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). / Graduation date: 1990
| Identifer | oai:union.ndltd.org:ORGSU/oai:ir.library.oregonstate.edu:1957/38226 |
| Date | 06 December 1989 |
| Creators | Almasoumi, Abdullah Muhammad Sultan |
| Contributors | Binney, Stephen E. |
| Source Sets | Oregon State University |
| Language | en_US |
| Detected Language | English |
| Type | Thesis/Dissertation |
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