# Tensile Specim Circular Grid Pattern and AI-Based Strain Calculation Method
## 1 Introduction  
### Research Background  
Historically, the invention or development of new materials has driven the advancement of industrial technologies. Particularly, metal materials have long been used in various fields and continue to be subjects of ongoing research. Recently, in the mobility sector, where efficiency is paramount, composite or metal materials with high strength and stiffness are used [1]. However, defects, such as fractures and wrinkles (cracks) in metal components, can lead not only to personal injuries but also to significant economic losses. Therefore, to establish design safety standards for metal components, it is important to understand the physical properties of the formed shapes, such as thickness, spring-back, and residual stress [2]. Finite element analysis is commonly used to understand the physical properties occurring during the forming of metal materials. When the production conditions of the metal (such as composition and heat treatment) are standardized, the reliability of numerical results regarding the metal's physical properties can be ensured through information obtained from extensive testing. However, for newly developed metals, material tests, such as tensile tests, are required to verify the reliability of numerical results by obtaining the material's physical properties [3]. The tensile testing procedure involves mounting a specimen processed to standard specifications in a tester and measuring the stress and strain generated when it is subjected to tensile stress at a constant speed. Strain measurement methods can be divided into contact methods using gauges and non-contact methods using cameras or sensors. Contact measurement methods include mechanical extensometers, electrical resistance extensometers (strain gauges), and inductive extensometers, all of which measure displacement by being directly attached to the specimen [4]. Non-contact measurement methods encompass video measurement, laser measurement, digital image correlation (DIC), and ultrasonic measurement. DIC, in particular, is noteworthy for its ability to measure 3D deformations and acquire data from multiple points, making it suitable for use in extreme temperatures and large deformation environments. Additionally, DIC can measure strain in the specimen's width and thickness directions, not just in the length direction. This method calculates strain by analyzing changes in the pattern applied to the specimen's surface and can track local strain at specific points, such as just before necking or fracture occurs [5; 6; 7]. Mechanical extensometers are attached to the specimen to provide highly reliable measurements and are less affected by environmental changes, such as ambient light or temperature. However, their measurement range can be exceeded by material elongation, and they may be difficult to attach to thin sheets [8]. Strain gauges can measure fine deformations through electrical resistance but are significantly affected by temperature changes [9]. Inductive extensometers can accurately measure fine deformations and are usable in high-temperature and extreme environments, although they are influenced by external electric fields. Contact measurement methods measure deformation based on the gauge length specified in tensile specimen standards, making it challenging to accurately analyze strain at actual fracture locations [10]. Non-contact measurement methods do not require physical contact with the specimen, preventing deformation caused by the measuring instrument in thin-sheet specimens and allowing usage under various environmental conditions, including different temperatures, pressures, and vacuum [11]. However, non-contact methods require expensive equipment, such as high-speed high-resolution cameras, lasers, ultrasonic devices, and image analysis software. They are also sensitive to optical conditions, such as lighting, reflection, and dust.