Suppr超能文献

Low-energy dynamic indentation method for analysis of ophthalmic materials.

作者信息

Artús Pau, Dürsteler Juan C, Martínez Antonio B

机构信息

Industrias de Optica S.A., Sant Cugat del Vallès, Spain.

出版信息

Optom Vis Sci. 2008 Jan;85(1):49-53. doi: 10.1097/OPX.0b013e31815ed713.

Abstract

PURPOSE

The purpose of the present work is to understand and study the mechanical behavior and critical parameters of ophthalmic polymers. The article introduces a novel low-energy indentation method that can be used to study and optimize the mechanical properties of ophthalmic materials. The technique has been developed in the frame of a larger study on the impact resistance of materials.

METHOD

The low-energy dynamic indentation method is based on a lumped mass-spring model solved by a 4th-order Runge-Kutta numerical method. The model can be used to predict the material response to the indentation of a hemi-spherical tip and calculate the elasticity modulus of materials, dissipated energy during impact, residual deformation after impact, indentation depth and their conservative and nonconservative components.

RESULTS

As an example, two ophthalmic polymers were compared: CR-39 as the universal ophthalmic standard, and Superfin as Indo Lens U.S., standard. Results showed the model is in good agreement with experimental data and allowed to obtain elasticity moduli for both materials, which showed similar values. A larger conservative component of the displacement for Superfin was also obtained and a smaller calculated residual displacement, which is indicative of less deformed material after low energy impacts.

CONCLUSIONS

The model can satisfactorily predict the behavior of materials under low energy indentation situations. In addition, it can be used to distinguish two apparently similar materials, such as CR-39 and Superfin, and classify them according to their response to these kind of indentations. The technique could be used as a very powerful tool to improve ophthalmic materials.

摘要

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验