Scholarlink

In the current chapter the assignment for GPT-4 on ChatGPT Plus is to generate a Python code for grain growth simulation by the phase field method. Specifically, the non-conserved Allen-Cahn equation with a suitable free energy functional is solved in 2D using the finite difference method and the explicit Euler forward time-stepping scheme. By virtue of a specific prompt design for GPT-4 the resulting Python code allows solving the phase field equations for any generalized initialization. To this end, two variants of initial grain structures are considered; (i) a spherical grain embedded in a larger grain, and (ii) a Voronoi tessellation-based initial structure. Key aspects such as prompt design, code verification and testing of the outcome are discussed.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Phase Field Modeling of Grain Growth

  • 章节

  • 发表日期：

    2025年

查看全文
  • Rahul Narkhede,
  • Bernhard Eidel

摘要

In the current chapter the assignment for GPT-4 on ChatGPT Plus is to generate a Python code for grain growth simulation by the phase field method. Specifically, the non-conserved Allen-Cahn equation with a suitable free energy functional is solved in 2D using the finite difference method and the explicit Euler forward time-stepping scheme. By virtue of a specific prompt design for GPT-4 the resulting Python code allows solving the phase field equations for any generalized initialization. To this end, two variants of initial grain structures are considered; (i) a spherical grain embedded in a larger grain, and (ii) a Voronoi tessellation-based initial structure. Key aspects such as prompt design, code verification and testing of the outcome are discussed.