# Statistical Tests for Convergence in Monte Carlo Criticality Calculations

## Abstract

This report describes methods for using statistical tests to automatically determine convergence of Monte Carlo (MC) iterations in criticality calculations. The methods described herein are intended to replace the traditional approach used for the past 60 years: make a trial run; determine convergence based on plots of k-effective and Shannon entropy vs cycle; adjust the input parameters for controlling the iterations; make a final run to obtain results and statistics.

- Authors:

- Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
- Univ. of Michigan, Ann Arbor, MI (United States)

- Publication Date:

- Research Org.:
- Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

- Sponsoring Org.:
- USDOE National Nuclear Security Administration (NNSA)

- OSTI Identifier:
- 1471319

- Report Number(s):
- LA-UR-18-28764

- DOE Contract Number:
- AC52-06NA25396

- Resource Type:
- Technical Report

- Country of Publication:
- United States

- Language:
- English

- Subject:
- MCNP; neutron transport

### Citation Formats

```
Brown, Forrest B., and Martin, William Russell.
```*Statistical Tests for Convergence in Monte Carlo Criticality Calculations*. United States: N. p., 2018.
Web. doi:10.2172/1471319.

```
Brown, Forrest B., & Martin, William Russell.
```*Statistical Tests for Convergence in Monte Carlo Criticality Calculations*. United States. doi:10.2172/1471319.

```
Brown, Forrest B., and Martin, William Russell. Fri .
"Statistical Tests for Convergence in Monte Carlo Criticality Calculations". United States. doi:10.2172/1471319. https://www.osti.gov/servlets/purl/1471319.
```

```
@article{osti_1471319,
```

title = {Statistical Tests for Convergence in Monte Carlo Criticality Calculations},

author = {Brown, Forrest B. and Martin, William Russell},

abstractNote = {This report describes methods for using statistical tests to automatically determine convergence of Monte Carlo (MC) iterations in criticality calculations. The methods described herein are intended to replace the traditional approach used for the past 60 years: make a trial run; determine convergence based on plots of k-effective and Shannon entropy vs cycle; adjust the input parameters for controlling the iterations; make a final run to obtain results and statistics.},

doi = {10.2172/1471319},

journal = {},

number = ,

volume = ,

place = {United States},

year = {2018},

month = {9}

}

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