This research explores how Large Language Models can transform scientific computing by automating code translation while maintaining correctness through human verification.

• Demonstrates effective translation of Fortran to C++ code for scientific applications
• Proposes a human-in-the-loop approach to ensure accuracy of AI-generated translations
• Establishes methodology for creating modern APIs from legacy scientific code
• Addresses challenges specific to scientific computing's unique requirements

For engineering teams, this research provides a practical framework to leverage AI for modernizing critical legacy code while maintaining scientific integrity and computational performance.

Leveraging Large Language Models for Code Translation and Software Development in Scientific Computing