Weihong Han¹, Zhihong Tian^1,*, Zizhong Huang², Lin Zhong³, Yan Jia²

CMC-Computers, Materials & Continua, Vol.59, No.1, pp. 167-180, 2019, DOI:10.32604/cmc.2019.05192

Abstract Network Security Situation Awareness System YHSAS acquires, understands and displays the security factors which cause changes of network situation, and predicts the future development trend of these security factors. YHSAS is developed for national backbone network, large network operators, large enterprises and other large-scale network. This paper describes its architecture and key technologies: Network Security Oriented Total Factor Information Collection and High-Dimensional Vector Space Analysis, Knowledge Representation and Management of Super Large-Scale Network Security, Multi-Level, Multi-Granularity and Multi-Dimensional Network Security Index Construction Method, Multi-Mode and Multi-Granularity Network Security Situation Prediction Technology, and so on. The performance tests show that YHSAS… More >

Xiaoying Zhuang^1,2,*, Shuai Zhou^3,4

CMC-Computers, Materials & Continua, Vol.59, No.1, pp. 57-77, 2019, DOI:10.32604/cmc.2019.04589

Abstract Advances in machine learning (ML) methods are important in industrial engineering and attract great attention in recent years. However, a comprehensive comparative study of the most advanced ML algorithms is lacking. Six integrated ML approaches for the crack repairing capacity of the bacteria-based self-healing concrete are proposed and compared. Six ML algorithms, including the Support Vector Regression (SVR), Decision Tree Regression (DTR), Gradient Boosting Regression (GBR), Artificial Neural Network (ANN), Bayesian Ridge Regression (BRR) and Kernel Ridge Regression (KRR), are adopted for the relationship modeling to predict crack closure percentage (CCP). Particle Swarm Optimization (PSO) is used for the hyper-parameters… More >

S. K. Panthi¹, Sanjeev Saxena²

CMC-Computers, Materials & Continua, Vol.32, No.1, pp. 15-28, 2012, DOI:10.3970/cmc.2012.032.015

Abstract Sheet metal forming process like deep drawing subjected to large irreversible deformation. It leads to high strain localization zones and then internal or superficial micro defects. The deformation behavior and crack initiation in cylindrical deep drawing of aluminum alloy are simulated by the elasto-plastic finite element simulation. A1100-O and A2024-T4 sheet material are used in the simulation. Material properties based on the tensile and plane strain test is used in the simulation. Six cases are simulated in this study with different blank diameter. The simulated results are compared with the experimental results in terms of the crack location and critical… More >

Y.J. Chen¹, N. Huber^1,2

CMC-Computers, Materials & Continua, Vol.29, No.1, pp. 1-14, 2012, DOI:10.3970/cmc.2012.029.001

Abstract Gear transmission is important in engineering due to its high efficiency in transferring both power and motion. As a surface phenomenon, wear may change the gear geometry, cause a non-uniform gear rate and increase dynamic effects, all of which can lead to reduced efficiency and even severe tooth failure. In numerical predictions of wear, the conventional method, where the contact pressure over the slip distance is integrated, will cause a computation bottle-neck. To obtain an accurate integration of the wear within the small, fast moving contact area, the finite element model needs to be meshed very finely, and the time… More >

Seon Doo Jo¹, Chan Kyu Park², Jae Hong Jeong², Seung Hoon Lee², Seung Hee Kwon³

CMC-Computers, Materials & Continua, Vol.27, No.3, pp. 189-210, 2012, DOI:10.3970/cmc.2011.027.189

Abstract When concrete is being pumped, a lubricating layer forms at the interface of the inner concrete and the wall of the pipe. The lubricating layer is one of the most dominant factors in determining the pumping capability, yet no study has endeavored to quantitatively estimate the thickness and rheological properties of the layer. Recently, there has been a growing demand for large-scale construction under extreme conditions, such as high-rise buildings and super-long span bridges. This demand has heightened the need for more accurate predictions of pumpability.
A possible mechanism that contributes to the formation of the lubricating layer is shear-induced… More >

Deli Gao¹, Zengxin Zhao²

CMC-Computers, Materials & Continua, Vol.26, No.2, pp. 157-166, 2011, DOI:10.3970/cmc.2011.026.157

Abstract The research on casing corrosion in sour environment by a synergism of sweet corrosion and H₂S corrosion has become the basis of casing selection and casing string safety evaluation with more and more sour reservoirs containing high H₂S concentration being developed. It is essential to scientifically utilize casing service ability and reasonably control production rate of gas well to achieve the effective and safe developing of gas resources during the safety period of casing service with a precise casing life prediction. Scanning electron microscopy and tensile testing were applied to investigate the corrosion of TP110TS tube steel in stimulant solution… More >

W. Liu, X. Y. Su, Y. R. An, K. F. Huang¹

CMC-Computers, Materials & Continua, Vol.25, No.2, pp. 177-194, 2011, DOI:10.3970/cmc.2011.025.177

Abstract Local buckling is a typical failure mode of large scale composite wind turbine blades. A procedure for predicting the onset and location of local buckling of composite wind turbine blades under aerodynamic loads is proposed in this paper. This procedure is distinct from its counterparts in adopting the pressure distributions obtained from Computational Fluid Dynamics (CFD) calculations as the loads. The finite element method is employed to investigate local buckling resistance of the composite blade. To address the mismatch between the unstructured CFD grids of the blade surface and the finite shell elements used during the buckling analysis, an interpolation… More >

Shurong Li^1,*, Yulei Ge², Renlin Zang²

CMES-Computer Modeling in Engineering & Sciences, Vol.114, No.1, pp. 95-116, 2018, DOI:10.3970/cmes.2018.114.095

Abstract In this paper, an interacting multiple-model (IMM) method based on data-driven identification model is proposed for the prediction of nonlinear dynamic systems. Firstly, two basic models are selected as combination components due to their proved effectiveness. One is Gaussian process (GP) model, which can provide the predictive variance of the predicted output and only has several optimizing parameters. The other is regularized extreme learning machine (RELM) model, which can improve the over-fitting problem resulted by empirical risk minimization principle and enhances the overall generalization performance. Then both of the models are updated continually using meaningful new data selected by data… More >

Sunil Kr. Jha¹, Zulfiqar Ahmad²

CMES-Computer Modeling in Engineering & Sciences, Vol.113, No.4, pp. 443-459, 2017, DOI:10.3970/cmes.2017.113.443

Abstract Microbial population and enzyme activities are the significant indicators of soil strength. Soil microbial dynamics characterize microbial population and enzyme activities. The present study explores the development of efficient predictive modeling systems for the estimation of specific soil microbial dynamics, like rock phosphate solubilization, bacterial population, and ACC-deaminase activity. More specifically, optimized subtractive clustering (SC) and Wang and Mendel's (WM) fuzzy inference systems (FIS) have been implemented with the objective to achieve the best estimation accuracy of microbial dynamics. Experimental measurements were performed using controlled pot experiment using minimal salt media with rock phosphate as sole carbon source inoculated with… More >

Hui Yin¹, Dejie Yu^1,2, Shengwen Yin¹, Baizhan Xia¹

CMES-Computer Modeling in Engineering & Sciences, Vol.109-110, No.3, pp. 221-246, 2015, DOI:10.3970/cmes.2015.109.221

Abstract This paper presents a new hybrid Chebyshev-perturbation method (HCPM) for the prediction of acoustic field with random and interval parameters. In HCPM, the perturbation method based on the first-order Taylor series that accounts for the random uncertainty is organically integrated with the first-order Chebyshev polynomials that deal with the interval uncertainty; specifically, a random interval function is firstly expanded with the first-order Taylor series by treating the interval variables as constants, and the expressions of the expectation and variance can be obtained by using the random moment method; then the expectation and variance of the function are approximated by using… More >