLE

    Unsteady MHD Casson Nanofluid Flow Past an Exponentially Accelerated Vertical Plate: An Analytical Strategy

    T. Aghalya, R. Tamizharasi*

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 431-460, 2024, DOI:10.32604/cmes.2024.046635

    Abstract In this study, the characteristics of heat transfer on an unsteady magnetohydrodynamic (MHD) Casson nanofluid over an exponentially accelerated vertical porous plate with rotating effects were investigated. The flow was driven by the combined effects of the magnetic field, heat radiation, heat source/sink and chemical reaction. Copper oxide () and titanium oxide () are acknowledged as nanoparticle materials. The nondimensional governing equations were subjected to the Laplace transformation technique to derive closed-form solutions. Graphical representations are provided to analyze how changes in physical parameters, such as the magnetic field, heat radiation, heat source/sink and chemical reaction, affect the velocity, temperature… More >

  • Open Access

    ARTICLE

    The Lambert-G Family: Properties, Inference, and Applications

    Jamal N. Al Abbasi1, Ahmed Z. Afify2,*, Badr Alnssyan3,*, Mustafa S. Shama4,5

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 513-536, 2024, DOI:10.32604/cmes.2024.046533

    Abstract This study proposes a new flexible family of distributions called the Lambert-G family. The Lambert family is very flexible and exhibits desirable properties. Its three-parameter special sub-models provide all significant monotonic and non-monotonic failure rates. A special sub-model of the Lambert family called the Lambert-Lomax (LL) distribution is investigated. General expressions for the LL statistical properties are established. Characterizations of the LL distribution are addressed mathematically based on its hazard function. The estimation of the LL parameters is discussed using six estimation methods. The performance of this estimation method is explored through simulation experiments. The usefulness and flexibility of the… More >

  • Open Access

    ARTICLE

    MPI/OpenMP-Based Parallel Solver for Imprint Forming Simulation

    Yang Li1, Jiangping Xu1,*, Yun Liu1, Wen Zhong2,*, Fei Wang3

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 461-483, 2024, DOI:10.32604/cmes.2024.046467

    Abstract In this research, we present the pure open multi-processing (OpenMP), pure message passing interface (MPI), and hybrid MPI/OpenMP parallel solvers within the dynamic explicit central difference algorithm for the coining process to address the challenge of capturing fine relief features of approximately 50 microns. Achieving such precision demands the utilization of at least 7 million tetrahedron elements, surpassing the capabilities of traditional serial programs previously developed. To mitigate data races when calculating internal forces, intermediate arrays are introduced within the OpenMP directive. This helps ensure proper synchronization and avoid conflicts during parallel execution. Additionally, in the MPI implementation, the coins… More > Graphic Abstract

    MPI/OpenMP-Based Parallel Solver for Imprint Forming Simulation

  • Open Access

    ARTICLE

    Modularized and Parametric Modeling Technology for Finite Element Simulations of Underground Engineering under Complicated Geological Conditions

    Jiaqi Wu1, Li Zhuo1,*, Jianliang Pei1, Yao Li2, Hongqiang Xie1, Jiaming Wu1, Huaizhong Liu1

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 621-645, 2024, DOI:10.32604/cmes.2024.046398

    Abstract The surrounding geological conditions and supporting structures of underground engineering are often updated during construction, and these updates require repeated numerical modeling. To improve the numerical modeling efficiency of underground engineering, a modularized and parametric modeling cloud server is developed by using Python codes. The basic framework of the cloud server is as follows: input the modeling parameters into the web platform, implement Rhino software and FLAC3D software to model and run simulations in the cloud server, and return the simulation results to the web platform. The modeling program can automatically generate instructions that can run the modeling process in… More >

  • Open Access

    ARTICLE

    Contact Stress Reliability Analysis Model for Cylindrical Gear with Circular Arc Tooth Trace Based on an Improved Metamodel

    Qi Zhang1,2,4,5, Zhixin Chen3, Yang Wu4,*, Guoqi Xiang2, Guang Wen1, Xuegang Zhang2, Yongchun Xie2, Guangchun Yang2

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 593-619, 2024, DOI:10.32604/cmes.2023.046319

    Abstract Although there is currently no unified standard theoretical formula for calculating the contact stress of cylindrical gears with a circular arc tooth trace (referred to as CATT gear), a mathematical model for determining the contact stress of CATT gear is essential for studying how parameters affect its contact stress and building the contact stress limit state equation for contact stress reliability analysis. In this study, a mathematical relationship between design parameters and contact stress is formulated using the Kriging Metamodel. To enhance the model’s accuracy, we propose a new hybrid algorithm that merges the genetic algorithm with the Quantum Particle… More >

  • Open Access

    ARTICLE

    A Web Application Fingerprint Recognition Method Based on Machine Learning

    Yanmei Shi1, Wei Yu2,*, Yanxia Zhao3,*, Yungang Jia4

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 887-906, 2024, DOI:10.32604/cmes.2024.046140

    Abstract Web application fingerprint recognition is an effective security technology designed to identify and classify web applications, thereby enhancing the detection of potential threats and attacks. Traditional fingerprint recognition methods, which rely on preannotated feature matching, face inherent limitations due to the ever-evolving nature and diverse landscape of web applications. In response to these challenges, this work proposes an innovative web application fingerprint recognition method founded on clustering techniques. The method involves extensive data collection from the Tranco List, employing adjusted feature selection built upon Wappalyzer and noise reduction through truncated SVD dimensionality reduction. The core of the methodology lies in… More >

  • Open Access

    ARTICLE

    Fatigue Crack Propagation Law of Corroded Steel Box Girders in Long Span Bridges

    Ying Wang1,*, Longxiao Chao1, Jun Chen2, Songbai Jiang1

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 201-227, 2024, DOI:10.32604/cmes.2024.046129

    Abstract In order to investigate the fatigue performance of orthotropic anisotropic steel bridge decks, this study realizes the simulation of the welding process through elastic-plastic finite element theory, thermal-structural sequential coupling, and the birth-death element method. The simulated welding residual stresses are introduced into the multiscale finite element model of the bridge as the initial stress. Furthermore, the study explores the impact of residual stress on crack propagation in the fatigue-vulnerable components of the corroded steel box girder. The results indicate that fatigue cracks at the weld toe of the top deck, the weld root of the top deck, and the… More > Graphic Abstract

    Fatigue Crack Propagation Law of Corroded Steel Box Girders in Long Span Bridges

  • Open Access

    ARTICLE

    Buckling Optimization of Curved Grid Stiffeners through the Level Set Based Density Method

    Zhuo Huang, Ye Tian, Yifan Zhang, Tielin Shi, Qi Xia*

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 711-733, 2024, DOI:10.32604/cmes.2024.045411

    Abstract Stiffened structures have great potential for improving mechanical performance, and the study of their stability is of great interest. In this paper, the optimization of the critical buckling load factor for curved grid stiffeners is solved by using the level set based density method, where the shape and cross section (including thickness and width) of the stiffeners can be optimized simultaneously. The grid stiffeners are a combination of many single stiffeners which are projected by the corresponding level set functions. The thickness and width of each stiffener are designed to be independent variables in the projection applied to each level… More >

  • Open Access

    ARTICLE

    An Image Fingerprint and Attention Mechanism Based Load Estimation Algorithm for Electric Power System

    Qing Zhu1,*, Linlin Gu1,2, Huijie Lin1,2

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 577-591, 2024, DOI:10.32604/cmes.2023.043307

    Abstract With the rapid development of electric power systems, load estimation plays an important role in system operation and planning. Usually, load estimation techniques contain traditional, time series, regression analysis-based, and machine learning-based estimation. Since the machine learning-based method can lead to better performance, in this paper, a deep learning-based load estimation algorithm using image fingerprint and attention mechanism is proposed. First, an image fingerprint construction is proposed for training data. After the data preprocessing, the training data matrix is constructed by the cyclic shift and cubic spline interpolation. Then, the linear mapping and the gray-color transformation method are proposed to… More >

  • Open Access

    ARTICLE

    Scheme Based on Multi-Level Patch Attention and Lesion Localization for Diabetic Retinopathy Grading

    Zhuoqun Xia1, Hangyu Hu1, Wenjing Li2,3, Qisheng Jiang1, Lan Pu1, Yicong Shu1, Arun Kumar Sangaiah4,5,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 409-430, 2024, DOI:10.32604/cmes.2024.030052

    Abstract Early screening of diabetes retinopathy (DR) plays an important role in preventing irreversible blindness. Existing research has failed to fully explore effective DR lesion information in fundus maps. Besides, traditional attention schemes have not considered the impact of lesion type differences on grading, resulting in unreasonable extraction of important lesion features. Therefore, this paper proposes a DR diagnosis scheme that integrates a multi-level patch attention generator (MPAG) and a lesion localization module (LLM). Firstly, MPAG is used to predict patches of different sizes and generate a weighted attention map based on the prediction score and the types of lesions contained… More >

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