Nuclear Engineering ETDs

Publication Date

Summer 7-14-2022

Abstract

The need to simulate subcritical benchmark parameters quickly and accurately is becoming increasing important. When using Monte Carlo methods this is traditionally done using a fixed-source calculation where a particle and its progeny are tracked until their removal from the system. This method can be slow for near critical systems. The use of a k-eigenvalue solver could reduce the computational footprint and reduce the need to post process data.

This is done for four parameters from the ICSBEP benchmark values: R_1 , R_2 , M_L, and M_eff. These parameters are calculated in two new distinct ways. First, is directly using MCNP KCODE. Second by using a response-based importance map to bias the starting weight of neutrons based on the birth location. The direct method benefits from reduced runtimes but suffers from inaccuracy at higher k-eigenvalues. The map-based method is very accurate and has improved computational efficiency.

Keywords

Subcritical, Benchmark, K-eigenvalue, MCNP

Document Type

Dissertation

Language

English

Degree Name

Nuclear Engineering

Level of Degree

Doctoral

Department Name

Nuclear Engineering

First Committee Member (Chair)

Christopher Perfetti

Second Committee Member

Michael Rising

Third Committee Member

Cassiano Endres De Oliveira

Fourth Committee Member

Brian Kiedrowski

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