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Numerical simulations of Geiger-Müller tubes to determine their conversion factors and directional response

radlab 최신버젼 다운로드

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![Header](https://raw.githubusercontent.com/Gissio/radlab/main/simulations/sbm20/data/geometry.png)

# Rad Lab

[![Python](https://img.shields.io/badge/Python-3.9%2B-blue.svg)](https://www.python.org/)
[![Geant4](https://img.shields.io/badge/Geant4-11.x-green.svg)](https://geant4.web.cern.ch/)
[![Calzone](https://img.shields.io/badge/powered_by-Calzone-orange)](https://calzone.readthedocs.io/)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)

## Overview

**Rad Lab** is a Monte-Carlo simulation toolkit for modeling the performance of **Geiger–Müller tubes**. Built on top of Calzone/Geant4, it provides an easy-to-use, reproducible, and extensible environment for detector simulation and design.

With Rad Lab, you can:

* Compute **detector efficiency** (detected particles per incident particle).
* Determine **dose sensitivity** (cpm per µSv/h) using ICRP 74.
* Explore the **directional response** of detectors.
* Obtain correct **sensitivities** for various radiation sources.
* Prototype and evaluate **measurement geometries**.

## Simulations

Explore the included notebooks:

* [Simulated gamma spectra](tools/build-spectra.ipynb)
* [J305 Geiger tube](simulations/j305/j305.ipynb)
* [M4011 Geiger tube](simulations/m4011/m4011.ipynb)
* [HH614 Geiger tube](simulations/hh614/hh614.ipynb)
* [СБМ20 (SBM20) Geiger tube](simulations/sbm20/sbm20.ipynb)
* [СИЗБГ (SI3BG) Geiger tube](simulations/si3bg/si3bg.ipynb)
* [LND 7317 Geiger tube](simulations/lnd7317/lnd7317.ipynb)

## Installation

1. Install the latest **Geant4** binary release: https://geant4.web.cern.ch/download/
2. Install Python: https://www.python.org/
3. Install PIP: https://pip.pypa.io/en/stable/
4. Install Python dependencies:

```
   pip install -r requirements.txt
   ```

5. Install VSCode: https://code.visualstudio.com/
6. In VSCode, install the **Jupyter** extension (left toolbar → Extensions → search for "Jupyter").

## Usage

1. Start from an existing example notebook to create or modify a detector.
2. Edit the geometry file `data/geometry.toml`. (See Calzone Geometry docs: [https://calzone.readthedocs.io/en/latest/geometry.html](https://calzone.readthedocs.io/en/latest/geometry.html))
3. Open the corresponding notebook in VS Code and run the simulation.

## Coordinate system

Rad Lab uses a right-handed coordinate system:

* **x-axis:** along the detector’s length
* **y-axis:** direction of incoming radiation
* **z-axis:** upward

## Display a geometry

To display a geometry:

```
calzone display [geometry.toml]
```

For navigation instructions, see the Calzone Interactive Display docs:
[https://calzone.readthedocs.io/en/latest/display.html](https://calzone.readthedocs.io/en/latest/display.html)

## Detailed explanation

Rad Lab performs the following steps:

1. **Loads geometry**

A `geometry.toml` file specifies:

* a `Source` box emitting parallel particles toward the detector at the coordinate origin. The source area equals the width × height of this box.
   * an `EffectiveVolume`, inside which freed electrons are counted.

2. **Runs Monte-Carlo transport**

Particle transport is simulated using Calzone/Geant4.

3. **Counts ionization electrons**

Electrons entering or produced in the `EffectiveVolume` are counted.

4. **Computes detector efficiency**

Efficiency = detected electrons / incident particles.

5. **Computes dose sensitivity**

* **Ambient dose equivalent:** using ICRP 74.

6. **Generates emission spectra**

* **Isotopes:** spectra from `paceENSDF` (IAEA ENSDF data).
   * **X-ray tubes:** spectra from `SpekPy`.
   * **Natural background:** modeled using data from Thakur (2022, Radiopurity studies of a rock sample from the Aut region).

7. **Computes equivalent effective dose** for each source.

### Supported radiation sources

| Source             | Type  | Main emissions         |
| ------------------ | ----- | ---------------------- |
| Cs-137             | γ     | 662 keV                |
| Co-60              | γ     | 1173 + 1332 keV        |
| Tc-99m             | γ     | 140 + 142 keV          |
| I-131              | γ     | Complex spectrum       |
| Lu-177             | γ     | 113 + 208 keV          |
| Am-241             | γ     | 59 keV                 |
| Radium             | γ     | Ra-226 chain           |
| Uranium ore        | γ     | U-235 and U-238 series |
| Uranium glaze      | γ     | Processed uranium      |
| Depleted uranium   | γ     | U-238                  |
| Thorium ore        | γ     | Th-232 series          |
| X-ray tube (60 kV) | X     | Bremsstrahlung         |
| K-40               | γ     | 1461 keV               |
| Natural background | Mixed | Typical environmental  |

## Adding radioactive sources

To generate or update gamma spectra, run the notebook:
[build-spectra.ipynb](tools/build-spectra.ipynb)

You will need:

* [paceENSDF](https://pypi.org/project/paceENSDF/)
* [spekPy](https://pypi.org/project/spekpy/)

## Acknowledgements

* Special thanks to **BikingBoffin** from [/r/radiation](https://www.reddit.com/r/Radiation/comments/1hdifrz/geiger_tube_efficiency_and_dose_rate/) for inspiring this project.

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