Ying Wang^1,*, Longxiao Chao¹, Jun Chen², Songbai Jiang¹

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 201-227, 2024, DOI:10.32604/cmes.2024.046129

Abstract In order to investigate the fatigue performance of orthotropic anisotropic steel bridge decks, this study realizes the simulation of the welding process through elastic-plastic finite element theory, thermal-structural sequential coupling, and the birth-death element method. The simulated welding residual stresses are introduced into the multiscale finite element model of the bridge as the initial stress. Furthermore, the study explores the impact of residual stress on crack propagation in the fatigue-vulnerable components of the corroded steel box girder. The results indicate that fatigue cracks at the weld toe of the top deck, the weld root of the top deck, and the… More > Graphic Abstract

Hongzhang Wang¹, Jing Guo¹, Shanjun Yang¹, Chaoheng Cheng², Jing Chen^3,*, Zhihao Chen³

Structural Durability & Health Monitoring, Vol.18, No.2, pp. 181-196, 2024, DOI:10.32604/sdhm.2024.044628

Abstract Pitting corrosion is harmful during bridge construction, which will lead to uneven roughness of steel surfaces and reduce the thickness of steel. Hence, the effect of pitting corrosion on the mechanical properties of cold-formed thin-walled steel stub columns is studied, and the empirical formulas are established through regression fitting to predict the ultimate load of web and flange under pitting corrosion. In detail, the failure modes and load-displacement curves of specimens with different locations, area ratios, and depths are obtained through a large number of non-linear finite element analysis. As for the specimens with pitting corrosion on the web, all… More > Graphic Abstract

Yan Wang^*, Siwen Li, Na Wei

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3467-3493, 2024, DOI:10.32604/cmes.2024.046454

Abstract A novel approach for analyzing coupled vibrations between vehicles and bridges is presented, taking into account spatiotemporal effects and mechanical phenomena resulting from vehicle braking. Efficient modeling and solution of bridge vibrations induced by vehicle deceleration are realized using this method. The method’s validity and reliability are substantiated through numerical examples. A simply supported beam bridge with a corrugated steel web is taken as an example and the effects of parameters such as the initial vehicle speed, braking acceleration, braking location, and road surface roughness on the mid-span displacement and impact factor of the bridge are analyzed. The results show… More >

Wangchen Yan^1,*, Jinbao Yang¹, Xin Luo²

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2507-2524, 2024, DOI:10.32604/cmes.2023.044709

Abstract Transfer learning could reduce the time and resources required by the training of new models and be therefore important for generalized applications of the trained machine learning algorithms. In this study, a transfer learning-enhanced convolutional neural network (CNN) was proposed to identify the gross weight and the axle weight of moving vehicles on the bridge. The proposed transfer learning-enhanced CNN model was expected to weigh different bridges based on a small amount of training datasets and provide high identification accuracy. First of all, a CNN algorithm for bridge weigh-in-motion (B-WIM) technology was proposed to identify the axle weight and the… More >

Shude Fu^1,2, Xinye Wu^1,2,*, Wenjie Wang³, Yixin Hu^1,3,*, Zhengke Li¹, Feng Jiang³

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2357-2382, 2024, DOI:10.32604/cmes.2023.031118

Abstract In this paper, given the shortcomings of jellyfish search algorithm with low search ability in the early stage and easy to fall into local optimal solution, this paper introduces adaptive weight function and elite strategy, improving the global search scope in the early stage and the ability to refine the local development in the later stage. In the numerical study, the benchmark problem of dimensional optimization with a 10-bar truss structure and simultaneous dimensional shape optimization with a 15-bar truss structure is adopted, and the corresponding penalty method is used for constraint treatment. The test results show that the improved… More > Graphic Abstract

Fabrizio Greco^*, Paolo Lonetti, Arturo Pascuzzo, Giulia Sansone

Structural Durability & Health Monitoring, Vol.17, No.6, pp. 457-483, 2023, DOI:10.32604/sdhm.2023.030075

Abstract This work proposes a numerical investigation on the effects of damage on the structural response of Reinforced Concrete (RC) bridge structures commonly adopted in highway and railway networks. An effective three-dimensional FE-based numerical model is developed to analyze the bridge’s structural response under several damage scenarios, including the effects of moving vehicle loads. In particular, the longitudinal and transversal beams are modeled through solid finite elements, while horizontal slabs are made of shell elements. Damage phenomena are also incorporated in the numerical model according to a smeared approach consistent with Continuum Damage Mechanics (CDM). In such a context, the proposed… More >

Zhuyou Hu¹, Ping Lin^2,3, He Guo^2,3, Yumei Zhang^2,3, Zhihai Xiang^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.27, No.1, pp. 1-2, 2023, DOI:10.32604/icces.2023.09475

Abstract In recent years, the vehicle scanning method for bridge inspection has drawn much attention by researchers because of its simple operation and high efficiency [1]. Besides the natural frequency, modal modes and other information of bridges, damage can also be detected in this way [2]. For example, we proposed the passive tap-scan damage detection method [3], which scans the bridge with the tapping force generated by a toothed wheel, mimicking the hunting behavior of woodpeckers. In this talk, we will discuss two critical aspects related to the mechanism of this method. One is the quantitative relationship between the vehicle acceleration… More >

Zhuyou Hu¹, Ping Lin^2,3, He Guo^2,3, Yumei Zhang^2,3, Zhihai Xiang^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.26, No.1, pp. 1-2, 2023, DOI:10.32604/icces.2023.09475

Abstract In recent years, the vehicle scanning method for bridge inspection has drawn much attention by researchers because of its simple operation and high efficiency [1]. Besides the natural frequency, modal modes and other information of bridges, damage can also be detected in this way [2]. For example, we proposed the passive tap-scan damage detection method [3], which scans the bridge with the tapping force generated by a toothed wheel, mimicking the hunting behavior of woodpeckers. In this talk, we will discuss two critical aspects related to the mechanism of this method. One is the quantitative relationship between the vehicle acceleration… More >

Ahmed Silik^1,2,7, Xiaodong Wang³, Chenyue Mei³, Xiaolei Jin³, Xudong Zhou⁴, Wei Zhou⁴, Congning Chen⁴, Weixing Hong^1,2, Jiawei Li^1,2, Mingjie Mao^1,2, Yuhan Liu^1,2, Mohammad Noori^5,6,*, Wael A. Altabey^8,*

Structural Durability & Health Monitoring, Vol.17, No.4, pp. 257-281, 2023, DOI:10.32604/sdhm.2023.023617

Abstract Damage detection is an important area with growing interest in mechanical and structural engineering. One of the critical issues in damage detection is how to determine indices sensitive to the structural damage and insensitive to the surrounding environmental variations. Current damage identification indices commonly focus on structural dynamic characteristics such as natural frequencies, mode shapes, and frequency responses. This study aimed at developing a technique based on energy Curvature Difference, power spectrum density, correlation-based index, load distribution factor, and neutral axis shift to assess the bridge deck condition. In addition to tracking energy and frequency over time using wavelet packet… More > Graphic Abstract

Zhen Zhen¹, Jian Gao^1,2,*

Computer Systems Science and Engineering, Vol.47, No.1, pp. 955-973, 2023, DOI:10.32604/csse.2023.039525

Abstract Telecommunication fraud has run rampant recently worldwide. However, previous studies depend highly on expert knowledge-based feature engineering to extract behavior information, which cannot adapt to the fast-changing modes of fraudulent subscribers. Therefore, we propose a new taxonomy that needs no hand-designed features but directly takes raw Call Detail Records (CDR) data as input for the classifier. Concretely, we proposed a fraud detection method using a convolutional neural network (CNN) by taking CDR data as images and applying computer vision techniques like image augmentation. Comprehensive experiments on the real-world dataset from the 2020 Digital Sichuan Innovation Competition show that our proposed… More >