Home / Journals / CMES / Vol.115, No.1, 2018
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  • Open AccessOpen Access

    ARTICLE

    Statistical Multiscale Analysis of Transient Conduction and Radiation Heat Transfer Problem in Random Inhomogeneous Porous Materials

    Yiqiang Li1, Liang Ma2, Zhiqiang Yang3, Xiaofei Guan4, Yufeng Nie1, Zihao Yang1, 2
    CMES-Computer Modeling in Engineering & Sciences, Vol.115, No.1, pp. 1-24, 2018, DOI:10.3970/cmes.2018.115.001
    Abstract This paper is devoted to the homogenization and statistical multiscale analysis of a transient heat conduction problem in random porous materials with a nonlinear radiation boundary condition. A novel statistical multiscale analysis method based on the two-scale asymptotic expansion is proposed. In the statistical multiscale formulations, a unified linear homogenization procedure is established and the second-order correctors are introduced for modeling the nonlinear radiative heat transfer in random perforations, which are our main contributions. Besides, a numerical algorithm based on the statistical multiscale method is given in details. Numerical results prove the accuracy and efficiency of our method for multiscale… More >

  • Open AccessOpen Access

    ARTICLE

    Grey Wolf Optimizer to Real Power Dispatch with Non-Linear Constraints

    G. R. Venkatakrishnan1,*, R. Rengaraj2, S. Salivahanan3
    CMES-Computer Modeling in Engineering & Sciences, Vol.115, No.1, pp. 25-45, 2018, DOI:10.3970/cmes.2018.115.025
    Abstract A new and efficient Grey Wolf Optimization (GWO) algorithm is implemented to solve real power economic dispatch (RPED) problems in this paper. The nonlinear RPED problem is one the most important and fundamental optimization problem which reduces the total cost in generating real power without violating the constraints. Conventional methods can solve the ELD problem with good solution quality with assumptions assigned to fuel cost curves without which these methods lead to suboptimal or infeasible solutions. The behavior of grey wolves which is mimicked in the GWO algorithm are leadership hierarchy and hunting mechanism. The leadership hierarchy is simulated using… More >

  • Open AccessOpen Access

    ARTICLE

    Simulation of Stochastic Ice Force Process of Vertical Offshore Structure Based on Spectral Model

    Tianyu Wu1, Wenliang Qiu1,*
    CMES-Computer Modeling in Engineering & Sciences, Vol.115, No.1, pp. 47-66, 2018, DOI:10.3970/cmes.2018.115.047
    Abstract The action of drifting ice floes may induce strong vibrations of offshore structures, and further reduce the structural safety and serviceability. The aim of this paper is to develop a method by considering ice crushing as a stochastic process. On the basis of ice force spectrum which considers the time and spatial correlation between the local ice forces, a simulation methodology to generate the stochastic ice forces process of vertical offshore structure is proposed. The crucial segment in the simulation is to accurately calculate the effective ice pressure, and it is accomplished by an empirical formula which can provide a… More >

  • Open AccessOpen Access

    ARTICLE

    Three-Variable Shifted Jacobi Polynomials Approach for Numerically Solving Three-Dimensional Multi-Term Fractional-Order PDEs with Variable Coefficients

    Jiaquan Xie1,3,*, Fuqiang Zhao1,3, Zhibin Yao1,3, Jun Zhang1,2
    CMES-Computer Modeling in Engineering & Sciences, Vol.115, No.1, pp. 67-84, 2018, DOI:10.3970/cmes.2018.115.067
    Abstract In this paper, the three-variable shifted Jacobi operational matrix of fractional derivatives is used together with the collocation method for numerical solution of three-dimensional multi-term fractional-order PDEs with variable coefficients. The main characteristic behind this approach is that it reduces such problems to those of solving a system of algebraic equations which greatly simplifying the problem. The approximate solutions of nonlinear fractional PDEs with variable coefficients thus obtained by three-variable shifted Jacobi polynomials are compared with the exact solutions. Furthermore some theorems and lemmas are introduced to verify the convergence results of our algorithm. Lastly, several numerical examples are presented… More >

  • Open AccessOpen Access

    ARTICLE

    Loose Gangues Backfill Body’s Acoustic Emissions Rules During Compaction Test: Based on Solid Backfill Mining

    Junmeng Li1, Yanli Huang1, Wenyue Qi1, Guoqiang Kong1, Tianqi Song1
    CMES-Computer Modeling in Engineering & Sciences, Vol.115, No.1, pp. 85-103, 2018, DOI:10.3970/cmes.2018.115.085
    Abstract In fully mechanized solid backfilling mining (FMSBM), the loose gangues backfill body (LGBB) that filled into the goaf becomes the main body of bearing the overburden load. The deformation resistance of LGBB is critical for controlling overburden movement and surface subsidence. During the process of load bearing, LGBB will experience grain crushing, which has a significant effect on its deformation resistance. Gangues block will be accompanied with obvious acoustic emissions (AE) features in process of slipping, flipping and damaging. Under confined compression test, monitoring the AE parameters of LGBB can reveal the impact mechanism of grain crushing on LGBB deformation.… More >

  • Open AccessOpen Access

    ARTICLE

    Neural Network-Based Second Order Reliability Method (NNBSORM) for Laminated Composite Plates in Free Vibration

    Mena E. Tawfik1, 2, Peter L. Bishay3, *, Edward A. Sadek1
    CMES-Computer Modeling in Engineering & Sciences, Vol.115, No.1, pp. 105-129, 2018, DOI:10.3970/cmes.2018.115.105
    Abstract Monte Carlo Simulations (MCS), commonly used for reliability analysis, require a large amount of data points to obtain acceptable accuracy, even if the Subset Simulation with Importance Sampling (SS/IS) methods are used. The Second Order Reliability Method (SORM) has proved to be an excellent rapid tool in the stochastic analysis of laminated composite structures, when compared to the slower MCS techniques. However, SORM requires differentiating the performance function with respect to each of the random variables involved in the simulation. The most suitable approach to do this is to use a symbolic solver, which renders the simulations very slow, although… More >

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