We tried some example's with MontePy

MontePy is a Python-based Monte Carlo simulation tool designed for radiation transport modeling and analysis, offering a flexible, open-source alternative to MCNP. It allows users to define geometries, materials, particle sources, and detectors within Python, enabling streamlined setup and automation of simulations. MontePy is ideal for educational, research, and development purposes where Python integration is beneficial.

You can try following code, this may help you:

To use MontePy, start by installing it via `pip install montepy` or by cloning the repository with `git clone https://github.com/username/montepy.git`, navigating to the folder, and running `pip install -e .`. Once installed, import the library using `import montepy as mp`. Define the geometry, for example, a sphere: `geometry = mp.Geometry(shape="sphere", radius=5)`, and assign it a material, like water, with `material = mp.Material(name="water", density=1.0)`, then associate the geometry with the material using `geometry.set_material(material)`. Next, define the particle source by setting the particle type and energy, as in `source = mp.Source(particle="neutron", energy=2.0)`. You can also add detectors to measure properties like flux: `detector = mp.Detector(position=(0, 0, 10), quantity="flux")`. Now configure the simulation with all defined elements, and run it using `simulation = mp.Simulation(geometry=geometry, source=source, detectors=[detector])` and `simulation.run(histories=10000)`. To access results, retrieve the flux measurement from the detector with `flux_result = detector.get_result("flux")` and print it: `print("Flux at detector position:", flux_result)`. Optionally, visualize the results using libraries like Matplotlib, such as `import matplotlib.pyplot as plt`, followed by `plt.plot(flux_result)`, `plt.title("Flux Distribution")`, `plt.xlabel("Position")`, and `plt.ylabel("Flux")`, finishing with `plt.show()`. This simple setup guides you through creating and analyzing a basic Monte Carlo simulation with MontePy.

Thank you so much for your information. I will try it.