Shaoqi Zheng¹, Zihao Yang^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.29, No.1, pp. 1-1, 2024, DOI:10.32604/icces.2024.012200

Abstract This study proposes a novel method for predicting the microcrack propagation in composites based on coupling the local and non-local micromechanics. The special feature of this method is that it can take full advantages of both the continuum micromechanics as a local model and peridynamic micromechanics as a non-local model to achieve composite fracture simulation with a higher level of accuracy and efficiency. Based on the energy equivalence, we first establish the equivalent continuum micromechanics model with equivalent stiffness operators through peridynamic micromechanics model. These two models are then coupled into a closed equation system, More >

Yangjian Si^1,2, Yujie Wei^1,2,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.29, No.1, pp. 1-1, 2024, DOI:10.32604/icces.2024.011974

Abstract Edge cracking represents one of the most prominent damage modes in engineering practice and hence receives immense attention from academic societies. When branched cracks or multiple cracks are present at the edge, their propagation may be affected by the interaction between the cracks. In this talk, we may cover the elasticity of a cracked half-plane with two typical scenarios: a double branched crack with two rays emanating from one point on the edge and two edge cracks spaced by a certain distance (Kalthoff–Winkler cracks). By adopting the combination of the Schwartz-Christoffel conformal mapping and the… More >

Qiuyi Wang¹, Rong Yang¹, Bo Chen², Rui Bao^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.29, No.1, pp. 1-1, 2024, DOI:10.32604/icces.2024.011878

Abstract Effects of hold time on the fatigue crack growth behavior in electron-beam powder-bed-fusion (PBF-EB) Inconel 718 alloy at 650 ∘C have been investigated in this study, with focuses on the anisotropic fatigue cracking resistance and fracture mechanism. The V-type specimen (which loading parallel to the columnar grain boundaries) gives better dwell-fatigue cracking resistance to the H-type specimen (which loading perpendicular to the columnar grain boundaries) due to its large deflections (nearly 90 °) on the crack path. These deflections are related to the change of crack growth mechanism. In both V-type and H-type specimens, when More >

Binchao Liu^1,2,*, Qiuyi Wang², Rui Bao²

The International Conference on Computational & Experimental Engineering and Sciences, Vol.29, No.1, pp. 1-1, 2024, DOI:10.32604/icces.2024.011835

Abstract With the everlasting pursuit for weight reduction, efforts are devoted to applying additively manufactured (AM) structures in aeronautic vehicles; however, anomalous fatigue crack growth (FCG) behaviors, such as deflection and branching, are recently observed in macroscale, which deviates from the predictions by classic fracture mechanics. In this work, FCG behaviors of direct energy deposited (DED) Ti–5Al–5Mo–5V–1Cr–1Fe (TC18 in China) are investigated, in which fatigue crack deflections induced by combined impacts of loading and microstructures are revealed. Experiment results show that cracks are more deflected in columnar grains due to the preferred distribution of acicular a… More >

Redžo Hasanagić^1,*, Umejr Šljivo¹, Leila Fathi², Pallavi Gautam³, Mohsen Bahmani^2,*, Miha Humar⁴

Journal of Renewable Materials, Vol.12, No.8, pp. 1417-1431, 2024, DOI:10.32604/jrm.2024.052826 - 06 September 2024

Abstract This study investigated the mechanical properties of beech (Fagus sylvatica L.) and fir (Abies alba) wood from Bosnia and Herzegovina under outdoor exposure. Samples were exposed for 3-month exposure to assess bending strength, color changes, and surface quality. Results showed outdoor exposure negatively affected mechanical properties, particularly in samples with extended finger joints, causing significant surface cracks in uncoated samples. Beech wood exhibited notable color changes under exposure, with approximately 50% darkening without coating compared to 25% under covered conditions. Coated samples displayed minimal color changes, affirming the efficacy of surface treatment. Fir wood exhibited a roughness More > Graphic Abstract

Yong Wan¹, Li Li¹, Jiaxin Zou¹, Hucheng Xiao², Mengdi Zhu², Ying Su², Jin Yang^2,*

FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.9, pp. 1941-1956, 2024, DOI:10.32604/fdmp.2024.053910 - 23 August 2024

Abstract Due to the low water-cement ratio of ultra-high-performance concrete (UHPC), fluidity and shrinkage cracking are key aspects determining the performance and durability of this type of concrete. In this study, the effects of different types of cementitious materials, chemical shrinkage-reducing agents (SRA) and steel fiber (SF) were assessed. Compared with M2-UHPC and M3-UHPC, M1-UHPC was found to have better fluidity and shrinkage cracking performance. Moreover, different SRA incorporation methods, dosage and different SF types and aspect ratios were implemented. The incorporation of SRA and SF led to a decrease in the fluidity of UHPC. SRA More >

Rui Wang¹, Zhihui Liu^2,*, Hongdi Liu³, Baozhong Su⁴, Chuanyi Ma⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 3035-3049, 2024, DOI:10.32604/cmes.2024.050806 - 08 July 2024

Abstract In underground engineering, the detection of structural cracks on tunnel surfaces stands as a pivotal task in ensuring the health and reliability of tunnel structures. However, the dim and dusty environment inherent to underground engineering poses considerable challenges to crack segmentation. This paper proposes a crack segmentation algorithm termed as Focused Detection for Subsurface Cracks YOLOv8 (FDSC-YOLOv8) specifically designed for underground engineering structural surfaces. Firstly, to improve the extraction of multi-layer convolutional features, the fixed convolutional module is replaced with a deformable convolutional module. Secondly, the model’s receptive field is enhanced by introducing a multi-branch More >

Haoan Gu¹, Kai Zhu¹, Alfred Strauss², Yehui Shi^3,4, Dragoslav Sumarac⁵, Maosen Cao^1,*

Structural Durability & Health Monitoring, Vol.18, No.4, pp. 363-380, 2024, DOI:10.32604/sdhm.2024.042388 - 05 June 2024

Abstract Concrete materials and structures are extensively used in transformation infrastructure and they usually bear cracks during their long-term operation. Detecting cracks using deep-learning algorithms like YOLOv3 (You Only Look Once version 3) is a new trend to pursue intelligent detection of concrete surface cracks. YOLOv3 is a typical deep-learning algorithm used for object detection. Owing to its generality, YOLOv3 lacks specific efficiency and accuracy in identifying concrete surface cracks. An improved algorithm based on YOLOv3, specialized in the rapid and accurate identification of concrete surface cracks is worthy of investigation. This study proposes a tailored… More >

Yang Li, Sibo Jiang^*, Ruixin Lan

Structural Durability & Health Monitoring, Vol.18, No.3, pp. 255-276, 2024, DOI:10.32604/sdhm.2024.047776 - 15 May 2024

Abstract Chloride (Cl) ion erosion effects can seriously impact the safety and service life of marine liquefied natural gas (LNG) storage tanks and other polar offshore structures. This study investigates the impact of different low-temperature cycles (20°C, –80°C, and −160°C) and concrete specimen crack widths (0, 0.3, and 0.6 mm) on the Cl ion diffusion performance through rapid erosion tests conducted on pre-cracked concrete. The results show that the minimum temperature and crack width of freeze-thaw cycles enhance the erosive effect of chloride ions. The Cl ion concentration and growth rate increased with the increasing crack More > Graphic Abstract

Dingping Chen¹, Zhiheng Zhu², Jinyang Fu^1,3, Jilin He^1,*

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1679-1703, 2024, DOI:10.32604/cmc.2024.049048 - 25 April 2024

Abstract The detection of crack defects on the walls of road tunnels is a crucial step in the process of ensuring travel safety and performing routine tunnel maintenance. The automatic and accurate detection of cracks on the surface of road tunnels is the key to improving the maintenance efficiency of road tunnels. Machine vision technology combined with a deep neural network model is an effective means to realize the localization and identification of crack defects on the surface of road tunnels. We propose a complete set of automatic inspection methods for identifying cracks on the walls… More >