Точка Синхронізації

Researchers specializing in computational engineering science introduced a novel framework on February 12, 2025, via the arXiv preprint server to address the critical issue of physical inconsistencies in structural modeling code produced by Large Language Models (LLMs). This new methodology, detailed in paper arXiv:2602.07083v1, seeks to ensure that automatically generated programmatic models are both simulation-executable and physically sound, preventing the catastrophic failures commonly seen when AI-generated code is applied to real-world engineering simulations. By focusing on physically consistent programmatic generation, the team aims to bridge the gap between abstract AI capabilities and the rigorous, non-negotiable requirements of structural engineering software. The development of this framework stems from a growing frustration within the engineering community regarding the unreliability of current LLMs. While models like GPT-4 or specialized coding assistants can generate complex structural code rapidly, they often produce "hallucinations" that violate basic physical laws, such as incorrect load distributions, impossible geometry, or invalid material properties. These minor errors, while seemingly small in a text editor, render the code entirely useless for high-fidelity downstream simulations, necessitating manual correction that offsets the time-saving benefits of AI automation. To overcome these hurdles, the proposed framework integrates stringent engineering constraints directly into the generation process. By treating structural modeling as a verifiable programmatic task rather than a purely linguistic one, the researchers have developed a system that validates the physical logic of the code before it reaches the simulation stage. This approach ensures that the output is not only syntactically correct but also adheres to the fundamental laws of physics and specific structural requirements. This advancement marks a significant step toward fully autonomous, reliable computational design, potentially revolutionizing how engineers develop complex infrastructure and mechanical systems.