Back to results

University of Ontario Institute of Technology

Development of a soft-landing system for space applications

Abstract

dc:description.abstract

The gamma-ray technique is used in industrial and scientific applications. For space, it is used to evaluate the distance in critical soft-landing operations of descent vehicles by measuring the backscattered rays from landing surfaces. While the concept is known, its implementation is poorly documented and concealed. This work aims to investigate the detail necessary for gamma-ray altimeters aside from those already found on spacecraft modules. Monte Carlo simulations along with experiments were performed using a 10 Ci 137Cs irradiator and a high-resolution LaBr detector at the Ontario Tech University gamma facility. The simulation was validated with experiments using aluminum sheets. Different backscattering surfaces were investigated for materials likely encountered by a descent module. The data suggests that surface material composition and density have limited importance. Hydrogen content influences the shape of the spectra, but it does not interfere with the backscatter peak. The simulation agrees with experiment data within 6.29%.

Degree

thesis:*
Name thesis:degree_name
Master of Applied Science (MASc)
Discipline thesis:degree_discipline
Nuclear Engineering
Grantor
University of Ontario Institute of Technology
Year dc:date.issued
2023

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Lee, Isaac
Advisor dc:contributor.advisor
  • Machrafi, Rachid

Rights

Language dc:language.iso
en

Identifiers

dc:identifier.*
Handle dc:identifier.uri
https://hdl.handle.net/10155/1887
OAI identifier oai:identifier
oai:ontariotechu.scholaris.ca:10155/1887

Chain of custody

source
Harvested from
Ontario Institute of Technology
Base URL
ontariotechu.scholaris.ca/server/oai/request
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
related terms
citation

Lee, Isaac. Development of a soft-landing system for space applications. University of Ontario Institute of Technology, 2023. https://hdl.handle.net/10155/1887