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  • 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., , 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

    Computing Resource Allocation for Blockchain-Based Mobile Edge Computing

    Wanbo Zhang1, Yuqi Fan1, Jun Zhang1, Xu Ding2,*, Jung Yoon Kim3,*

    CMES-Computer Modeling in Engineering & Sciences, Vol., , DOI:10.32604/cmes.2024.047295

    Abstract Users and edge servers are not fully mutually trusted in mobile edge computing (MEC), and hence blockchain can be introduced to provide trustable MEC. In blockchain-based MEC, each edge server functions as a node in both MEC and blockchain, processing users’ tasks and then uploading the task related information to the blockchain. That is, each edge server runs both users’ offloaded tasks and blockchain tasks simultaneously. Note that there is a trade-off between the resource allocation for MEC and blockchain tasks. Therefore, the allocation of the resources of edge servers to the blockchain and the MEC is crucial for the… More >

  • Open Access

    ARTICLE

    Blade Wrap Angle Impact on Centrifugal Pump Performance: Entropy Generation and Fluid-Structure Interaction Analysis

    Hayder Kareem Sakran1,2, Mohd Sharizal Abdul Aziz1,*, Chu Yee Khor3

    CMES-Computer Modeling in Engineering & Sciences, Vol., , DOI:10.32604/cmes.2024.047245

    Abstract The centrifugal pump is a prevalent power equipment widely used in different engineering patterns, and the impeller blade wrap angle significantly impacts its performance. A numerical investigation was conducted to analyze the influence of the blade wrap angle on flow characteristics and energy distribution of a centrifugal pump evaluated as a low specific speed with a value of 69. This study investigates six impeller models that possess varying blade wrap angles (95°, 105°, 115°, 125°, 135°, and 145°) that were created while maintaining the same volute and other geometrical characteristics. The investigation of energy loss was conducted to evaluate the… More > Graphic Abstract

    Blade Wrap Angle Impact on Centrifugal Pump Performance: Entropy Generation and Fluid-Structure Interaction Analysis

  • 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., , 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

    Novelty of Different Distance Approach for Multi-Criteria Decision-Making Challenges Using q-Rung Vague Sets

    Murugan Palanikumar1, Nasreen Kausar2,*, Dragan Pamucar3,4, Seifedine Kadry5,6,7,*, Chomyong Kim8, Yunyoung Nam9

    CMES-Computer Modeling in Engineering & Sciences, Vol., , DOI:10.32604/cmes.2024.031439

    Abstract In this article, multiple attribute decision-making problems are solved using the vague normal set (VNS). It is possible to generalize the vague set (VS) and q-rung fuzzy set (FS) into the q-rung vague set (VS). A log q-rung normal vague weighted averaging (log q-rung NVWA), a log q-rung normal vague weighted geometric (log q-rung NVWG), a log generalized q-rung normal vague weighted averaging (log Gq-rung NVWA), and a log generalized q-rung normal vague weighted geometric (log Gq-rung NVWG) operator are discussed in this article. A description is provided of the scoring function, accuracy function and operational laws of the log… 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., , 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

    Conditional Generative Adversarial Network Enabled Localized Stress Recovery of Periodic Composites

    Chengkan Xu1,2,4, Xiaofei Wang3, Yixuan Li2, Guannan Wang2,*, He Zhang2,4,*

    CMES-Computer Modeling in Engineering & Sciences, Vol., , DOI:10.32604/cmes.2024.047327

    Abstract Structural damage in heterogeneous materials typically originates from microstructures where stress concentration occurs. Therefore, evaluating the magnitude and location of localized stress distributions within microstructures under external loading is crucial. Repeating unit cells (RUCs) are commonly used to represent microstructural details and homogenize the effective response of composites. This work develops a machine learning-based micromechanics tool to accurately predict the stress distributions of extracted RUCs. The locally exact homogenization theory efficiently generates the microstructural stresses of RUCs with a wide range of parameters, including volume fraction, fiber/matrix property ratio, fiber shapes, and loading direction. Subsequently, the conditional generative adversarial network… More > Graphic Abstract

    Conditional Generative Adversarial Network Enabled Localized Stress Recovery of Periodic Composites

  • Open Access

    ARTICLE

    A Hybrid SIR-Fuzzy Model for Epidemic Dynamics: A Numerical Study

    Muhammad Shoaib Arif1,2,*, Kamaleldin Abodayeh1, Yasir Nawaz2

    CMES-Computer Modeling in Engineering & Sciences, Vol., , DOI:10.32604/cmes.2024.046944

    Abstract This study focuses on the urgent requirement for improved accuracy in disease modeling by introducing a new computational framework called the Hybrid SIR-Fuzzy Model. By integrating the traditional Susceptible-Infectious-Recovered (SIR) model with fuzzy logic, our method effectively addresses the complex nature of epidemic dynamics by accurately accounting for uncertainties and imprecisions in both data and model parameters. The main aim of this research is to provide a model for disease transmission using fuzzy theory, which can successfully address uncertainty in mathematical modeling. Our main emphasis is on the imprecise transmission rate parameter, utilizing a three-part description of its membership level.… 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., , 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

    A Study on the Transmission Dynamics of the Omicron Variant of COVID-19 Using Nonlinear Mathematical Models

    S. Dickson1, S. Padmasekaran1, Pushpendra Kumar2,*, Kottakkaran Sooppy Nisar3, Hamidreza Marasi4

    CMES-Computer Modeling in Engineering & Sciences, Vol., , DOI:10.32604/cmes.2023.030286

    Abstract This research examines the transmission dynamics of the Omicron variant of COVID-19 using SEIQIcRVW and SQIRV models, considering the delay in converting susceptible individuals into infected ones. The significant delays eventually resulted in the pandemic’s containment. To ensure the safety of the host population, this concept integrates quarantine and the COVID-19 vaccine. We investigate the stability of the proposed models. The fundamental reproduction number influences stability conditions. According to our findings, asymptomatic cases considerably impact the prevalence of Omicron infection in the community. The real data of the Omicron variant from Chennai, Tamil Nadu, India, is used to validate the… More >

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