NUIT 0.2

Wrapper for source term alaysis code NUIT

Contents

• Summary
• Install
• Get Started
• Reference

Summary

pyNUIT is a package in Python which wrappers the source term analysis code NUIT, and integrates various util tools for its control and management.

Install

1. Using git clone: git clone https://github.com/thu-inet/pyNUIT.git
2. Download the zip and unzip to destination path

Only a few basic Python packages are required, including:

• Numpy
• Matplotlib
• Pandas *pyNUIT is platform-independent, yet NUIT is in C++ and you need to have the right complied version to use it. Currrently, pyNUIT uses wine and NUIT for windows to make it usable on Linux, so make sure you get wine installed correctly if you are working with Linux.

Get Started

The most basic module is nt.Model and nt.Output, for management of NUIT input model and its output.

# import pyNUIT
import pyNUIT as nt

# define the model
model = nt.Model()
model.add_nuclide("U235", 0.85)
model.add_nuclide("U238", 4.15)

# define power history
for i in range(10):
    model.add_burnup(time=10, unit='day', val=800E-6)

# define the output
model.set_output("isotope", print_all_step=0)

# library configuration
model.set_library(r"D:\\NUIT\\NUITLib_HTGR_900k")

# run the model to get output
out = model("model.xml", nuitpath="D:\\NUIT\\NUITx.exe")

# read calculation results
burnup = out.burnups[-1]
density = out.get_nuclide_mass("Cs137")[-1]
print(f"Nuclide density of Cs137 at {burnup} MWd/kgU is {density} n/cm/barn")

Histogram class is used to represent the power history, and can transfer its power history into nt.Model to form a complete model.

# define two histogram instances
histo1 = nt.Histogram(["2019-01-15 00:00", "2019-02-26 00:00", "2019-03-26 00:00"], [(0,0), (3.7E6,3.7E6), (3.7E6, 0)])
histo2 = nt.Histogram(["2019-05-28 00:00", "2019-07-02 00:00"], [(0, 0), (3E6, 3E6)])

# concatenate two histograms
histo = histo1 + histo2

# pass the power history to model
histo.model = model
model = histo.to_model(step_length=10*86400)

Classes in nt.data are used to interact with data libraries.

# read the multi-group xs lib
mgxslib = nt.data.MGXSlib.from_datfile("D:\\NUIT\\NUITLib_HTGR_900k\\NuitMgXsLib.dat")

# use existing flux data to collapse into one-group xslib
xslib = mgxslib.to_xslib(flux)

# check the xs of Cs134, MT=102 reaction
print(f"Cross section of Cs-134 Reaction(102) is {xslib("Cs134")(102)}")

# export xslib into .dat file
xslib.to_datfile("xslib.dat")

Reference