Graduate Thesis Or Dissertation
 

Monte Carlo model of a capture gamma ray analyzer for a seafloor core sample

Public Deposited

Downloadable Content

Download PDF
Request Accessible Version
https://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/gq67jv45s

Descriptions

Attribute NameValues
Creator
Abstract
  • Of great benefit, but not limited to seafloor mineral exploration, is a technique that fairly rapidly determines the composition of a drilled vibracore (in a time comparable to the time involved in obtaining the core). The rapid assessment is desired to predict whether a given region warrants further exploration by coring. A proposed monitoring system, based on neutron capture gamma ray analysis, consists of a container tank filled with water and tubular extensions that house a Cf-252 neutron source and a detector positioned within the tank. The core sample is passed through the system in stop and count steps. The net count rates, due to "signature" capture gamma rays from neutron capture in elements in the core sample, are proportional to the amount of the element responsible for emitting the capture gamma ray. The proposed system was modeled and simulated by the Monte Carlo method to predict the relationship between the response of the detector and the elemental concentrations within the sample. Accurate and detailed treatment of neutron transport and gamma ray production and attenuation within the system were employed not only to predict the relationship of the photopeak responses with respect to elemental concentrations, but also to permit investigation of the design parameters and structural material changes in the system. The developed Monte Carlo code utilizes a variety of variance reduction techniques, such as implicit absorption with Russian Roulette and deterministic production of the gamma rays of interest, along with a form of correlated sampling to predict simultaneously the responses over a range of interest of the elemental concentrations. The predicted results were compared with predictions obtained from a well established general purpose Monte Carlo code (MCNP).
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, 8-bit Grayscale) using ScandAll PRO 1.8.1 on a Fi-6770A in PDF format. CVista PdfCompressor 5.0 was used for pdf compression and textual OCR.
Replaces
Accessibility Feature

Relationships

Parents:

This work has no parents.

In Collection:

Items

Thumbnail Title Date Uploaded Visibility Actions
file details AlmasoumiAbdullahMS1990.pdf 2017-08-16 Public Download