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  • Open Access

    REVIEW

    Review of Collocation Methods and Applications in Solving Science and Engineering Problems

    Weiwu Jiang1, Xiaowei Gao1,2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 41-76, 2024, DOI:10.32604/cmes.2024.048313

    Abstract The collocation method is a widely used numerical method for science and engineering problems governed by partial differential equations. This paper provides a comprehensive review of collocation methods and their applications, focused on elasticity, heat conduction, electromagnetic field analysis, and fluid dynamics. The merits of the collocation method can be attributed to the need for element mesh, simple implementation, high computational efficiency, and ease in handling irregular domain problems since the collocation method is a type of node-based numerical method. Beginning with the fundamental principles of the collocation method, the discretization process in the continuous domain is elucidated, and how… More >

  • Open Access

    ARTICLE

    Aggravation of Cancer, Heart Diseases and Diabetes Subsequent to COVID-19 Lockdown via Mathematical Modeling

    Fatma Nese Efil1, Sania Qureshi1,2,3, Nezihal Gokbulut1,4, Kamyar Hosseini1,3, Evren Hincal1,4,*, Amanullah Soomro2

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 485-512, 2024, DOI:10.32604/cmes.2024.047907

    Abstract The global population has been and will continue to be severely impacted by the COVID-19 epidemic. The primary objective of this research is to demonstrate the future impact of COVID-19 on those who suffer from other fatal conditions such as cancer, heart disease, and diabetes. Here, using ordinary differential equations (ODEs), two mathematical models are developed to explain the association between COVID-19 and cancer and between COVID-19 and diabetes and heart disease. After that, we highlight the stability assessments that can be applied to these models. Sensitivity analysis is used to examine how changes in certain factors impact different aspects… More >

  • Open Access

    ARTICLE

    Reliable Data Collection Model and Transmission Framework in Large-Scale Wireless Medical Sensor Networks

    Haosong Gou1, Gaoyi Zhang1, Renê Ripardo Calixto2, Senthil Kumar Jagatheesaperumal3, Victor Hugo C. de Albuquerque2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 1077-1102, 2024, DOI:10.32604/cmes.2024.047806

    Abstract Large-scale wireless sensor networks (WSNs) play a critical role in monitoring dangerous scenarios and responding to medical emergencies. However, the inherent instability and error-prone nature of wireless links present significant challenges, necessitating efficient data collection and reliable transmission services. This paper addresses the limitations of existing data transmission and recovery protocols by proposing a systematic end-to-end design tailored for medical event-driven cluster-based large-scale WSNs. The primary goal is to enhance the reliability of data collection and transmission services, ensuring a comprehensive and practical approach. Our approach focuses on refining the hop-count-based routing scheme to achieve fairness in forwarding reliability. Additionally,… More >

  • Open Access

    ARTICLE

    Enhancing Ulcerative Colitis Diagnosis: A Multi-Level Classification Approach with Deep Learning

    Hasan J. Alyamani*

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 1129-1142, 2024, DOI:10.32604/cmes.2024.047756

    Abstract The evaluation of disease severity through endoscopy is pivotal in managing patients with ulcerative colitis, a condition with significant clinical implications. However, endoscopic assessment is susceptible to inherent variations, both within and between observers, compromising the reliability of individual evaluations. This study addresses this challenge by harnessing deep learning to develop a robust model capable of discerning discrete levels of endoscopic disease severity. To initiate this endeavor, a multi-faceted approach is embarked upon. The dataset is meticulously preprocessed, enhancing the quality and discriminative features of the images through contrast limited adaptive histogram equalization (CLAHE). A diverse array of data augmentation… More > Graphic Abstract

    Enhancing Ulcerative Colitis Diagnosis: A Multi-Level Classification Approach with Deep Learning

  • Open Access

    ARTICLE

    Predicting Rock Burst in Underground Engineering Leveraging a Novel Metaheuristic-Based LightGBM Model

    Kai Wang1, Biao He2,*, Pijush Samui3, Jian Zhou4

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 229-253, 2024, DOI:10.32604/cmes.2024.047569

    Abstract Rock bursts represent a formidable challenge in underground engineering, posing substantial risks to both infrastructure and human safety. These sudden and violent failures of rock masses are characterized by the rapid release of accumulated stress within the rock, leading to severe seismic events and structural damage. Therefore, the development of reliable prediction models for rock bursts is paramount to mitigating these hazards. This study aims to propose a tree-based model—a Light Gradient Boosting Machine (LightGBM)—to predict the intensity of rock bursts in underground engineering. 322 actual rock burst cases are collected to constitute an exhaustive rock burst dataset, which serves… More >

  • Open Access

    ARTICLE

    A Coupled Thermomechanical Crack Propagation Behavior of Brittle Materials by Peridynamic Differential Operator

    Tianyi Li1,2, Xin Gu2, Qing Zhang2,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 339-361, 2024, DOI:10.32604/cmes.2024.047566

    Abstract This study proposes a comprehensive, coupled thermomechanical model that replaces local spatial derivatives in classical differential thermomechanical equations with nonlocal integral forms derived from the peridynamic differential operator (PDDO), eliminating the need for calibration procedures. The model employs a multi-rate explicit time integration scheme to handle varying time scales in multi-physics systems. Through simulations conducted on granite and ceramic materials, this model demonstrates its effectiveness. It successfully simulates thermal damage behavior in granite arising from incompatible mineral expansion and accurately calculates thermal crack propagation in ceramic slabs during quenching. To account for material heterogeneity, the model utilizes the Shuffle algorithm… More >

  • Open Access

    ARTICLE

    Study of the Ballistic Impact Behavior of Protective Multi-Layer Composite Armor

    Dongsheng Jia, Yingjie Xu*, Liangdi Wang, Jihong Zhu, Weihong Zhang

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 171-199, 2024, DOI:10.32604/cmes.2024.046703

    Abstract The abalone shell, a composite material whose cross-section is composed of inorganic and organic layers, has high strength and toughness. Inspired by the abalone shell, several multi-layer composite plates with different layer sequences and thicknesses are studied as bullet-proof material in this paper. To investigate the ballistic performance of this multi-layer structure, the complete characterization model and related material parameters of large deformation, failure and fracture of Al2O3 ceramics and Carbon Fiber Reinforced Polymer (CFRP) are studied. Then, 3D finite element models of the proposed composite plates with different layer sequences and thicknesses impacted by a 12.7 mm armor-piercing incendiary… More >

  • 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

    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 >

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