omid2007hope/MOP-Simulator: v3.7.0: Autonomous AI Penetration Research Platform

Abstract

After 536 commits, I am incredibly proud to announce the first stable release of MOP Simulator V3.7! 🚀 This release evolves the project from a standalone native binary into a full-stack autonomous AI research platform. It tightly couples a high-performance C++23 terminal ballistics simulation engine with a Node.js/Express backend API, Google Gemini AI integration, and a modern Next.js 16 Web UI. 🌟 Key Features Two Modes of Operation: Interactive Simulation: Run manual, executable-based simulations directly from the terminal. Autonomous AI Agent: Let the LLM hypothesize target geometries, execute massive multi-scenario penetrations, aggregate telemetry to MongoDB, and automatically synthesize findings into research articles. High-Fidelity Physics Engine: Simulates massive ordnance penetrators (e.g., GBU-57, BLU-109), orbital kinetic strikes, and various bunker buster bombs. Includes cavity-expansion / Two-Phase Forrestal deceleration models. Integrates Walker-Anderson Hydrodynamic Rod Erosion (WAPM). Applies CEB-FIP Dynamic Increase Factors (DIF) and Walker-Wasley Hugoniot shock initiation criteria. Rich Scenarios: Support for complex layered bunkers, different target materials, and sequential multi-bomb salvo strikes (e.g., Operation Midnight Hammer). ⚠️ Important Disclaimers & EULA WARNING: This software is a high-fidelity, advanced physics and penetration simulator. Usage of this application is strictly restricted to recreational, educational, and hobbyist purposes. I am a solo developer, not a researcher at a national lab (like Los Alamos). While the physics engine is designed to be as accurate as possible, it is not certified for real-world engineering, defense analysis, or physical destructive testing. There are still missing capabilities and accuracy gaps that will be addressed in future versions. By using this repository, you acknowledge the terms of the EULA and understand this is an educational research sandbox. 💬 Feedback Feedback is highly encouraged and appreciated! Please be honest, precise, and constructive regarding the physics models, the numerical drift, and where accuracy can be improved in V4.0. 🛠️ Installation Please refer to the README.md for full instructions on setting up the C++ engine (requires GCC/MinGW-w64 with C++23 support), the Node.js backend, and the Next.js frontend.