This document set represents the current, consolidated Version 3.0 of the Interpretive Engineering Methodology for Controlled Pressure-Relief Intervention. It is intended as an open proposal for structured, independent evaluation by qualified fire-safety engineers and researchers. Development History and Transparent Correction In the interest of complete transparency, we have documented the project's development history. Early working drafts (v1.0) contained significant methodological errors, including speculative numerical results derived from fabricated computational fluid dynamics (CFD) simulations and fictionalized reconstructions of historical firefighting incidents. These errors have been completely removed, not merely edited. We treat these earlier versions not as failures, but as a critical part of the verification process; the discipline of an engineering project lies in the ability to identify, disclose, and correct errors rather than attempting to conceal them Utility of Archive Versions for Researchers We have opted to maintain access to earlier versions of this work, as they serve as a valuable "research log" for those studying the intersection of engineering and artificial intelligence. For researchers, these documents provide a clear, real-world example of how generative AI systems can produce "hallucinations"—plausible-sounding but factually incorrect technical data, detailed fake scenarios, and misleading CFD results. We believe that providing this transparency offers a useful case study for the broader research community on the critical necessity of verifying all AI-generated technical content. Current Standing The current Version 3.0 We explicitly state that this concept currently sits at Technology Readiness Level (TRL) 1–2. No component of this work should be read as validated, demonstrated, or field-ready. Version 3.0 is the sole source for this methodology. Earlier versions are preserved strictly for historical accountability and should not be used as a basis for any engineering or operational assessment.
Oleg Zmiievskyi (Sun,) studied this question.