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  • Open AccessOpen Access

    EDITORIAL

    Introduction to the Special Issue on Mechanics of Composite Materials and Structures

    Jian Xiong1,*, Jinshui Yang2, Hui Li3, Wu Xu4
    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.2, pp. 357-359, 2022, DOI:10.32604/cmes.2022.023418 - 15 June 2022
    （This article belongs to the Special Issue: Mechanics of Composite Materials and Structures)
    Abstract This article has no abstract. More >

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    886

  • Open AccessOpen Access

    REVIEW

    Review of Numerical Simulation of TGO Growth in Thermal Barrier Coatings

    Quan Wen1, Fulei Jing1,*, Changxian Zhang1, Shibai Tang1, Junjie Yang2,*
    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.2, pp. 361-391, 2022, DOI:10.32604/cmes.2022.019528 - 15 June 2022
    （This article belongs to the Special Issue: Recent Trends in Thermal Barrier Coatings for Turbine Blades: Theory, Simulation, and Experiment)
    Abstract Thermally grown oxide (TGO) is a critical factor for the service life of thermal barrier coatings (TBC). Numerical simulations of the growth process of TGO have become an effective means of comprehensively understanding the progressive damage of the TBC system. At present, technologies of numerical simulation to TGO growth include two categories: coupled chemical-mechanical methods and mechanical equivalent methods. The former is based on the diffusion analysis of oxidizing elements, which can describe the influence of bond coat (BC) consumption and phase transformation in the growth process of TGO on the mechanical behavior of each More >

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    3270

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    1401

  • Open AccessOpen Access

    ARTICLE

    Dynamical Model to Optimize Student’s Academic Performance

    Evren Hincal, Amna Hashim Alzadjali
    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.2, pp. 393-411, 2022, DOI:10.32604/cmes.2022.019781 - 15 June 2022
    Abstract Excellent student’s academic performance is the uppermost priority and goal of educators and facilitators. The dubious marginal rate between admission and graduation rates unveils the rates of dropout and withdrawal from school. To improve the academic performance of students, we optimize the performance indices to the dynamics describing the academic performance in the form of nonlinear system ODE. We established the uniform boundedness of the model and the existence and uniqueness result. The independence and interdependence equilibria were found to be locally and globally asymptotically stable. The optimal control analysis was carried out, and lastly, More >

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    1108

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    843

  • Open AccessOpen Access

    ARTICLE

    A New Criterion for Defining Inhomogeneous Slope Failure Using the Strength Reduction Method

    Chengya Hua1, Leihua Yao1,*, Chenguang Song1, Qihang Ni1, Dongfang Chen2
    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.2, pp. 413-434, 2022, DOI:10.32604/cmes.2022.020260 - 15 June 2022
    Abstract A new variational method treating the system as a whole with rigorous mathematical and physical derivation was presented in this paper. Combined with classical and engineering examples, variational energy expressions of slopes were derived. In addition, the calculation programs were written in the FISH language set in FLAC3D (fast Lagrangian analysis of continua in three dimensions) software. Factors of safety (FOSs) of the models were determined by the variational method based on the strength reduction method (SRM) and then compared with other criteria or methods. The result showed that the variational method reflected the process… More >

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    2024

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    804

  • Open AccessOpen Access

    ARTICLE

    Email Filtering Using Hybrid Feature Selection Model

    Adel Hamdan Mohammad1,* , Sami Smadi2, Tariq Alwada’n3
    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.2, pp. 435-450, 2022, DOI:10.32604/cmes.2022.020088 - 15 June 2022
    Abstract Undoubtedly, spam is a serious problem, and the number of spam emails is increased rapidly. Besides, the massive number of spam emails prompts the need for spam detection techniques. Several methods and algorithms are used for spam filtering. Also, some emergent spam detection techniques use machine learning methods and feature extraction. Some methods and algorithms have been introduced for spam detecting and filtering. This research proposes two models for spam detection and feature selection. The first model is evaluated with the email spam classification dataset, which is based on reducing the number of keywords to… More >

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    2159

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    982

  • Open AccessOpen Access

    ARTICLE

    Topology Optimization of Self-Supporting Structures for Additive Manufacturing with Adaptive Explicit Continuous Constraint

    Jun Zou*, Haolei Mou
    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.2, pp. 451-469, 2022, DOI:10.32604/cmes.2022.020111 - 15 June 2022
    （This article belongs to the Special Issue: New Trends in Structural Optimization)
    Abstract The integration of topology optimization (TO) and additive manufacturing (AM) technologies can create significant synergy benefits, while the lack of AM-friendly TO algorithms is a serious bottleneck for the application of TO in AM. In this paper, a TO method is proposed to design self-supporting structures with an explicit continuous self-supporting constraint, which can be adaptively activated and tightened during the optimization procedure. The TO procedure is suitable for various critical overhang angles (COA), which is integrated with build direction assignment to reduce performance loss. Besides, a triangular directional self-supporting constraint sensitivity filter is devised More >

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    2556

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    1116

  • Open AccessOpen Access

    ARTICLE

    Isogeometric Boundary Element Method for Two-Dimensional Steady-State Non-Homogeneous Heat Conduction Problem

    Yongsong Li1, Xiaomeng Yin2, Yanming Xu1,*
    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.2, pp. 471-488, 2022, DOI:10.32604/cmes.2022.020201 - 15 June 2022
    （This article belongs to the Special Issue: Recent Advance of the Isogeometric Boundary Element Method and its Applications)
    Abstract The isogeometric boundary element technique (IGABEM) is presented in this study for steady-state inhomogeneous heat conduction analysis. The physical unknowns in the boundary integral formulations of the governing equations are discretized using non-uniform rational B-spline (NURBS) basis functions, which are utilized to build the geometry of the structures. To speed up the assessment of NURBS basis functions, the B´ezier extraction approach is used. To solve the extra domain integrals, we use a radial integration approach. The numerical examples show the potential of IGABEM for dimension reduction and smooth integration of CAD and numerical analysis. More >

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    1997

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    945

  • Open AccessOpen Access

    ARTICLE

    Stability Analysis of Predator-Prey System with Consuming Resource and Disease in Predator Species

    Asad Ejaz1, Yasir Nawaz1, Muhammad Shoaib Arif1,3,*, Daoud S. Mashat2, Kamaleldin Abodayeh3
    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.2, pp. 489-506, 2022, DOI:10.32604/cmes.2022.019440 - 15 June 2022
    （This article belongs to the Special Issue: Mathematical Aspects of Computational Biology and Bioinformatics)
    Abstract The present study is concerned with formulating a predator-prey eco-epidemiological mathematical model assuming that an infection exists in the predator species. The two classes of predator species (susceptible and infected) compete for the same sources available in the environment with the predation option. It is assumed that the disease does not spread vertically. The proposed model is analyzed for the stability of the coexistence of the predators and prey. The fixed points are carried out, and the coexisting fixed point is studied in detail by constructing the Lyapunov function. The movement of species in search… More >

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    2528

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    1157

  • Open AccessOpen Access

    ARTICLE

    COVID-19 Imaging Detection in the Context of Artificial Intelligence and the Internet of Things

    Xiaowei Gu1,#, Shuwen Chen1,2,#,*, Huisheng Zhu1, Mackenzie Brown3,*
    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.2, pp. 507-530, 2022, DOI:10.32604/cmes.2022.018948 - 15 June 2022
    （This article belongs to the Special Issue: Computer-Assisted Imaging Processing and Machine Learning Applications on Diagnosis of Chest Radiograph)
    Abstract Coronavirus disease 2019 brings a huge burden on the medical industry all over the world. In the background of artificial intelligence (AI) and Internet of Things (IoT) technologies, chest computed tomography (CT) and chest X-ray (CXR) scans are becoming more intelligent, and playing an increasingly vital role in the diagnosis and treatment of diseases. This paper will introduce the segmentation of methods and applications. CXR and CT diagnosis of COVID-19 based on deep learning, which can be widely used to fight against COVID-19. More >

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    2579

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    1232

  • Open AccessOpen Access

    ARTICLE

    Enhancing the Effectiveness of Trimethylchlorosilane Purification Process Monitoring with Variational Autoencoder

    Jinfu Wang1, Shunyi Zhao1,*, Fei Liu1, Zhenyi Ma2
    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.2, pp. 531-552, 2022, DOI:10.32604/cmes.2022.019521 - 15 June 2022
    （This article belongs to the Special Issue: Advances on Modeling and State Estimation for Industrial Processes)
    Abstract In modern industry, process monitoring plays a significant role in improving the quality of process conduct. With the higher dimensional of the industrial data, the monitoring methods based on the latent variables have been widely applied in order to decrease the wasting of the industrial database. Nevertheless, these latent variables do not usually follow the Gaussian distribution and thus perform unsuitable when applying some statistics indices, especially the T2 on them. Variational AutoEncoders (VAE), an unsupervised deep learning algorithm using the hierarchy study method, has the ability to make the latent variables follow the Gaussian More >

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    1751

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    919

  • Open AccessOpen Access

    ARTICLE

    RBMDO Using Gaussian Mixture Model-Based Second-Order Mean-Value Saddlepoint Approximation

    Debiao Meng1,2,3, Shiyuan Yang1, Tao Lin4,5,*, Jiapeng Wang1, Hengfei Yang1, Zhiyuan Lv1
    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.2, pp. 553-568, 2022, DOI:10.32604/cmes.2022.020756 - 15 June 2022
    （This article belongs to the Special Issue: Computer-Aided Structural Integrity and Safety Assessment)
    Abstract Actual engineering systems will be inevitably affected by uncertain factors. Thus, the Reliability-Based Multidisciplinary Design Optimization (RBMDO) has become a hotspot for recent research and application in complex engineering system design. The Second-Order/First-Order Mean-Value Saddlepoint Approximate (SOMVSA/FOMVSA) are two popular reliability analysis strategies that are widely used in RBMDO. However, the SOMVSA method can only be used efficiently when the distribution of input variables is Gaussian distribution, which significantly limits its application. In this study, the Gaussian Mixture Model-based Second-Order Mean-Value Saddlepoint Approximation (GMM-SOMVSA) is introduced to tackle above problem. It is integrated with the More >

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    954

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    35

  • Open AccessOpen Access

    ARTICLE

    Aczel-Alsina Weighted Aggregation Operators of Simplified Neutrosophic Numbers and Its Application in Multiple Attribute Decision Making

    Rui Yong1,2,*, Jun Ye1,2, Shigui Du1,2, Aqin Zhu1, Yingying Zhang1
    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.2, pp. 569-584, 2022, DOI:10.32604/cmes.2022.019509 - 15 June 2022
    （This article belongs to the Special Issue: Extension, Modeling and Applications of Fuzzy Set Theory in Engineering and Science)
    Abstract The simplified neutrosophic number (SNN) can represent uncertain, imprecise, incomplete, and inconsistent information that exists in scientific, technological, and engineering fields. Hence, it is a useful tool for describing truth, falsity, and indeterminacy information in multiple attribute decision-making (MADM) problems. To suit decision makers’ preference selection, the operational flexibility of aggregation operators shows its importance in dealing with the flexible decision-making problems in the SNN environment. To solve this problem, this paper develops the Aczel-Alsina aggregation operators of SNNs for MADM problems in view of the Aczel-Alsina operational flexibility. First, we define the Aczel-Alsina operations More >

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    1908

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    873

  • Open AccessOpen Access

    ARTICLE

    Research on Distributed Cooperative Control Strategy of Microgrid Hybrid Energy Storage Based on Adaptive Event Triggering

    Wenqian Zhang1, Jingwen Chen1,*, Saleem Riaz3, Naiwen Zheng1, Li Li2
    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.2, pp. 585-604, 2022, DOI:10.32604/cmes.2022.020523 - 15 June 2022
    （This article belongs to the Special Issue: Artificial Intelligence in Renewable Energy and Storage Systems)
    Abstract Distributed collaborative control strategies for microgrids often use periodic time to trigger communication, which is likely to enhance the burden of communication and increase the frequency of controller updates, leading to greater waste of communication resources. In response to this problem, a distributed cooperative control strategy triggered by an adaptive event is proposed. By introducing an adaptive event triggering mechanism in the distributed controller, the triggering parameters are dynamically adjusted so that the distributed controller can communicate only at a certain time, the communication pressure is reduced, and the DC bus voltage deviation is effectively More >

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    2753

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    1095

  • Open AccessOpen Access

    ARTICLE

    Accelerated Iterative Learning Control for Linear Discrete Systems with Parametric Perturbation and Measurement Noise

    Xiaoxin Yang1, Saleem Riaz2,*
    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.2, pp. 605-626, 2022, DOI:10.32604/cmes.2022.020412 - 15 June 2022
    （This article belongs to the Special Issue: Artificial Intelligence in Renewable Energy and Storage Systems)
    Abstract An iterative learning control algorithm based on error backward association and control parameter correction has been proposed for a class of linear discrete time-invariant systems with repeated operation characteristics, parameter disturbance, and measurement noise taking PD type example. Firstly, the concrete form of the accelerated learning law is presented, based on the detailed description of how the control factor is obtained in the algorithm. Secondly, with the help of the vector method, the convergence of the algorithm for the strict mathematical proof, combined with the theory of spectral radius, sucient conditions for the convergence of More >

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    2446

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    1077

  • Open AccessOpen Access

    ARTICLE

    Numerical Study on the Suitability of Passive Solar Heating Technology Based on Differentiated Thermal Comfort Demand

    Xiaona Fan, Qin Zhao, Guochen Sang, Yiyun Zhu*
    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.2, pp. 627-660, 2022, DOI:10.32604/cmes.2022.020507 - 15 June 2022
    （This article belongs to the Special Issue: Numerical Methods in Engineering Analysis, Data Analysis and Artificial Intelligence)
    Abstract Indoor thermal comfort and passive solar heating technologies have been extensively studied. However, few studies have explored the suitability of passive solar heating technologies based on differentiated thermal comfort demands. This work took the rural dwellings in Northwest China as the research object. First, the current indoor and outdoor thermal environment in winter and the mechanism of residents’ differentiated demand for indoor thermal comfort were obtained through tests, questionnaires, and statistical analysis. Second, a comprehensive passive optimized design of existing buildings was conducted, and the validity of the optimized combination scheme was explored using DesignBuilder… More >

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    2754

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    1212

  • Open AccessOpen Access

    ARTICLE

    Pollution Dispersion in Urban Street Canyons with Green Belts

    Xiaoxuan Zhu1, Xueyan Wang2, Li Lei1,*, Yuting Zhao1
    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.2, pp. 661-679, 2022, DOI:10.32604/cmes.2022.020427 - 15 June 2022
    （This article belongs to the Special Issue: Numerical Methods in Engineering Analysis, Data Analysis and Artificial Intelligence)
    Abstract In this study, numerical simulations were used to explore the effects of roadside green belt, urban street spatial layout, and wind speed on vehicle exhaust emission diffusion in street canyon. The diffusion of different sized particles in the street canyon and the influence of wind speed were investigated. The individual daily average pollutant intake was used to evaluate the exposure level in a street canyon microenvironment. The central and leeward green belts of the road were the most conducive to the diffusion of pollutants, while the positioning of the green belts both sides of a More >

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    1931

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    950

  • Open AccessOpen Access

    ARTICLE

    Mechanical Properties of Soil-Rock Mixture Filling in Fault Zone Based on Mesostructure

    Mei Tao1, Qingwen Ren1,*, Hanbing Bian2, Maosen Cao1, Yun Jia3
    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.2, pp. 681-705, 2022, DOI:10.32604/cmes.2022.019522 - 15 June 2022
    （This article belongs to the Special Issue: Numerical Methods in Engineering Analysis, Data Analysis and Artificial Intelligence)
    Abstract Soil-rock mixture (SRM) filling in fault zone is an inhomogeneous geomaterial, which is composed of soil and rock block. It controls the deformation and stability of the abutment and dam foundation, and threatens the long-term safety of high arch dams. To study the macroscopic and mesoscopic mechanical properties of SRM, the development of a viable mesoscopic numerical simulation method with a mesoscopic model generation technology, and a reasonable parametric model is crucially desired to overcome the limitations of experimental conditions, specimen dimensions, and experiment fund. To this end, this study presents a mesoscopic numerical method… More >

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