Graduate Thesis Or Dissertation
 

An inherently parallel Monte Carlo linear systems solver applied to neutron diffusion equations

Public Deposited

Downloadable Content

Download PDF
https://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/cj82kb580

Descriptions

Attribute NameValues
Creator
Abstract
  • Linear solvers are often used to solve neutron diffusion problems. These tools have two significant shortcomings. First, parallel implementations provide only a modest speedup. The operations cannot be divided cleanly between processors. Second, for large matrices they can be very slow. Our primary goal is to find a new method for solving linear systems which reduces the impact of these two problems. In this study, we consider a different kind of approach. We employ a Monte Carlo algorithm in two dimensions to solve our linear systems probabilistic ally. We develop our probabilistic model and describe the formulation of our linear system. We also discuss our random sampling technique in some detail. We tally our solutions for both the forward and adjoint problems using path length and last event estimators. Computational results are compared to analytic and numerical benchmark solutions for three metrics: accuracy, convergence, and efficiency. The results detailed herein indicate that the method we have developed can be competitive with common linear solvers. We develop an on-the-fly algorithm as well, which is intended to make more efficient use of our computing resources. While this algorithm exhibits longer run-times, it is far less taxing on the system memory.
Resource Type
Date Available
Date Issued
Degree Level
Degree Name
Degree Field
Degree Grantor
Commencement Year
Advisor
Committee Member
Academic Affiliation
Non-Academic Affiliation
Subject
Rights Statement
Publisher
Peer Reviewed
Language
Digitization Specifications
  • File scanned at 300 ppi (Monochrome, 256 Grayscale) using Capture Perfect 3.0.82 on a Canon DR-9080C in PDF format. CVista PdfCompressor 4.0 was used for pdf compression and textual OCR.
Replaces

Relationships

Parents:

This work has no parents.

In Collection:

Items

Thumbnail Title Date Uploaded Visibility Actions
file details EcclestonBradleyR2001.pdf 2017-08-15 Public Download