This work shows uncertainty qualification using isogeometric analysis with boundary element methods (IGABEM) based on model order reduction. The stochastic analysis is performed with Monte-Carlo simulation (MCs). IGABEM accelerates the sampling process by conducting numerical simulation directly from computer-aided design models without meshing. The Proper Orthogonal Decomposition (POD) and Radial Basis Functions (RBF) give fast approximation of system responses.
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Haojie Lian1, Zhongwang Wang2,3,*, Haowen Hu3, Shengze Li4, Xuan Peng5, Leilei Chen2,3
CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.1, pp. 1-20, 2021, DOI:10.32604/cmes.2021.016775
（This article belongs to this Special Issue: Recent Advance of the Isogeometric Boundary Element Method and its Applications)
Abstract This paper presents a novel framework for stochastic analysis of linear elastic fracture problems. Monte Carlo simulation (MCs) is adopted to address the multi-dimensional uncertainties, whose computation cost is reduced by combination of Proper Orthogonal Decomposition (POD) and the Radial Basis Function (RBF). In order to avoid re-meshing and retain the geometric exactness, isogeometric boundary element method (IGABEM) is employed for simulation, in which the Non-Uniform Rational B-splines (NURBS) are employed for representing the crack surfaces and discretizing dual boundary integral equations. The stress intensity factors (SIFs) are extracted by M integral method. The numerical examples simulate several cracked structures… More >
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I. G. Ameen1, N. A. Elkot2, M. A. Zaky3,*, A. S. Hendy4,5, E. H. Doha2
CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.1, pp. 21-41, 2021, DOI:10.32604/cmes.2021.015310
Abstract We target here to solve numerically a class of nonlinear fractional two-point boundary value problems involving
left- and right-sided fractional derivatives. The main ingredient of the proposed method is to recast the problem
into an equivalent system of weakly singular integral equations. Then, a Legendre-based spectral collocation
method is developed for solving the transformed system. Therefore, we can make good use of the advantages of the
Gauss quadrature rule. We present the construction and analysis of the collocation method. These results can be
indirectly applied to solve fractional optimal control problems by considering the corresponding Euler–Lagrange
equations. Two numerical examples… More >
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Yunxing Zhang, Shan Ma, Kangping Liao, Wenyang Duan*
CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.1, pp. 43-64, 2021, DOI:10.32604/cmes.2021.014847
Abstract In this study, a numerical model for simulating two-phase flow is developed. The Cartesian grid with Adaptive Mesh Refinement (AMR) is adopted to reduce the computational cost. An explicit projection method is used for the time integration and the Finite Difference Method (FDM) is applied on a staggered grid for the discretization of spatial derivatives. The Volume of Fluid (VOF) method with Piecewise-Linear Interface Calculation (PLIC) is extended to the AMR grid to capture the gas-water interface accurately. A coarse-fine interface treatment method is developed to preserve the flux conservation at the interfaces. Several two-dimensional (2D) and three-dimensional (3D) benchmark… More >
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Shufang Song1,*, Ruyang He1, Zhaoyin Shi1, Weiya Zhang2
CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.1, pp. 65-85, 2021, DOI:10.32604/cmes.2021.015378
Abstract The variable importance measure (VIM) can be implemented to rank or select important variables, which can effectively reduce the variable dimension and shorten the computational time. Random forest (RF) is an ensemble learning method by constructing multiple decision trees. In order to improve the prediction accuracy of random forest, advanced random forest is presented by using Kriging models as the models of leaf nodes in all the decision trees. Referring to the Mean Decrease Accuracy (MDA) index based on Out-of-Bag (OOB) data, the single variable, group variables and correlated variables importance measures are proposed to establish a complete VIM system… More >
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İlyas Kacar*
CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.1, pp. 87-108, 2021, DOI:10.32604/cmes.2021.015227
Abstract Locking nuts are widely used in industry and any defects from their manufacturing may cause loosening of the connection during their service life. In this study, simulations of the folding process of a nut’s flange made from AISI 1040 steel are performed. Besides the bilinear isotropic hardening rule, Chaboche’s nonlinear kinematic hardening rule is employed with associated flow rule and Hill48 yield criterion to set a plasticity model. The bilinear isotropic hardening rule’s parameters are determined by means of a monotonic tensile test. The Chaboche’s parameters are determined by using a low cycle tension/compression test by applying curve fitting methods… More >
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Weiping Luo1,2, Dajun Yuan1,2, Dalong Jin1,2,*, Ping Lu1,2, Jian Chen3
CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.1, pp. 109-127, 2021, DOI:10.32604/cmes.2021.015683
Abstract The control of slurry pressure aiming to be consistent with the external water and earth pressure during shield tunnelling has great significance for face stability, especially in urban areas or underwater where the surrounding environment is very sensitive to the fluctuation of slurry pressure. In this study, an optimal control method for slurry pressure during shield tunnelling is developed, which is composed of an identifier and a controller. The established identifier based on the random forest (RF) can describe the complex non-linear relationship between slurry pressure and its influencing factors. The proposed controller based on particle swarm optimization (PSO) can… More >
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Tongming Qu1, Shaocheng Di2, Y. T. Feng1,3,*, Min Wang4, Tingting Zhao3, Mengqi Wang1
CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.1, pp. 129-144, 2021, DOI:10.32604/cmes.2021.016172
（This article belongs to this Special Issue: Computational Mechanics of Granular Materials and its Engineering Applications)
Abstract This study presents an AI-based constitutive modelling framework wherein the prediction model directly learns from triaxial testing data by combining discrete element modelling (DEM) and deep learning. A constitutive learning strategy is proposed based on the generally accepted frame-indifference assumption in constructing material constitutive models. The low-dimensional principal stress-strain sequence pairs, measured from discrete element modelling of triaxial testing, are used to train recurrent neural networks, and then the predicted principal stress sequence is augmented to other high-dimensional or general stress tensor via coordinate transformation. Through detailed hyperparameter investigations, it is found that long short-term memory (LSTM) and gated recurrent… More >
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Shaomin Liang, Lu Liu, Shunying Ji*
CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.1, pp. 145-160, 2021, DOI:10.32604/cmes.2021.016403
（This article belongs to this Special Issue: Computational Mechanics of Granular Materials and its Engineering Applications)
Abstract Based on the discrete element method and hydrostatics theory, an improved Archimedes principle is proposed to
study the rules pertaining to resistance changes during the penetration process of an intruder into the particulate
materials. The results illustrate the fact that the lateral contribution to the resistance is very small, while the
tangential force of the lateral resistance originates from friction effects. Conversely, the resistance of particulate
materials on the intruder mainly occurs at the bottom part of the intruding object. Correspondingly, the factors that
determine the resistance of the bottom part of the intruding object and the rules pertaining to… More >
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Dejia Shi1, Hanzhong Zheng2,*
CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.1, pp. 161-181, 2021, DOI:10.32604/cmes.2021.014917
（This article belongs to this Special Issue: Recent Advances on Deep Learning for Medical Signal Analysis (RADLMSA))
Abstract ICU patients are vulnerable to medications, especially infusion medications, and the rate and dosage of infusion drugs may worsen the condition. The mortality prediction model can monitor the real-time response of patients to drug treatment, evaluate doctors’ treatment plans to avoid severe situations such as inverse Drug-Drug Interactions (DDI), and facilitate the timely intervention and adjustment of doctor’s treatment plan. The treatment process of patients usually has a time-sequence relation (which usually has the missing data problem) in patients’ treatment history. The state-of-the-art method to model such time-sequence is to use Recurrent Neural Network (RNN). However, sometimes, patients’ treatment can… More >
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Fouad A. Abolaban*
CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.1, pp. 183-201, 2021, DOI:10.32604/cmes.2021.015472
（This article belongs to this Special Issue: Mathematical Aspects of Computational Biology and Bioinformatics)
Abstract Various epidemics have occurred throughout history, which has led to the investigation and understanding of their transmission dynamics. As a result, non-local operators are used for mathematical modeling in this study. Therefore, this research focuses on developing a dysentery diarrhea model with the use of a fractional operator using a one-parameter Mittag–Leffler kernel. The model consists of three classes of the human population, whereas the fourth one belongs to the pathogen population. The model carefully deals with the dimensional homogeneity among the parameters and the fractional operator. In addition, the model was validated by fitting the actual number of dysentery… More >
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