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  • Open Access


    Thermodynamic Performance Analysis of Geothermal Power Plant Based on Organic Rankine Cycle (ORC) Using Mixture of Pure Working Fluids

    Abdul Sattar Laghari1, Mohammad Waqas Chandio1, Laveet Kumar2,*, Mamdouh El Haj Assad3

    Energy Engineering, Vol.121, No.8, pp. 2023-2038, 2024, DOI:10.32604/ee.2024.051082

    Abstract The selection of working fluid significantly impacts the geothermal ORC’s Efficiency. Using a mixture as a working fluid is a strategy to improve the output of geothermal ORC. In the current study, modelling and thermodynamic analysis of ORC, using geothermal as a heat source, is carried out at fixed operating conditions. The model is simulated in the Engineering Equation Solver (EES). An environment-friendly mixture of fluids, i.e., R245fa/R600a, with a suitable mole fraction, is used as the operating fluid. The mixture provided the most convenient results compared to the pure working fluid under fixed operating More >

  • Open Access


    Applying an Ordinal Priority Approach Based Neutrosophic Fuzzy Axiomatic Design Approach to Develop Sustainable Geothermal Energy Source

    Chia-Nan Wang, Thuy-Duong Thi Pham*, Nhat-Luong Nhieu

    Energy Engineering, Vol.121, No.8, pp. 2039-2064, 2024, DOI:10.32604/ee.2024.050224

    Abstract Geothermal energy is considered a renewable, environmentally friendly, especially carbon-free, sustainable energy source that can solve the problem of climate change. In general, countries with geothermal energy resources are the ones going through the ring of fire. Therefore, not every country is lucky enough to own this resource. As a country with 117 active volcanoes and within the world’s ring of fire, it is a country whose geothermal resources are estimated to be about 40% of the world’s geothermal energy potential. However, the percentage used compared to the geothermal potential is too small. Therefore, this… More >

  • Open Access


    Quantifying Uncertainty in Dielectric Solids’ Mechanical Properties Using Isogeometric Analysis and Conditional Generative Adversarial Networks

    Shuai Li1, Xiaodong Zhao1,2,*, Jinghu Zhou1, Xiyue Wang1

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 2587-2611, 2024, DOI:10.32604/cmes.2024.052203

    Abstract Accurate quantification of the uncertainty in the mechanical characteristics of dielectric solids is crucial for advancing their application in high-precision technological domains, necessitating the development of robust computational methods. This paper introduces a Conditional Generation Adversarial Network Isogeometric Analysis (CGAN-IGA) to assess the uncertainty of dielectric solids’ mechanical characteristics. IGA is utilized for the precise computation of electric potentials in dielectric, piezoelectric, and flexoelectric materials, leveraging its advantage of integrating seamlessly with Computer-Aided Design (CAD) models to maintain exact geometrical fidelity. The CGAN method is highly efficient in generating models for piezoelectric and flexoelectric materials, More >

  • Open Access


    Integrating Neighborhood Geographic Distribution and Social Structure Influence for Social Media User Geolocation

    Meng Zhang1,2, Xiangyang Luo1,2,*, Ningbo Huang2

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 2513-2532, 2024, DOI:10.32604/cmes.2024.050517

    Abstract Geolocating social media users aims to discover the real geographical locations of users from their publicly available data, which can support online location-based applications such as disaster alerts and local content recommendations. Social relationship-based methods represent a classical approach for geolocating social media. However, geographically proximate relationships are sparse and challenging to discern within social networks, thereby affecting the accuracy of user geolocation. To address this challenge, we propose user geolocation methods that integrate neighborhood geographical distribution and social structure influence (NGSI) to improve geolocation accuracy. Firstly, we propose a method for evaluating the homophily… More >

  • Open Access


    A Novel ISSA–DELM Model for Predicting Rock Mass Permeability

    Chen Xing1, Leihua Yao1,*, Yingdong Wang2

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 2825-2848, 2024, DOI:10.32604/cmes.2024.049330

    Abstract In pumped storage projects, the permeability of rock masses is a crucial parameter in engineering design and construction. The rock mass permeability coefficient (K) is influenced by various geological parameters, and previous studies aimed to establish an accurate relationship between K and geological parameters. This study uses the improved sparrow search algorithm (ISSA) to optimize the parameter settings of the deep extreme learning machine (DELM), constructing a prediction model with flexible parameter selection and high accuracy. First, the Spearman method is applied to analyze the correlation between geological parameters. A sample database is built by comprehensively… More >

  • Open Access


    Mesures d’accessibilité géographique aux soins de santé dans le district sanitaire de Bougouni au Mali

    Sidiki Traoré1,2,*

    Revue Internationale de Géomatique, Vol.33, pp. 167-182, 2024, DOI:10.32604/rig.2024.052696

    Abstract Au Mali, l’accès à la santé est une préoccupation majeure. Il est devenu une priorité nationale depuis la déclaration d’Alma-Ata en 1978. Dès lors, des efforts importants ont été consentis par l’État et ses partenaires pour atteindre cet objectif. Ces efforts semblent insuffisants dans le district sanitaire de Bougouni, car, plus de la moitié de la population reste très loin des services de santé de base. Face à ce constat, évaluer l’accessibilité géographique aux soins de santé est essentiel pour identifier les localités qui ont été laissées pour compte, d’’où l’objet de cette recherche dans… More >

  • Open Access


    A Harmonic Approach to Handwriting Style Synthesis Using Deep Learning

    Mahatir Ahmed Tusher1, Saket Choudary Kongara1, Sagar Dhanraj Pande2, SeongKi Kim3,*, Salil Bharany4,*

    CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 4063-4080, 2024, DOI:10.32604/cmc.2024.049007

    Abstract The challenging task of handwriting style synthesis requires capturing the individuality and diversity of human handwriting. The majority of currently available methods use either a generative adversarial network (GAN) or a recurrent neural network (RNN) to generate new handwriting styles. This is why these techniques frequently fall short of producing diverse and realistic text pictures, particularly for terms that are not commonly used. To resolve that, this research proposes a novel deep learning model that consists of a style encoder and a text generator to synthesize different handwriting styles. This network excels in generating conditional… More >

  • Open Access


    Generalized nth-Order Perturbation Method Based on Loop Subdivision Surface Boundary Element Method for Three-Dimensional Broadband Structural Acoustic Uncertainty Analysis

    Ruijin Huo1,2,3, Qingxiang Pei1,2,3, Xiaohui Yuan1,*, Yanming Xu3

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.2, pp. 2053-2077, 2024, DOI:10.32604/cmes.2024.049185

    Abstract In this paper, a generalized th-order perturbation method based on the isogeometric boundary element method is proposed for the uncertainty analysis of broadband structural acoustic scattering problems. The Burton-Miller method is employed to solve the problem of non-unique solutions that may be encountered in the external acoustic field, and the th-order discretization formulation of the boundary integral equation is derived. In addition, the computation of loop subdivision surfaces and the subdivision rules are introduced. In order to confirm the effectiveness of the algorithm, the computed results are contrasted and analyzed with the results under Monte More >

  • Open Access


    A Distributionally Robust Optimization Scheduling Model for Regional Integrated Energy Systems Considering Hot Dry Rock Co-Generation

    Hao Qi1, Mohamed Sharaf2, Andres Annuk3, Adrian Ilinca4, Mohamed A. Mohamed5,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.2, pp. 1387-1404, 2024, DOI:10.32604/cmes.2024.048672

    Abstract Hot dry rock (HDR) is rich in reserve, widely distributed, green, low-carbon, and has broad development potential and prospects. In this paper, a distributionally robust optimization (DRO) scheduling model for a regionally integrated energy system (RIES) considering HDR co-generation is proposed. First, the HDR-enhanced geothermal system (HDR-EGS) is introduced into the RIES. HDR-EGS realizes the thermoelectric decoupling of combined heat and power (CHP) through coordinated operation with the regional power grid and the regional heat grid, which enhances the system wind power (WP) feed-in space. Secondly, peak-hour loads are shifted using price demand response guidance More >

  • Open Access


    Comprehensive Analysis of Gender Classification Accuracy across Varied Geographic Regions through the Application of Deep Learning Algorithms to Speech Signals

    Abhishek Singhal*, Devendra Kumar Sharma

    Computer Systems Science and Engineering, Vol.48, No.3, pp. 609-625, 2024, DOI:10.32604/csse.2023.046730

    Abstract This article presents an exhaustive comparative investigation into the accuracy of gender identification across diverse geographical regions, employing a deep learning classification algorithm for speech signal analysis. In this study, speech samples are categorized for both training and testing purposes based on their geographical origin. Category 1 comprises speech samples from speakers outside of India, whereas Category 2 comprises live-recorded speech samples from Indian speakers. Testing speech samples are likewise classified into four distinct sets, taking into consideration both geographical origin and the language spoken by the speakers. Significantly, the results indicate a noticeable difference… More >

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