Masanori Honda^1,3, Chikara Kawamura^1,3, Isamu Kizaki¹, Yoichi Miyajima¹, Akihiro Takezawa^2,*, Mitsuru Kitamura³

CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.2, pp. 731-742, 2021, DOI:10.32604/cmes.2021.016181

Abstract A body frame composed of thin sheet metal is a crucial structure that determines the safety performance of a vehicle. Designing a correct weight and high-performance automotive body is an emerging engineering problem. To improve the performance of the automotive frame, we attempt to reconstruct its design criteria based on statistical and mechanical approaches. At first, a fundamental study on the frame strength is conducted and a cross-sectional shape optimization problem is developed for designing the cross-sectional shape of an automobile frame having a very high mass efficiency for strength. Shape optimization is carried out using the nonlinear finite element… More >

Hung-Chun Yang, Tz-Cheng Chiu^*

CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.2, pp. 639-668, 2021, DOI:10.32604/cmes.2021.016159

Abstract An implicit integration scheme was developed for simulating the viscoplastic constitutive behavior of Sn3.0Ag0.5Cu solder and programmed into a user material subroutine of the finite element software ANSYS. The numerical procedure first solves the essential state variables by using a three-level iterative procedure, and updates the remaining stress and state variables accordingly. The numerical implementation was applied to consider the responses of solder joints in an electronic assembly under temperature cycling condition. The viscoplastic strain energy density accumulation over one temperature cycle was identified as a feasible parameter for evaluating the thermomechanical reliability of the solder joints. More >

Jiaxiu Dong^1,2,3, Jianhua Liu⁴, Niannian Wang^1,2,3,*, Hongyuan Fang^1,2,3, Jinping Zhang¹, Haobang Hu^1,2,3, Duo Ma^1,2,3

CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.2, pp. 541-564, 2021, DOI:10.32604/cmes.2021.015875

Abstract Nowadays, asphalt road has dominated highways around the world. Among various defects of asphalt road, cracks have been paid more attention, since cracks often cause major engineering and personnel safety incidents. Current manual crack inspection methods are time-consuming and labor-intensive, and most segmentation methods cannot detect cracks at the pixel level. This paper proposes an intelligent segmentation and measurement model based on the modified Mask R-CNN algorithm to automatically and accurately detect asphalt road cracks. The model proposed in this paper mainly includes a convolutional neural network (CNN), an optimized region proposal network (RPN), a region of interest (RoI) Align… More >

Haiquan Li¹, Qinghui Zhang^2,*, Xiaoqian Chen³

CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.2, pp. 605-621, 2021, DOI:10.32604/cmes.2021.015747

Abstract Flight load computations (FLC) are generally expensive and time-consuming. This paper studies deep learning (DL)-based surrogate models of FLC to provide a reliable basis for the strength design of aircraft structures. We mainly analyze the influence of Mach number, overload, angle of attack, elevator deflection, altitude, and other factors on the loads of key monitoring components, based on which input and output variables are set. The data used to train and validate the DL surrogate models are derived using aircraft flight load simulation results based on wind tunnel test data. According to the FLC features, a deep neural network (DNN)… More >

Wanxia Yang^*, Miaoqi Li, Beibei Zhou, Yan Liu, Kenan Liu, Zhiyu Hu

CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.2, pp. 623-637, 2021, DOI:10.32604/cmes.2021.015629

Abstract To address the difficulty of detecting low embedding rate and high-concealment CNV-QIM (complementary neighbor vertices-quantization index modulation) steganography in low bit-rate speech codec, the code-word correlation model based on a BiLSTM (bi-directional long short-term memory) neural network is built to obtain the correlation features of the LPC codewords in speech codec in this paper. Then, softmax is used to classify and effectively detect low embedding rate CNV-QIM steganography in VoIP streams. The experimental results show that for speech steganography of short samples with low embedding rate, the BiLSTM method in this paper has a superior detection accuracy than state-of-the-art methods… More >

Karpagam Sundararajan¹, Lalit Garg^2,*, Kathiravan Srinivasan^4,*, Ali Kashif Bashir³, Jayakumar Kaliappan⁴, Ganapathy Pattukandan Ganapathy⁵, Senthil Kumaran Selvaraj⁶, T. Meena⁷

CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.2, pp. 447-487, 2021, DOI:10.32604/cmes.2021.015528

Abstract Drought is the least understood natural disaster due to the complex relationship of multiple contributory factors. Its beginning and end are hard to gauge, and they can last for months or even for years. India has faced many droughts in the last few decades. Predicting future droughts is vital for framing drought management plans to sustain natural resources. The data-driven modelling for forecasting the metrological time series prediction is becoming more powerful and flexible with computational intelligence techniques. Machine learning (ML) techniques have demonstrated success in the drought prediction process and are becoming popular to predict the weather, especially the… More >

Buyu Jia, Siyi Mao, Quansheng Yan, Xiaolin Yu^*

CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.2, pp. 565-582, 2021, DOI:10.32604/cmes.2021.015183

Abstract Research on the lateral vibrational stability of footbridges has attracted increasing attention in recent years. However, this stability contains a series of complex mechanisms, such as nonlinear vibration, random excitation, and random stability. The Lyapunov method is regarded as an effective tool for analyzing random vibrational stability; however, it is a qualitative method and can only provide a binary judgment for stability. This study proposes a new method, IEVIE–SA, which combines the energy method based on the comparison between the input energy and the variation of intrinsic energy (IEVIE) and the stochastic averaging (SA) method. The improved Nakamura model was… More >

Jian Yang, Lang Xin^#, Haihui Huang^*,#, Qiang He

CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.2, pp. 779-802, 2021, DOI:10.32604/cmes.2021.014993

Abstract Object detection plays an important role in the sorting process of mechanical fasteners. Although object detection has been studied for many years, it has always been an industrial problem. Edge-based model matching is only suitable for a small range of illumination changes, and the matching accuracy is low. The optical flow method and the difference method are sensitive to noise and light, and camshift tracking is less effective in complex backgrounds. In this paper, an improved target detection method based on YOLOv3-tiny is proposed. The redundant regression box generated by the prediction network is filtered by soft nonmaximum suppression (NMS)… More >

Fuzhang Wang^1,2, Enran Hou^2,*, Imtiaz Ahmad³, Hijaz Ahmad⁴, Yan Gu⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.2, pp. 687-698, 2021, DOI:10.32604/cmes.2021.014739

Abstract Numerical solutions of the second-order one-dimensional hyperbolic telegraph equations are presented using the radial basis functions. The purpose of this paper is to propose a simple novel direct meshless scheme for solving hyperbolic telegraph equations. This is fulfilled by considering time variable as normal space variable. Under this scheme, there is no need to remove time-dependent variable during the whole solution process. Since the numerical solution accuracy depends on the condition of coefficient matrix derived from the radial basis function method. We propose a simple shifted domain method, which can avoid the full-coefficient interpolation matrix easily. Numerical experiments performed with… More >

Luciano Pereira da Silva^1,*, Bruno Benato Rutyna¹, Aline Roberta Santos Righi², Marcio Augusto Villela Pinto³

CMES-Computer Modeling in Engineering & Sciences, Vol.128, No.2, pp. 699-715, 2021, DOI:10.32604/cmes.2021.014239

Abstract In this article, we improve the order of precision of the two-dimensional Poisson equation by combining extrapolation techniques with high order schemes. The high order solutions obtained traditionally generate non-sparse matrices and the calculation time is very high. We can obtain sparse matrices by applying compact schemes. In this article, we compare compact and exponential finite difference schemes of fourth order. The numerical solutions are calculated in quadruple precision (Real * 16 or extended precision) in FORTRAN language, and iteratively obtained until reaching the round-off error magnitude around 1.0E −32. This procedure is performed to ensure that there is no… More >