MCNP-Automation-Toolkit 🚀

A high‑performance workflow suite for MCNP6 simulations, bridging the gap between resource‑aware task orchestration and lightning‑fast data post‑processing.

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🌐 Language / 語言選擇

• English Description
• 中文說明文件

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🌟 Why This Toolkit?

Running MCNP simulations often involves tedious manual work: babysitting system resources to avoid freezes, manually organizing piles of output files, and extracting tally data by hand.

MCNP-Automation-Toolkit eliminates that drudgery with a dual‑engine approach:

• The Orchestrator (Python) – intelligently manages your hardware and schedules tasks so your PC stays responsive.
• The Parser (C) – extracts simulation results at blazing speed, turning messy .o files into clean spreadsheets.

Whether you're running a single case or a hundred, this toolkit lets you focus on science, not housekeeping.

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📦 Core Components

Component	Language	What it does
Runner / Orchestrator	Python	Monitors CPU/RAM, queues input files, launches MCNP instances, and provides a retro‑style dashboard while you wait.
Data Parser	C	Scans gigabytes of .o files, aligns tally results with your source.csv, and produces consolidated reports in CSV format.

Both tools can be used independently, or you can chain them together for a fully automated workflow.

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🚀 Quick Start

1️⃣ Clone the repository

git clone https://github.com/10809104/MCNP-Automation-Toolkit.git
cd MCNP-Automation-Toolkit

2️⃣ Build the C Parser (optional – pre‑built executables are also available)

cd Parser
gcc -o MCNP_Parser.exe main.c -lcomdlg32 -lshell32 -lgdi32 -lwininet -lurlmon -lshlwapi

Note: You can skip this step by downloading MCNP_Parser.exe from the Releases page.

3️⃣ Install Python dependencies (if running from source)

cd ../Runner
pip install -r requirements.txt   # only requires psutil

4️⃣ Run the full workflow

• Option A (source): python MCNP_Runner.py
• Option B (pre‑built): Download MCNP_Runner.exe from Releases and double‑click.

The GUI will guide you through selecting:

• Your MCNP environment batch file (e.g., mcnp_630_env.bat)
• The working directory containing your model parameter
• The specific input files to run
• CPU and RAM usage limits

After all simulations finish, you can run MCNP_Parser.exe

The GUI will guide you to:

• Click HELP to understand the required file structure and placement
• Select the source CSV files
• Choose the working directory containing your .o output files
• After processing completes, decide whether to merge the results into a single .xlsx file

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📂 Project Structure

MCNP-Automation-Toolkit/
├── Runner/                     # Python source for the Orchestrator
│   ├── MCNP_Runner.py          # Main entry point
│   ├── requirements.txt        # Python dependencies
│   └── README.md               # Component‑specific docs
│
├── Parser/                      # C source for the Data Parser (flat structure for Dev‑C++)
│   ├── main.c                   # Main program (originally in src/)
│   ├── config.h                 # Configuration header
│   ├── tools.h                  # Core parsing functions
│   ├── merge.ps1                # PowerShell script for Excel integration
│   ├── MCNP_Parser.dev          # Dev-c++
│   ├── MCNP_Parser.ico          # Application icon (optional)
│   ├── MCNP_Parser.rc           # Application icon config
│   ├── version.txt              # for auto update
│   └── README.md                # Component‑specific docs
│
├── Examples/                     # Result screenshots and sample outputs
│   ├── runner_demo.png
│   ├── parser_demo.png
│   └── sample_report.csv
│
└── README.md                      # This file

Note for Dev‑C++ users: All C source files are kept in the same directory (Parser/) for easy opening with Dev‑C++ projects. Simply open main.c and compile.

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🖼️ Examples

Runner in Action

The retro‑style dashboard showing active tasks and resource usage

Parser Output

Clean, aligned CSV output ready for analysis

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📜 License

This project is licensed under the MIT License – see the LICENSE file for details.

Developer's Note: This toolkit was born from real nuclear engineering research. You may encounter mixed Chinese/English comments in the source – a mark of its "battle‑tested" origins.

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About Parser/You can get more fromMCNP-Data-Toolkit

Now go automate your MCNP workflow!
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