Yalong Yang^1,2,3, Wenjing Xu^1,2,3, Yinfeng Zhu⁴, Liangliang Su^1,2,3,*, Gongquan Zhang^1,2,3

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 761-773, 2023, DOI:10.32604/cmes.2023.027010

Abstract As a current popular method, intelligent detection of cracks is of great significance to road safety, so deep learning has gradually attracted attention in the field of crack image detection. The nonlinear structure, low contrast and discontinuity of cracks bring great challenges to existing crack detection methods based on deep learning. Therefore, an end-to-end deep convolutional neural network (AttentionCrack) is proposed for automatic crack detection to overcome the inaccuracy of boundary location between crack and non-crack pixels. The AttentionCrack network is built on U-Net based encoder-decoder architecture, and an attention mechanism is incorporated into the multi-scale convolutional feature to enhance… More >

Bingrui Ju¹, Wenzhen Qu^1,2,*, Yan Gu^1,2

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2677-2690, 2023, DOI:10.32604/cmes.2023.025886

Abstract This paper develops a new numerical framework for mode III crack problems of thin-walled structures by integrating multiple advanced techniques in the boundary element literature. The details of special crack-tip elements for displacement and stress are derived. An exponential transformation technique is introduced to accurately calculate the nearly singular integral, which is the key task of the boundary element simulation of thin-walled structures. Three numerical experiments with different types of cracks are provided to verify the performance of the present numerical framework. Numerical results demonstrate that the present scheme is valid for mode III crack problems of thin-walled structures with… More >

Peng Geng^*, Ji Lu, Hongtao Ma, Guiyi Yang

Structural Durability & Health Monitoring, Vol.17, No.1, pp. 1-22, 2023, DOI:10.32604/sdhm.2023.018632

Abstract Accurate and reliable crack segmentation is a challenge and meaningful task. In this article, aiming at the characteristics of cracks on the concrete images, the intensity frequency information of source images which is obtained by Discrete Wavelet Transform (DWT) is fed into deep learning-based networks to enhance the ability of network on crack segmentation. To well integrate frequency information into network an effective and novel DWTA module based on the DWT and scSE attention mechanism is proposed. The semantic information of cracks is enhanced and the irrelevant information is suppressed by DWTA module. And the gap between frequency information and… More >

Hong-Hu Chu¹, Muhammad Rizwan Saeed², Javed Rashid^3,4,*, Muhammad Tahir Mehmood⁵, Israr Ahmad⁶, Rao Sohail Iqbal⁴, Ghulam Ali¹

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1863-1881, 2023, DOI:10.32604/cmc.2023.035287

Abstract The increasing global population at a rapid pace makes road traffic dense; managing such massive traffic is challenging. In developing countries like Pakistan, road traffic accidents (RTA) have the highest mortality percentage among other Asian countries. The main reasons for RTAs are road cracks and potholes. Understanding the need for an automated system for the detection of cracks and potholes, this study proposes a decision support system (DSS) for an autonomous road information system for smart city development with the use of deep learning. The proposed DSS works in layers where initially the image of roads is captured and coordinates… More >

M. J. Anitha^1,*, R. Hemalatha²

Computer Systems Science and Engineering, Vol.46, No.1, pp. 1183-1200, 2023, DOI:10.32604/csse.2023.031888

Abstract Detection of cracks at the early stage is considered as very constructive since precautionary steps need to be taken to avoid the damage to the civil structures. Moreover, identifying and classifying the severity level of cracks is inevitable in order to find the stability of buildings. Hence, this paper proposes an efficient strategy to classify the cracks into fine, medium, and thick using a novel bilayer crack detection algorithm. The bilayer crack detection algorithm helps in extracting the requisite features from the crack for efficient classification. The proposed algorithm works well in the dark background and connects the discontinued cracks… More >

Jianwei Yuan¹, Xinli Song^1,*, Huaijian Pu², Zhixiong Zheng³, Ziyang Niu³

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6485-6503, 2023, DOI:10.32604/cmc.2023.035165

Abstract Regular inspection of bridge cracks is crucial to bridge maintenance and repair. The traditional manual crack detection methods are time-consuming, dangerous and subjective. At the same time, for the existing mainstream vision-based automatic crack detection algorithms, it is challenging to detect fine cracks and balance the detection accuracy and speed. Therefore, this paper proposes a new bridge crack segmentation method based on parallel attention mechanism and multi-scale features fusion on top of the DeeplabV3+ network framework. First, the improved lightweight MobileNet-v2 network and dilated separable convolution are integrated into the original DeeplabV3+ network to improve the original backbone network Xception… More >

Zhihui Xiong, Xiaohui Zhou^*, Jinjie Zhao, Hao Cui, Bo Wang

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.3, pp. 2449-2478, 2023, DOI:10.32604/cmes.2023.023353

Abstract The numerical simulation results utilizing the Peridynamics (PD) method reveal that the initial crack and crack propagation of the tunnel concrete lining structure agree with the experimental data compared to the Japanese prototype lining test. The load structure model takes into account the cracking process and distribution of the lining segment under the influence of local bias pressure and lining thickness. In addition, the influence of preset cracks and lining section form on the crack propagation of the concrete lining model is studied. This study evaluates the stability and sustainability of tunnel structure by the Peridynamics method, which provides a… More >

Jing Xu^1,2,*, Yuquan Yao³, Kai Zhang¹, Jiangang Yang², Jie Gao², Jian Zhou²

Journal of Renewable Materials, Vol.11, No.3, pp. 1339-1351, 2023, DOI:10.32604/jrm.2022.023270

Abstract This study focuses on the effect of oils on rheology and oxidation aging of Styrene-Butadiene-Styrene modified asphalt (SBSMA) in the long term, after reducing one low-temperature Performance Grade (PG) of SBSMA by incorporating oils. Two oils, including corn-based bio-oil and re-refined engine oil bottom (REOB), were selected to enhance the low-temperature performance of SBSMA. All samples were subjected to Rolling Thin Film Oven (RTFO) aging and 20-h as well as 40-h Pressure Aging Vessel (PAV20 and PAV40) aging, prior to multiple stress creep recovery (MSCR), frequency sweep and Flourier transform infrared spectroscopy (FTIR) scanning. A good high-temperature performance of oil/SBS… More >

Huazhe Jiao^1,2,3, Wenxiang Zhang^1,2,3,*, Yunfei Wang^1,2,3,*, Xinming Chen^1,2,3, Liuhua Yang^1,2,3, Yangyang Rong^1,2,3

Journal of Renewable Materials, Vol.11, No.3, pp. 1513-1529, 2023, DOI:10.32604/jrm.2023.026008

Abstract The green disposal of tailings solid waste is a problem to be solved in mine production. Cemented tailings filling stoping method can realize the dual goals of solid waste resource utilization and mined-out area reduction. However, the volume of the mined-out area of the open-pit method is larger than the filling capacity, resulting in the complex stratification of the underground backfill, and the strength of the backfill cannot meet the requirements. In this paper, according to the delamination situation, the specimens of horizontal and inclination angle layered cemented tailings backfill (LCTB) is made for a uniaxial compression test, and the… More >

Tong An^1,2,*, Rui Zhou^1,2, Fei Qin^1,2,*, Pei Chen^1,2, Yanwei Dai^1,2, Yanpeng Gong^1,2

CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.2, pp. 1481-1502, 2023, DOI:10.32604/cmes.2023.022475

Abstract A micromechanical model is presented to study the initiation and propagation of microcracks of intermetallic compounds (IMCs) in solder joints. The effects of the grain aggregate morphology, the grain boundary defects and the sensitivity of the various cohesive zone parameters in predicting the overall mechanical response are investigated. The overall strength is predominantly determined by the weak grain interfaces; both the grain aggregate morphology and the weak grain interfaces control the crack configuration; the different normal and tangential strengths of grain interfaces result in different intergranular cracking behaviors and play a critical role in determining the macroscopic mechanical response of… More >