Fan Yang^1,2,3,*, Jianwei Ren^1,2

CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.2, pp. 801-814, 2020, DOI:10.32604/cmes.2020.08889

Abstract Based on the rapid simulation of Markov Chain on samples in failure region, a novel method of reliability analysis combining Monte Carlo Markov Chain (MCMC) with random forest algorithm was proposed. Firstly, a series of samples distributing around limit state function are generated by MCMC. Then, the samples were taken as training data to establish the random forest model. Afterwards, Monte Carlo simulation was used to evaluate the failure probability. Finally, examples demonstrate the proposed method possesses higher computational efficiency and accuracy. More >

Jiaqi He¹, Yangjun Luo^1,2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.2, pp. 777-800, 2020, DOI:10.32604/cmes.2020.010688

Abstract For structures that only the predicted bounds of uncertainties are available, this study proposes a Bayesian method to logically evaluate the nonprobabilistic reliability of structures based on multi-ellipsoid convex model and performance test data. According to the given interval ranges of uncertainties, we determine the initial characteristic parameters of a multi-ellipsoid convex set. Moreover, to update the plausibility of characteristic parameters, a Bayesian network for the information fusion of prior uncertainty knowledge and subsequent performance test data is constructed. Then, an updated multi-ellipsoid set with the maximum likelihood of the performance test data can be More >

Junfu Zhu¹, Qian Yin^1,2,*, Hongwen Jing¹, Xinshuai Shi¹, Minliang Chen^1,3

CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.2, pp. 725-753, 2020, DOI:10.32604/cmes.2020.012648

Abstract This study experimentally and numerically investigated the anchorage properties, bolt force evolution, deformation and stress fields of blocky rock mass with various dip angles of joint surfaces under an applied axial load. The results show that due to bolt reinforcement, the axial stress-strain curves of anchorage blocky rock mass show typical strain-hardening characteristics, and compared with models without anchorage, the peak strength and elastic modulus increase by 21.56% and 20.0%, respectively. With an increase in axial stress, the lateral strain continuously increases, and restriction effects of bolts reduce the overall deformation of model surfaces. The… More >

Xianghui Lu¹, Junliang Fan², Lifeng Wu^1,*, Jianhua Dong³

CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.2, pp. 699-723, 2020, DOI:10.32604/cmes.2020.011004

Abstract It is important for regional water resources management to know the agricultural water consumption information several months in advance. Forecasting reference evapotranspiration (ET₀) in the next few months is important for irrigation and reservoir management. Studies on forecasting of multiple-month ahead ET₀ using machine learning models have not been reported yet. Besides, machine learning models such as the XGBoost model has multiple parameters that need to be tuned, and traditional methods can get stuck in a regional optimal solution and fail to obtain a global optimal solution. This study investigated the performance of the hybrid extreme… More >

S. Jerald Nirmal Kumar^1,*, S. Ravimaran², M. M. Gowthul Alam³

CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.2, pp. 671-697, 2020, DOI:10.32604/cmes.2020.09361

Abstract Nowadays, succeeding safe communication and protection-sensitive data from unauthorized access above public networks are the main worries in cloud servers. Hence, to secure both data and keys ensuring secured data storage and access, our proposed work designs a Novel Quantum Key Distribution (QKD) relying upon a non-commutative encryption framework. It makes use of a Novel Quantum Key Distribution approach, which guarantees high level secured data transmission. Along with this, a shared secret is generated using Diffie Hellman (DH) to certify secured key generation at reduced time complexity. Moreover, a non-commutative approach is used, which effectively More >

S. Velliangiri^1,*, J. Premalatha²

CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.2, pp. 625-645, 2020, DOI:10.32604/cmes.2020.010869

Abstract Different devices in the recent era generated a vast amount of digital video. Generally, it has been seen in recent years that people are forging the video to use it as proof of evidence in the court of justice. Many kinds of researches on forensic detection have been presented, and it provides less accuracy. This paper proposed a novel forgery detection technique in image frames of the videos using enhanced Convolutional Neural Network (CNN). In the initial stage, the input video is taken as of the dataset and then converts the videos into image frames. More >

Jiachen Guo^1,2, Yunfei Xu², Zhenyu Jiang^1,*, Xiaoyi Liu², Yang Cai^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.2, pp. 611-623, 2020, DOI:10.32604/cmes.2020.011148

Abstract Both of Buckling and post-buckling are fundamental problems of geometric nonlinearity in solid mechanics. With the rapid development of nanotechnology in recent years, buckling behaviors in nanobeams receive more attention due to its applications in sensors, actuators, transistors, probes, and resonators in nanoelectromechanical systems (NEMS) and biotechnology. In this work, buckling and post-buckling of copper nanobeam under uniaxial compression are investigated with theoretical analysis and atomistic simulations. Different cross sections are explored for the consideration of surface effects. To avoid complicated high order buckling modes, a stressbased simplified model is proposed to analyze the critical… More >

Xing Deng^1,2, Haijian Shao^1,2,*, Liang Shi³, Xia Wang^4,5, Tongling Xie⁶

CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.2, pp. 579-596, 2020, DOI:10.32604/cmes.2020.011920

Abstract The Coronavirus Disease 2019 (COVID-19) is wreaking havoc around the world, bring out that the enormous pressure on national health and medical staff systems. One of the most effective and critical steps in the fight against COVID-19, is to examine the patient’s lungs based on the Chest X-ray and CT generated by radiation imaging. In this paper, five keras-related deep learning models: ResNet50, InceptionResNetV2, Xception, transfer learning and pre-trained VGGNet16 is applied to formulate an classification–detection approaches of COVID-19. Two benchmark methods SVM (Support Vector Machine), CNN (Convolutional Neural Networks) are provided to compare with More >

Anber Saleem^1,2, Salman Akhtar³, Sohail Nadeem^3,*, Alibek Issakhov⁴, Mehdi Ghalambaz^5,6

CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.2, pp. 565-577, 2020, DOI:10.32604/cmes.2020.011883

Abstract The blood flow through a catheterized artery having a mild stenosis at the wall together with a blood clot at the centre is studied in the current investigation. Stenosis can occur in vessels carrying blood to brain (i.e., Carotid arteries), Renal arteries that supply blood to kidneys etc. The flow is refined in such vessels by application of catheter. We have used a Newtonian viscous fluid model and also distinct shapes of stenosis, (i.e., symmetric and non-symmetric shapes) are considered for this study. The entropy generation together with viscous dissipation is also taken into account… More >

Jingfa Li¹, Bo Yu^1,*, Qianqian Shao², Dongliang Sun¹

CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.2, pp. 541-563, 2020, DOI:10.32604/cmes.2020.011835

Abstract In this work, the drag-reducing mechanism of high-Reynoldsnumber turbulent channel flow with surfactant additives is investigated by using large eddy simulation (LES) method. An N-parallel finitely extensible nonlinear elastic model with Peterlin’s approximation (FENE-P) is used to describe the rheological behaviors of non-Newtonian fluid with surfactant. To close the filtered LES equations, a hybrid subgrid scale (SGS) model coupling the spatial filter and temporal filter is applied to compute the subgrid stress and other subfilter terms. The finite difference method and projection algorithm are adopted to solve the LES governing equations. To validate the correctness More >