报告题目：Characterization of Elastomer Materials using Instrumented Indentation Test and the Shape-Manifold Approach
报告时间：2023年10月23日 星期一 10:30-12:00
报告摘要：The Instrumented Indentation Test (IIT) has emerged as a practical, efficient and non-destructive method for assessing the mechanical response of a wide range of materials, making it a valuable tool in materials science and engineering. This versatile technique can be used to optimize the parameters of industrial processes. It is particularly suitable for manufacturing applications involving components with gradient properties, such as welded joints and 3D printed parts, as well as those undergoing surface treatments like coating, shot peening, and heat treatment. IIT utility extends to examining small-scale devices, including nanometer-sized specimens. In recent scientific research, there has been a notable increase in the adoption of instrumented indentation technique to comprehensively assess the mechanical properties of elastomeric and hyperplastic biological materials. These materials exhibit unique mechanical behaviors, characterized by their capacity for substantial nonlinear elastic deformations, often accompanied by viscosity effects. The present work focuses on extracting the parameters of the material behavior law from experimental instrumented indentation curve specifically for elastomer materials. To accurately address this inverse problem, the shape-manifold machine learning approach is employed. We generate a reduced-order model through interpolation from a design of experiments of finite element simulations. While our approach has been successfully validated using synthetic data, challenges arise when determining material properties from actual experimental measurements. These challenges include quantifying the friction coefficient between the indenter tip and the specimen surface, which is required for simulations, as well as addressing contact detection complexities, particularly on soft materials. The roughness of rubber surfaces, compared to harder materials like metals or ceramics, presents an additional challenge due to limited polishing capabilities. Moreover, tip adhesion effects may be prominent in these materials.In response to these challenges, our study introduces and tests various numerical and experimental solutions, yielding promising results. Ongoing work is dedicated to further enhancing the efficiency of this innovative approach.
经费资助信息：2023.1-2026.12，国家自然科学基金面上项目‘大规模结构动力学拓扑优化的动态多保真缩减理论与方法’，（Grant No. 12272302）