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  • Open Access


    Numerical Investigation of an Idealized Total Cavopulmonary Connection Physiology Assisted by the Axial Blood Pump With and Without Diffuser

    Zhenxin Zhao1,#, Tong Chen2,#, Xudong Liu3, Shengzhang Wang2,4,*, Haiyan Lu5,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.3, pp. 1173-1184, 2020, DOI:10.32604/cmes.2020.013702

    Abstract In order to improve the surgical treatment of the congenital heart disease patient with single ventricle defect, two axial flow blood pumps, one with diffuser and the other without diffuser, were designed and virtually implanted into an idealized total cavopulmonary connection (TCPC) model to form two types of Pump-TCPC physiological structure. Computational fluid dynamics (CFD) simulations were performed to analyze the variations of the hemodynamic characteristics, such as flow field, wall shear stress (WSS), oscillatory shear index (OSI), relative residence time (RRT), between the two Pump-TCPC models. Numerical results indicate that the Pump-TCPC with diffuser More >

  • Open Access


    Prediction of Permeability Using Random Forest and Genetic Algorithm Model

    Junhui Wang1, Wanzi Yan1, Zhijun Wan1,*, Yi Wang2,*, Jiakun Lv1, Aiping Zhou3

    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.3, pp. 1135-1157, 2020, DOI:10.32604/cmes.2020.014313

    Abstract Precise recovery of Coalbed Methane (CBM) based on transparent reconstruction of geological conditions is a branch of intelligent mining. The process of permeability reconstruction, ranging from data perception to real-time data visualization, is applicable to disaster risk warning and intelligent decision-making on gas drainage. In this study, a machine learning method integrating the Random Forest (RF) and the Genetic Algorithm (GA) was established for permeability prediction in the Xishan Coalfield based on Uniaxial Compressive Strength (UCS), effective stress, temperature and gas pressure. A total of 50 sets of data collected by a self-developed apparatus were… More >

  • Open Access


    Thermal Analysis of MHD Non-Newtonian Nanofluids over a Porous Media

    Asad Ejaz1, Imran Abbas1, Yasir Nawaz1, Muhammad Shoaib Arif1, Wasfi Shatanawi2,3,4,*, Javeria Nawaz Abbasi5

    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.3, pp. 1119-1134, 2020, DOI:10.32604/cmes.2020.012091

    Abstract In the present research, Tiwari and Das model are used for the impact of a magnetic field on non-Newtonian nanofluid flow in the presence of injection and suction. The PDEs are converted into ordinary differential equations (ODEs) using the similarity method. The obtained ordinary differential equations are solved numerically using shooting method along with RK-4. Part of the present study uses nanoparticles (NPs) like TiO2 and Al2O3 and sodium carboxymethyl cellulose (CMC/water) is considered as a base fluid (BF). This study is conducted to find the influence of nanoparticles, Prandtl number, and magnetic field on velocity More >

  • Open Access


    Performance of Geometric Multigrid Method for Two-Dimensional Burgers’ Equations with Non-Orthogonal, Structured Curvilinear Grids

    Daiane Cristina Zanatta1,*, Luciano Kiyoshi Araki2, Marcio Augusto Villela Pinto2, Diego Fernando Moro3

    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.3, pp. 1061-1081, 2020, DOI:10.32604/cmes.2020.012634

    Abstract This paper seeks to develop an efficient multigrid algorithm for solving the Burgers problem with the use of non-orthogonal structured curvilinear grids in L-shaped geometry. For this, the differential equations were discretized by Finite Volume Method (FVM) with second-order approximation scheme and deferred correction. Moreover, the algebraic method and the differential method were used to generate the non-orthogonal structured curvilinear grids. Furthermore, the influence of some parameters of geometric multigrid method, as well as lexicographical Gauss–Seidel (Lex-GS), η-line Gauss–Seidel (η-line-GS), Modified Strongly Implicit (MSI) and modified incomplete LU decomposition (MILU) solvers on the Central Processing… More >

  • Open Access


    Modelling the Effect of Self-Immunity and the Impacts of Asymptomatic and Symptomatic Individuals on COVID-19 Outbreak

    M. H. A. Biswas1,*, M. A. Islam1, S. Akter2, S. Mandal2, M. S. Khatun1, S. A. Samad1, A. K. Paul1, M. R. Khatun1

    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.3, pp. 1033-1060, 2020, DOI:10.32604/cmes.2020.012792

    Abstract COVID-19 is one of the most highly infectious diseases ever emerged and caused by newly discovered severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It has already led the entire world to health and economic crisis. It has invaded the whole universe all most every way. The present study demonstrates with a nine mutually exclusive compartmental model on transmission dynamics of this pandemic disease (COVID-19), with special focus on the transmissibility of symptomatic and asymptomatic infection from susceptible individuals. Herein, the compartmental model has been investigated with mathematical analysis and computer simulations in order to understand… More >

  • Open Access


    SEIHCRD Model for COVID-19 Spread Scenarios, Disease Predictions and Estimates the Basic Reproduction Number, Case Fatality Rate, Hospital, and ICU Beds Requirement

    Avaneesh Singh*, Manish Kumar Bajpai

    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.3, pp. 991-1031, 2020, DOI:10.32604/cmes.2020.012503

    Abstract We have proposed a new mathematical method, the SEIHCRD model, which has an excellent potential to predict the incidence of COVID-19 diseases. Our proposed SEIHCRD model is an extension of the SEIR model. Three-compartments have added death, hospitalized, and critical, which improves the basic understanding of disease spread and results. We have studied COVID-19 cases of six countries, where the impact of this disease in the highest are Brazil, India, Italy, Spain, the United Kingdom, and the United States. After estimating model parameters based on available clinical data, the model will propagate and forecast dynamic… More >

  • Open Access


    Study of Non-Pharmacological Interventions on COVID-19 Spread

    Avaneesh Singh*, Saroj Kumar Chandra, Manish Kumar Bajpai

    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.3, pp. 967-990, 2020, DOI:10.32604/cmes.2020.011601

    Abstract COVID-19 disease has emerged as one of the life threatening threat to the society. A novel beta coronavirus causes it. It began as unidentified pneumonia of unknown etiology in Wuhan City, Hubei province in China emerged in December 2019. No vaccine has been produced till now. Mathematical models are used to study the impact of different measures used to decrease pandemic. Mathematical models have been designed to estimate the numbers of spreaders in different scenarios in the present manuscript. In the present manuscript, three different mathematical models have been proposed with different scenarios, such as More >

  • Open Access


    Prediction of Proteins Associated with COVID-19 Based Ligand Designing and Molecular Modeling

    Majid Monajjemi1,*, Rahim Esmkhani2, Fatemeh Mollaamin1, Sara Shahriari3

    CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.3, pp. 907-926, 2020, DOI:10.32604/cmes.2020.012846

    Abstract Current understanding about how the virus that causes COVID-19 spreads is largely based on what is known about similar coronaviruses. Some of the Natural products are suitable drugs against SARS-CoV-2 main protease. For recognizing a strong inhibitor, we have accomplished docking studies on the major virus protease with 4 natural product species as anti COVID-19 (SARS-CoV-2), namely “Vidarabine”, “Cytarabine”, “Gemcitabine” and “Matrine” which have been extracted from Gillan’s leaves plants. These are known as Chuchaq, Trshvash, Cote-Couto and Khlvash in Iran. Among these four studied compounds, Cytarabine appears as a suitable compound with high effectiveness… More >

  • Open Access


    Study on the Soy Protein-Based Adhesive Cross-Linked by Glyoxal

    Zhigang Wu1,2,#, Jiankun Liang3,#, Hong Lei1,*, Bengang Zhang1, Xuedong Xi1, Lifen Li2

    Journal of Renewable Materials, Vol.9, No.2, pp. 205-218, 2021, DOI:10.32604/jrm.2021.013655

    Abstract Based on the ESI-MS and 13C-NMR analysis of the forms of glyoxal in acidic and alkaline solutions, the soy-based adhesive cross-linked by glyoxal was prepared in this work. The results showed that glyoxal existed in water in different forms at different pH levels. Under alkaline conditions, glyoxal transformed to glycolate through the intramolecular disproportionation reaction. Under acidic conditions, although some of glyoxal transformed to glycolate as what happened under alkaline conditions, most of glyoxal molecules existed in the form of five- or six-membered cyclic ether structure. No ethylene tetraol or free aldehyde group was actually detected More >

  • Open Access


    Ancient Materials and Substitution Materials Used in Thai Historical Masonry Structure Preservation

    Natthanan Wonganan, Chainarong Athisakul*, Peerasit Mahasuwanchai, Weerachart Tangchirapat, Raktipong Sahamitmongkol, Sutat Leelataviwat

    Journal of Renewable Materials, Vol.9, No.2, pp. 179-204, 2021, DOI:10.32604/jrm.2021.013134

    Abstract The historical structures of Thailand are some of the most fascinating ancient sites in Asia. Their architectures reveal past cultures, traditions, knowledge, and expertise. Masonry materials are the major materials used to construct the historical structures in Thailand. One of the essential problem of Thai historical structure preservation is a shortage of engineering properties data for the structural stability assessment. Moreover, the in-depth engineering properties and the suitable substitution materials for Thai historical preservation are rarely found. Therefore, the engineering properties of the ancient masonry materials have to be explored together with the development of… More >

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