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  • Open Access

    ARTICLE

    DETAILED ANALYSIS OF AN ENDOREVERSIBLE FUEL CELL : MAXIMUM POWER AND OPTIMAL OPERATING TEMPERATURE DETERMINATION

    Alexandre Vaudreya,*, Philippe Baucourb, François Lanzettab, Raynal Glisesb

    Frontiers in Heat and Mass Transfer, Vol.3, No.3, pp. 1-8, 2012, DOI:10.5098/hmt.v3.3.3001

    Abstract Producing electrical work in consuming chemical energy, the fuel cell (FC) is forced by the 2nd law to reject heat to its surrounding. However, as it occurs for any other type of engine, this thermal energy cannot be exchanged in an isothermal way in finite time or through finite areas. As it was already done for various types of systems, including chemical engines, the fuel cell is here studied within the finite time thermodynamics framework. An endoreversible fuel cell is then defined, internally reversible but producing entropy during heat exchanges with its ambiance. Considering usual H2/O2 and H2/air chemical reactions… More >

  • Open Access

    ARTICLE

    Maximum Correntropy Criterion-Based UKF for Loosely Coupling INS and UWB in Indoor Localization

    Yan Wang*, You Lu, Yuqing Zhou, Zhijian Zhao

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2673-2703, 2024, DOI:10.32604/cmes.2023.046743

    Abstract Indoor positioning is a key technology in today’s intelligent environments, and it plays a crucial role in many application areas. This paper proposed an unscented Kalman filter (UKF) based on the maximum correntropy criterion (MCC) instead of the minimum mean square error criterion (MMSE). This innovative approach is applied to the loose coupling of the Inertial Navigation System (INS) and Ultra-Wideband (UWB). By introducing the maximum correntropy criterion, the MCCUKF algorithm dynamically adjusts the covariance matrices of the system noise and the measurement noise, thus enhancing its adaptability to diverse environmental localization requirements. Particularly in the presence of non-Gaussian noise,… More >

  • Open Access

    ARTICLE

    Natural Convection and Irreversibility of Nanofluid Due to Inclined Magnetohydrodynamics (MHD) Filled in a Cavity with Y-Shape Heated Fin: FEM Computational Configuration

    Afraz Hussain Majeed1, Rashid Mahmood2, Sayed M. Eldin3, Imran Saddique4,5,*, S. Saleem6, Muhammad Jawad7

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1505-1519, 2024, DOI:10.32604/cmes.2023.030255

    Abstract This study explains the entropy process of natural convective heating in the nanofluid-saturated cavity in a heated fin and magnetic field. The temperature is constant on the Y-shaped fin, insulating the top wall while the remaining walls remain cold. All walls are subject to impermeability and non-slip conditions. The mathematical modeling of the problem is demonstrated by the continuity, momentum, and energy equations incorporating the inclined magnetic field. For elucidating the flow characteristics Finite Element Method (FEM) is implemented using stable FE pair. A hybrid fine mesh is used for discretizing the domain. Velocity and thermal plots concerning parameters are… More >

  • Open Access

    ARTICLE

    Optical Fibre Communication Feature Analysis and Small Sample Fault Diagnosis Based on VMD-FE and Fuzzy Clustering

    Xiangqun Li1,*, Jiawen Liang2, Jinyu Zhu2, Shengping Shi2, Fangyu Ding2, Jianpeng Sun2, Bo Liu2

    Energy Engineering, Vol.121, No.1, pp. 203-219, 2024, DOI:10.32604/ee.2023.029295

    Abstract To solve the problems of a few optical fibre line fault samples and the inefficiency of manual communication optical fibre fault diagnosis, this paper proposes a communication optical fibre fault diagnosis model based on variational modal decomposition (VMD), fuzzy entropy (FE) and fuzzy clustering (FC). Firstly, based on the OTDR curve data collected in the field, VMD is used to extract the different modal components (IMF) of the original signal and calculate the fuzzy entropy (FE) values of different components to characterize the subtle differences between them. The fuzzy entropy of each curve is used as the feature vector, which… More >

  • Open Access

    ARTICLE

    Deep Learning-Enhanced Brain Tumor Prediction via Entropy-Coded BPSO in CIELAB Color Space

    Mudassir Khalil1, Muhammad Imran Sharif2,*, Ahmed Naeem3, Muhammad Umar Chaudhry1, Hafiz Tayyab Rauf4,*, Adham E. Ragab5

    CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 2031-2047, 2023, DOI:10.32604/cmc.2023.043687

    Abstract Early detection of brain tumors is critical for effective treatment planning. Identifying tumors in their nascent stages can significantly enhance the chances of patient survival. While there are various types of brain tumors, each with unique characteristics and treatment protocols, tumors are often minuscule during their initial stages, making manual diagnosis challenging, time-consuming, and potentially ambiguous. Current techniques predominantly used in hospitals involve manual detection via MRI scans, which can be costly, error-prone, and time-intensive. An automated system for detecting brain tumors could be pivotal in identifying the disease in its earliest phases. This research applies several data augmentation techniques… More >

  • Open Access

    ARTICLE

    Fusion of Region Extraction and Cross-Entropy SVM Models for Wheat Rust Diseases Classification

    Deepak Kumar1, Vinay Kukreja1, Ayush Dogra1,*, Bhawna Goyal2, Talal Taha Ali3

    CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 2097-2121, 2023, DOI:10.32604/cmc.2023.044287

    Abstract Wheat rust diseases are one of the major types of fungal diseases that cause substantial yield quality losses of 15%–20% every year. The wheat rust diseases are identified either through experienced evaluators or computerassisted techniques. The experienced evaluators take time to identify the disease which is highly laborious and too costly. If wheat rust diseases are predicted at the development stages, then fungicides are sprayed earlier which helps to increase wheat yield quality. To solve the experienced evaluator issues, a combined region extraction and cross-entropy support vector machine (CE-SVM) model is proposed for wheat rust disease identification. In the proposed… More >

  • Open Access

    ARTICLE

    Short-Term Wind Power Prediction Based on ICEEMDAN-SE-LSTM Neural Network Model with Classifying Seasonal

    Shumin Sun1, Peng Yu1, Jiawei Xing1, Yan Cheng1, Song Yang1, Qian Ai2,*

    Energy Engineering, Vol.120, No.12, pp. 2761-2782, 2023, DOI:10.32604/ee.2023.042635

    Abstract Wind power prediction is very important for the economic dispatching of power systems containing wind power. In this work, a novel short-term wind power prediction method based on improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) and (long short-term memory) LSTM neural network is proposed and studied. First, the original data is prepossessed including removing outliers and filling in the gaps. Then, the random forest algorithm is used to sort the importance of each meteorological factor and determine the input climate characteristics of the forecast model. In addition, this study conducts seasonal classification of the annual data where… More >

  • Open Access

    ARTICLE

    ENTROPY GENERATION IN BOUNDARY LAYER FLOW OF A MICRO POLAR FLUID OVER A STRETCHING SHEET EMBEDDED IN A HIGHLY ABSORBING MEDIUM

    M. Y. Abdollahzadeh Jamalabadi*

    Frontiers in Heat and Mass Transfer, Vol.6, pp. 1-13, 2015, DOI:10.5098/hmt.6.7

    Abstract An analytical study of entropy generation in steady boundary layer flow, heat and mass transfer characteristic of 2D convective flow of a micro polar fluid over a stretching sheet embedded through a highly absorbing medium is performed. The governing equations are continuity, momentum boundary layer, micro rotation, and energy takes into account of Rosseland approximation for thermal radiation sources are solved analytically. The governing system of partial differential equations is first transformed into a system of non-linear ordinary differential equations using similarity transformation. The transformed equations are non-linear coupled differential equations which are then linearized by quasi-linearization method and solved… More >

  • Open Access

    ARTICLE

    THERMODYNAMIC ANALYSIS FOR THE MHD FLOW OF TWO IMMISCIBLE MICROPOLAR FLUIDS BETWEEN TWO PARALLEL PLATES

    J. Srinivas*, J. V. Ramana Murthy

    Frontiers in Heat and Mass Transfer, Vol.6, pp. 1-11, 2015, DOI:10.5098/hmt.6.4

    Abstract The paper aims the heat transfer analysis for the flow of two immiscible micropolar fluids inside a horizontal channel, by the first and second laws of thermodynamics under the action of an imposed transverse magnetic field. The plates of the channel are maintained at constant temperatures higher than that of the fluid. The flow region consists of two zones, the flow of the heavier fluid taking place in the lower zone. The condition of hyper-stick is taken on the plates and continuity of velocity, micro-rotation, temperature, heat flux, shear stress and couple stress are imposed at the interface. The velocity,… More >

  • Open Access

    ARTICLE

    MHD MIXED CONVECTION AND ENTROPY GENERATION IN A 3D LID-DRIVEN CAVITY

    Lioua Kolsia,b,*

    Frontiers in Heat and Mass Transfer, Vol.7, pp. 1-10, 2016, DOI:10.5098/hmt.7.26

    Abstract In this study, the effects of Richardson and Hartmann numbers on heat and mass transfer in a three-dimensional lid-driven cubical cavity subjected to a uniform magnetic field are investigated numerically. The lid is maintained at constant high temperature and is moving downwards in the negative y-direction. The wall opposite to the lid is stationary and maintained at constant low temperature, and all other walls are kept adiabatic. Entropy generation is also calculated to investigate the nature of irreversibility in heat transfer inside the cavity. The computations are performed for the Richardson numbers 10 and 100, and Hartmann number in the… More >

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