Ling Ding^{1, 2}, Huyin Zhang^{1, *}, 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 >

Kuan-Ting Liu¹, Chun-Lin Lu¹, Nyan-Hwa Tai², Meng-Kao Yeh^{1, *}

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 >

Dongjie Liu¹, Jin Zhao^{1, *}, Axin Xi², Chao Wang¹, Xinnian Huang¹, Kuncheng Lai¹, Chang Liu¹

CMES-Computer Modeling in Engineering & Sciences, Vol.122, No.2, pp. 593-617, 2020, DOI:10.32604/cmes.2020.08641

Abstract With the advent of deep learning, self-driving schemes based on deep learning are becoming more and more popular. Robust perception-action models should learn from data with different scenarios and real behaviors, while current end-to-end model learning is generally limited to training of massive data, innovation of deep network architecture, and learning in-situ model in a simulation environment. Therefore, we introduce a new image style transfer method into data augmentation, and improve the diversity of limited data by changing the texture, contrast ratio and color of the image, and then it is extended to the scenarios that the model has been… More >

Siyang Piao¹, Huajiang Ouyang^{1, 2}, Yahui Zhang^{1, *}

CMES-Computer Modeling in Engineering & Sciences, Vol.122, No.2, pp. 571-591, 2020, DOI: 10.32604/cmes.2020.08789

Abstract A beam approximation method for dynamic analysis of launch vehicles modelled as stiffened cylindrical shells is proposed. Firstly, an initial beam model of the stiffened cylindrical shell is established based on the cross-sectional area equivalence principle that represents the shell skin and its longitudinal ribs as a beam with annular cross-section, and the circumferential ribs as lumped masses at the nodes of the beam elements. Then, a fine finite element model (FE model) of the stiffened cylindrical shell is constructed and a modal analysis is carried out. Finally, the initial beam model is improved through model updating against the natural… More >

Tian Li^{1, *}, Zhiyuan Dai¹, Weihua Zhang¹

CMES-Computer Modeling in Engineering & Sciences, Vol.122, No.2, pp. 555-570, 2020, DOI:10.32604/cmes.2020.08101

Abstract Detached eddy simulation has been widely applied to simulate the flow around trains in recent years. The Reynolds-averaged Navier-Stokes (RANS) model for delayed detached eddy simulation (DDES) is an essential user input. The effect of the RANS model for DDES on the aerodynamic characteristics of a train in crosswinds is investigated in this study. Three different DDES models are used, based on the Spalart-Allmaras model (SA), the realizable k-ε model (RKE), and the shear stress transport k-ω model (SST). Results show that all DDES models can give relatively accurate predictions of pressure coefficient on almost all surfaces. There are only… More >

Qing Dong^{1, *}, Bin He¹, Gening Xu¹

CMES-Computer Modeling in Engineering & Sciences, Vol.122, No.2, pp. 525-553, 2020, DOI: 10.32604/cmes.2020.08498

Abstract To compensate for the shortcomings of quasi-static law in anti-fatigue analysis of foundry crane metal structures, the fatigue life evaluation method of foundry crane metal structure considering load dynamic response and crack closure effect is proposed. In line with the theory of mechanical vibration, a dynamic model of crane structure during the working cycle is constructed, and dynamic coefficients under diverse actions are analysed. Calculation models of the internal force dynamic change process of dangerous cross-sections and a simulation model of first principal stress-time history are established by using the steel structure design criteria, which is utilised to extract the… More >

Lei Chen^{1, #}, Kanghu Bo^{2, #}, Feifei Lee^{1, *}, Qiu Chen^{1, 3, *}

CMES-Computer Modeling in Engineering & Sciences, Vol.122, No.2, pp. 505-523, 2020, DOI:10.32604/cmes.2020.08425

Abstract Scene recognition is a popular open problem in the computer vision field. Among lots of methods proposed in recent years, Convolutional Neural Network (CNN) based approaches achieve the best performance in scene recognition. We propose in this paper an advanced feature fusion algorithm using Multiple Convolutional Neural Network (MultiCNN) for scene recognition. Unlike existing works that usually use individual convolutional neural network, a fusion of multiple different convolutional neural networks is applied for scene recognition. Firstly, we split training images in two directions and apply to three deep CNN model, and then extract features from the last full-connected (FC) layer… More >

Manlika Ratchagit¹, Benchawan Wiwatanapataphee¹, Nikolai Dokuchaev^{1, *}

CMES-Computer Modeling in Engineering & Sciences, Vol.122, No.2, pp. 487-504, 2020, DOI:10.32604/cmes.2020.08865

Abstract The classical autoregressive (AR) model has been widely applied to predict future data using m past observations over five decades. As the classical AR model required m unknown parameters, this paper implements the AR model by reducing m parameters to two parameters to obtain a new model with an optimal delay called as the m-delay AR model. We derive the m-delay AR formula for approximating two unknown parameters based on the least squares method and develop an algorithm to determine optimal delay based on a brute-force technique. The performance of the m-delay AR model was tested by comparing with the… More >

Zijun Wu¹, Shuting Wang², Wenjun Shao^{3, *}, Lianqing Yu¹

CMES-Computer Modeling in Engineering & Sciences, Vol.122, No.2, pp. 459-485, 2020, DOI:10.32604/cmes.2020.08697

Abstract We propose a new approach to reuse the basis function evaluations in the numerical integration of isogeometric analysis. The concept of reusability of the basis functions is introduced according to their symmetrical, translational and proportional features on both the coarse and refined levels. Based on these features and the parametric domain regularity of each basis, we classify the bases on the original level and then reuse them on the refined level, which can reduce the time for basis calculations at integration nodes. By using the sum factorization method and the mean value theorem for the integrals, a new integration method… More >

Kei Saito^{1, 2, *}, Tei Hirashima¹, Ninshu Ma^{2, *}, Hidekazu Murakawa²

CMES-Computer Modeling in Engineering & Sciences, Vol.122, No.2, pp. 415-432, 2020, DOI:10.32604/cmes.2020.08847

Abstract A characteristic tensor is defined using stress tensor averaged in a small circular domain at the crack tip and multiplied by the root of domain radius. It possesses the original stress tensor characteristics and has a simple relationship with conventional fracture-mechanics parameters. Therefore, it can be used to estimate stress intensity factors (SIFs) for cracks of arbitrary shape subjected to multiaxial stress loads. A characteristic tensor can also be used to estimate SIFs for kinked cracks. This study examines the relation between a characteristic tensor and SIFs to demonstrate the correlation between the characteristic tensor and fracture-mechanics parameters. Consequently, a… More >