scholarly journals Multiscale Simulation of Surface Defect Influence in Nanoindentation by a Quasi-Continuum Method

2019 ◽  
Author(s):  
Zhongli Zhang ◽  
Yushan Ni ◽  
Jinming Zhang ◽  
Can Wang ◽  
Xuedi Ren
Keyword(s):  
Surface Defect ◽  
Multiscale Simulation

scholarly journals Multiscale Simulation of Surface Defects Influence Nanoindentation by a Quasi-Continuum Method

Crystals ◽  
2018 ◽  
Vol 8 (7) ◽  
pp. 291 ◽  
Author(s):  
Zhongli Zhang ◽  
Yushan Ni ◽  
Jinming Zhang ◽  
Can Wang ◽  
Kun Jiang ◽  
...  
Keyword(s):  
Surface Defect ◽  
Surface Defects ◽  
Wave Pattern ◽  
Multiscale Simulation ◽  
Theoretical Formula ◽  
Initial Surface ◽  
Face Centered Cubic ◽  
Quasicontinuum Method ◽  
Atomic Spacing ◽  
Face Centered

Microscopic properties of nanocrystal aluminum thin film have been investigated using the quasicontinuum method in order to study the influence of surface defects in nanoindentation. Various distances between the surface defect and indenter have been taken into account. The results show that as the distance between the pit and indenter increases, the nanohardness increases in a wave pattern associated with a cycle of three atoms, which is closely related to the crystal structure of periodic atoms arrangement on {1 1 1} atomic close-packed planes of face-centered cubic metal; when the adjacent distance between the pit and indenter is more than 16 atomic spacing, there is almost no effect on nanohardness. In addition, the theoretical formula for the necessary load for elastic-to-plastic transition of Al film has been modified with the initial surface defect size, which may contribute to the investigation of material property with surface defects.

scholarly journals Multiscale Simulation of Surface Defect Influence in Nanoindentation by the Quasi-Continuum Method

Proceedings ◽  
2018 ◽  
Vol 2 (14) ◽  
pp. 1113
Author(s):  
Zhongli Zhang ◽  
Jinming Zhang ◽  
Yushan Ni ◽  
Can Wang ◽  
Kun Jiang ◽  
...  
Keyword(s):  
Surface Defect ◽  
Surface Defects ◽  
Wave Pattern ◽  
Multiscale Simulation ◽  
Theoretical Formula ◽  
Initial Surface ◽  
Face Centered Cubic ◽  
Quasicontinuum Method ◽  
Atomic Spacing ◽  
Face Centered

Microscopic properties of nanocrystal Aluminum thin film have been simulated using the quasicontinuum method in order to study the surface defect influence in nanoindentation. Various distances between the surface defect and indenter have been taken into account. The results show that as the distance between the pit and indenter increases, the nanohardness increases in a wave pattern associated with a cycle of three atoms, which is closely related to the crystal structure of periodic atoms arrangement on {111} atomic close-packed planes of face-centered cubic metal; when the adjacent distance between the pit and indenter is more than 16 atomic spacing, there is almost no effect on nanohardness. In addition, the theoretical formula for the necessary load for the elastic-to-plastic transition of Al film has been modified with the initial surface defect size, which may contribute to the investigation of material properties with surface defects.

scholarly journals Downscaled Finite Element Modeling of Metal Targets for Surface Roughness Level under Pulsed Laser Irradiation

2021 ◽  
Vol 11 (3) ◽  
pp. 1253
Author(s):  
Evaggelos Kaselouris ◽  
Kyriaki Kosma ◽  
Yannis Orphanos ◽  
Alexandros Skoulakis ◽  
Ioannis Fitilis ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Finite Element ◽  
Surface Acoustic Waves ◽  
Pulsed Laser ◽  
Multiscale Simulation ◽  
Experimental Methodology ◽  
Computational Domain ◽  
Area Of Interest ◽  
Depth Analysis ◽  
Laser Solid Interactions

A three-dimensional, thermal-structural finite element model, originally developed for the study of laser–solid interactions and the generation and propagation of surface acoustic waves in the macroscopic level, was downscaled for the investigation of the surface roughness influence on pulsed laser–solid interactions. The dimensions of the computational domain were reduced to include the laser-heated area of interest. The initially flat surface was progressively downscaled to model the spatial roughness profile characteristics with increasing geometrical accuracy. Since we focused on the plastic and melting regimes, where structural changes occur in the submicrometer scale, the proposed downscaling approach allowed for their accurate positioning. Additionally, the multiscale simulation results were discussed in relation to experimental findings based on white light interferometry. The combination of this multiscale modeling approach with the experimental methodology presented in this study provides a multilevel scientific tool for an in-depth analysis of the influence of heat parameters on the surface roughness of solid materials and can be further extended to various laser–solid interaction applications.

scholarly journals X-SDD: A New Benchmark for Hot Rolled Steel Strip Surface Defects Detection

Symmetry ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 706
Author(s):  
Xinglong Feng ◽  
Xianwen Gao ◽  
Ling Luo
Keyword(s):  
Surface Defect ◽  
Surface Defects ◽  
Steel Strip ◽  
Rolled Strip ◽  
Rolled Steel ◽  
Strip Surface ◽  
Hot Rolled Strip ◽  
Hot Rolled ◽  
Hot Rolled Steel ◽  
Detection Of Defects

It is important to accurately classify the defects in hot rolled steel strip since the detection of defects in hot rolled steel strip is closely related to the quality of the final product. The lack of actual hot-rolled strip defect data sets currently limits further research on the classification of hot-rolled strip defects to some extent. In real production, the convolutional neural network (CNN)-based algorithm has some difficulties, for example, the algorithm is not particularly accurate in classifying some uncommon defects. Therefore, further research is needed on how to apply deep learning to the actual detection of defects on the surface of hot rolled steel strip. In this paper, we proposed a hot rolled steel strip defect dataset called Xsteel surface defect dataset (X-SDD) which contains seven typical types of hot rolled strip defects with a total of 1360 defect images. Compared with the six defect types of the commonly used NEU surface defect database (NEU-CLS), our proposed X-SDD contains more types. Then, we adopt the newly proposed RepVGG algorithm and combine it with the spatial attention (SA) mechanism to verify the effect on the X-SDD. Finally, we apply multiple algorithms to test on our proposed X-SDD to provide the corresponding benchmarks. The test results show that our algorithm achieves an accuracy of 95.10% on the testset, which exceeds other comparable algorithms by a large margin. Meanwhile, our algorithm achieves the best results in Macro-Precision, Macro-Recall and Macro-F1-score metrics.

SDDNet: A Fast and Accurate Network for Surface Defect Detection

2021 ◽  
Vol 70 ◽  
pp. 1-13
Author(s):  
Lisha Cui ◽  
Xiaoheng Jiang ◽  
Mingliang Xu ◽  
Wanqing Li ◽  
Pei Lv ◽  
...  
Keyword(s):  
Defect Detection ◽  
Surface Defect ◽  
Surface Defect Detection
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