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  • Open Access

    ARTICLE

    An Investigation into the Effects of the Reynolds Number on High-Speed Trains Using a Low Temperature Wind Tunnel Test Facility

    Yundong Han1, Dawei Chen1, Shaoqing Liu1, Gang Xu2

    FDMP-Fluid Dynamics & Materials Processing, Vol.16, No.1, pp. 1-19, 2020, DOI:10.32604/fdmp.2020.06525

    Abstract A series of tests have been conducted using a Cryogenic Wind Tunnel to study the effect of Reynolds number (Re) on the aerodynamic force and surface pressure experienced by a high speed train. The test Reynolds number has been varied from 1 million to 10 million, which is the highest Reynolds number a wind tunnel has ever achieved for a train test. According to our results, the drag coefficient of the leading car decreases with higher Reynolds number for yaw angles up to 30º. The drag force coefficient drops about 0.06 when Re is raised from 1 million to 10… More >

  • Open Access

    ARTICLE

    Data-Driven Structural Design Optimization for Petal-Shaped Auxetics Using Isogeometric Analysis

    Yingjun Wang1, Zhongyuan Liao1, Shengyu Shi1, *, Zhenpei Wang2, *, Leong Hien Poh3

    CMES-Computer Modeling in Engineering & Sciences, Vol.122, No.2, pp. 433-458, 2020, DOI:10.32604/cmes.2020.08680

    Abstract Focusing on the structural optimization of auxetic materials using data-driven methods, a back-propagation neural network (BPNN) based design framework is developed for petal-shaped auxetics using isogeometric analysis. Adopting a NURBS-based parametric modelling scheme with a small number of design variables, the highly nonlinear relation between the input geometry variables and the effective material properties is obtained using BPNN-based fitting method, and demonstrated in this work to give high accuracy and efficiency. Such BPNN-based fitting functions also enable an easy analytical sensitivity analysis, in contrast to the generally complex procedures of typical shape and size sensitivity approaches. More >

  • Open Access

    ARTICLE

    A Numerical Study on Hydraulic Fracturing Problems via the Proper Generalized Decomposition Method

    Daobing Wang1, *, Sergio Zlotnik2, *, Pedro Díez2, Hongkui Ge3, Fujian Zhou3, Bo Yu4

    CMES-Computer Modeling in Engineering & Sciences, Vol.122, No.2, pp. 703-720, 2020, DOI:10.32604/cmes.2020.08033

    Abstract The hydraulic fracturing is a nonlinear, fluid-solid coupling and transient problem, in most cases it is always time-consuming to simulate this process numerically. In recent years, although many numerical methods were proposed to settle this problem, most of them still require a large amount of computer resources. Thus it is a high demand to develop more effificient numerical approaches to achieve the real-time monitoring of the fracture geometry during the hydraulic fracturing treatment. In this study, a reduced order modeling technique namely Proper Generalized Decomposition (PGD), is applied to accelerate the simulations of the transient, non-linear coupled system of hydraulic… More >

  • Open Access

    ARTICLE

    Intelligent Spectrum Detection Model Based on Compressed Sensing in Cognitive Radio Network

    Yanli Ji1, *, Weidong Wang2, Yinghai Zhang2

    CMES-Computer Modeling in Engineering & Sciences, Vol.122, No.2, pp. 691-701, 2020, DOI:10.32604/cmes.2020.07861

    Abstract In view of the uncertainty of the status of primary users in cognitive networks and the fact that the random detection strategy cannot guarantee cognitive users to accurately find available channels, this paper proposes a joint random detection strategy using the idle cognitive users in cognitive wireless networks. After adding idle cognitive users for detection, the compressed sensing model is employed to describe the number of available channels obtained by the cognitive base station to derive the detection performance of the cognitive network at this time. Both theoretical analysis and simulation results show that using idle cognitive users can reduce… More >

  • Open Access

    ARTICLE

    Experimental Simulation and Numerical Modeling of Deformation and Damage Evolution of Pre-Holed Sandstones After Heat Treatment

    Shuo Yang1, Yuanhai Li1, 2, ∗, Xiaojie Tang1, 2, Jinshan Liu1, 2

    CMES-Computer Modeling in Engineering & Sciences, Vol.122, No.2, pp. 633-659, 2020, DOI:10.32604/cmes.2020.07919

    Abstract The deformation and damage evolution of sandstone after heat treatment greatly influence the efficient and safe development of deep geothermal energy extraction. To investigate this issue, laboratory confined compression tests and numerical simulations were conducted on pre-holed sandstone specimens after heat treatment. The laboratory test results show that the failure modes are closely related to the heat treatment temperature, with increasing treatment temperature, the failure modes change from mixed and shear modes to a splitting mode. The cracks always initiate from the sidewalls of the hole and then propagate. The failure process inside the hole proceeds as follows: calm period,… More >

  • Open Access

    ARTICLE

    Growing and Pruning Based Deep Neural Networks Modeling for Effective Parkinson’s Disease Diagnosis

    Kemal Akyol1, *

    CMES-Computer Modeling in Engineering & Sciences, Vol.122, No.2, pp. 619-632, 2020, DOI:10.32604/cmes.2020.07632

    Abstract Parkinson’s disease is a serious disease that causes death. Recently, a new dataset has been introduced on this disease. The aim of this study is to improve the predictive performance of the model designed for Parkinson’s disease diagnosis. By and large, original DNN models were designed by using specific or random number of neurons and layers. This study analyzed the effects of parameters, i.e., neuron number and activation function on the model performance based on growing and pruning approach. In other words, this study addressed the optimum hidden layer and neuron numbers and ideal activation and optimization functions in order… More >

  • Open Access

    ARTICLE

    Analytical and Numerical Investigation for the DMBBM Equation

    Abdulghani Alharbi1, Mahmoud A. E. Abdelrahman1, 2, *, M. B. Almatrafi1

    CMES-Computer Modeling in Engineering & Sciences, Vol.122, No.2, pp. 743-756, 2020, DOI:10.32604/cmes.2020.07996

    Abstract The nonlinear dispersive modified Benjamin-Bona-Mahony (DMBBM) equation is solved numerically using adaptive moving mesh PDEs (MMPDEs) method. Indeed, the exact solution of the DMBBM equation is obtained by using the extended Jacobian elliptic function expansion method. The current methods give a wider applicability for handling nonlinear wave equations in engineering and mathematical physics. The adaptive moving mesh method is compared with exact solution by numerical examples, where the explicit solutions are known. The numerical results verify the accuracy of the proposed method. More >

  • Open Access

    ARTICLE

    Grading Method for Hypoxic-Ischemic Encephalopathy Based on Neonatal EEG

    Jingmin Guo1, Xiu Cheng1, Duanpo Wu2, 3, *

    CMES-Computer Modeling in Engineering & Sciences, Vol.122, No.2, pp. 721-741, 2020, DOI:10.32604/cmes.2020.07470

    Abstract The grading of hypoxic-ischemic encephalopathy (HIE) contributes to the clinical decision making for neonates with HIE. In this paper, an automated grading method based on electroencephalogram (EEG) data is proposed to describe the severity of HIE infants, namely mild asphyxia, moderate asphyxia and severe asphyxia. The automated grading method is based on a multi-class support vector machine (SVM) classifier, and the input features of SVM classifier include long-term features which are extracted by decomposing the EEG data into different 64 s epoch data and short-term features which are extracted by segmenting the 64 s epoch data into 8 s epoch… More >

  • Open Access

    ARTICLE

    Mixed Noise Parameter Estimation Based on Variance Stable Transform

    Ling Ding1, 2, Huyin Zhang1, *, Jinsheng Xiao3, Junfeng Lei3, Fang Xu3, Shejie Lu2

    CMES-Computer Modeling in Engineering & Sciences, Vol.122, No.2, pp. 675-690, 2020, DOI:10.32604/cmes.2020.07987

    Abstract The ultimate goal of image denoising from video is to improve the given image, which can reduce noise interference to ensure image quality. Through denoising technology, image quality can have effectively optimized, signal-to-noise ratio can have increased, and the original mage information can have better reflected. As an important preprocessing method, people have made extensive research on image denoising algorithm. Video denoising needs to take into account the various level of noise. Therefore, the estimation of noise parameters is particularly important. This paper presents a noise estimation method based on variance stability transformation, which estimates the parameters of variance stability… More >

  • Open Access

    ARTICLE

    Stress Analysis of Printed Circuit Board with Different Thickness and Composite Materials Under Shock Loading

    Kuan-Ting Liu1, Chun-Lin Lu1, Nyan-Hwa Tai2, Meng-Kao Yeh1, *

    CMES-Computer Modeling in Engineering & Sciences, Vol.122, No.2, pp. 661-674, 2020, DOI:10.32604/cmes.2020.07792

    Abstract In this study, the deformation and stress distribution of printed circuit board (PCB) with different thickness and composite materials under a shock loading were analyzed by the finite element analysis. The standard 8-layer PCB subjected to a shock loading 1500 g was evaluated first. Moreover, the finite element models of the PCB with different thickness by stacking various number of layers were discussed. In addition to changing thickness, the core material of PCB was replaced from woven E-glass/epoxy to woven carbon fiber/epoxy for structural enhancement. The non-linear material property of copper foil was considered in the analysis. The results indicated… More >

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