Study on the Approach to Obtaining Mechanical Properties Using Digital Image Correlation Technology

Accurate mechanical property parameters constitute an indispensable guarantee for the accuracy of finite element simulations. Traditionally, uniaxial tensile tests are instrumental in acquiring the stress-strain data of materials during elongation, thereby facilitating the determination of the materials' mechanical property parameters. By capitalizing on the digital image correlation (DIC) non-contact optical measurement technique, the entire test can be comprehensively documented using high-speed cameras. Subsequently, through in-depth analysis and meticulous numerical computations enabled by computer vision technology, the complete strain evolution of the specimen throughout the test can be precisely obtained. In this study, a comparison was made between the application of strain gauges and DIC testing systems for measuring the strain alterations during the tensile testing of 316L stainless steel, which serves as the material for the primary circuit pipelines of pressurized water reactor (PWR) nuclear power plants (NPPs). The data procured from these two methods were utilized as material mechanical parameters for finite element simulations, and a numerical simulation of the uniaxial tensile test was executed. The results reveal that, within the measuring range of the strain gauge, the DIC method generates measurement outcomes that are virtually identical to those obtained by strain gauges. Given its wider measurement range, the DIC method can be effectively adopted in the process of obtaining material mechanical parameters for finite element simulations.

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Publication Details

Journal
Materials
Published
2025-04-19
DOI
https://doi.org/10.3390/ma18081875
Citations
1
Primary Topic
Advanced Surface Polishing Techniques
Type
article
Field-Weighted Citation Impact
0.67

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article

Study on the Approach to Obtaining Mechanical Properties Using Digital Image Correlation Technology

Xiaoyan Gong, Yubiao Zhang, Shengyong Mu, Shuai Wang et al.
1 citations
Materials
Advanced Surface Polishing Techniques
0.67
article

Study on the Approach to Obtaining Mechanical Properties Using Digital Image Correlation Technology

Xiaoyan Gong, Yubiao Zhang, Shengyong Mu, Shuai Wang, Bin Wang, Jianlong Zhang
article en
1 citations

Abstract

Accurate mechanical property parameters constitute an indispensable guarantee for the accuracy of finite element simulations. Traditionally, uniaxial tensile tests are instrumental in acquiring the stress-strain data of materials during elongation, thereby facilitating the determination of the materials' mechanical property parameters. By capitalizing on the digital image correlation (DIC) non-contact optical measurement technique, the entire test can be comprehensively documented using high-speed cameras. Subsequently, through in-depth analysis and meticulous numerical computations enabled by computer vision technology, the complete strain evolution of the specimen throughout the test can be precisely obtained. In this study, a comparison was made between the application of strain gauges and DIC testing systems for measuring the strain alterations during the tensile testing of 316L stainless steel, which serves as the material for the primary circuit pipelines of pressurized water reactor (PWR) nuclear power plants (NPPs). The data procured from these two methods were utilized as material mechanical parameters for finite element simulations, and a numerical simulation of the uniaxial tensile test was executed. The results reveal that, within the measuring range of the strain gauge, the DIC method generates measurement outcomes that are virtually identical to those obtained by strain gauges. Given its wider measurement range, the DIC method can be effectively adopted in the process of obtaining material mechanical parameters for finite element simulations.

MaterialsVol. 18(8)
Xi'an University of Science and Technology (CN), University of London (GB), Xi'an Shiyou University (CN), Anhui Special Equipment Inspection Institute (CN), Brunel University of London (GB)
National Natural Science Foundation of China, Natural Science Foundation of Shaanxi Province
Openalex Percentile: Top 33%
Advanced Surface Polishing Techniques
0.67
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