An Assessment of Mullins Effect in Some Rubber Compounds Over Different Cycles for Their Energy Absorption Ability Through Artificial Intelligence

In recent times, large language models have become popular in materials science for the development of new materials and formulations. An attempt is made in this work to utilize large language models such as the ones used in commercial ChatGPT versions for artificial intelligence applications. In this paper, an assessment is made for the energy absorption in rubber formulations during different cycles of loading and unloading which is intended to stabilize stress softening in rubber-like materials and in each case for the same maximum load. The experimental data obtained by earlier investigators is used for this purpose. Chat GPT4o has been used for the purpose for which the graphical data has been culled from the graphs available for Mullins effect using the commercially available graphical plotting and analysing software. No attempt is made here to go into reasons for behaviour in Mullins effect nor the various aspects of constitutive models for the Mullins effect.