DrTheo Glashier
Research Associate in Large-scale Infrastructure Monitoring
Department of Civil and Environmental Engineering - Faculty of Engineering
Orcid identifier0000-0003-4513-8022 (opens in a new tab)
- Research Associate in Large-scale Infrastructure MonitoringDepartment of Civil and Environmental Engineering - Faculty of Engineering
- 251, Skempton Building, South Kensington Campus, United Kingdom
BIO
My PhD focuses on the health monitoring of the world’s first metal 3D printed structure: the MX3D Bridge.
Little is known of the long-term behaviour of metal produced using additive manufacturing, as its response to static loading differs from conventionally formed metal. For instance, the new manufactured components exhibit reduced strength, stiffness and ductility in the build direction.
Adequate monitoring of the bridge is therefore required to gain a better understanding of long-term response of additively manufactured metal. However, to enable health monitoring of the MX3D Bridge, through accurate structural change detection, the environmental and operational variations (such as temperature) which real-world structures are exposed to, first require modelling.
I have, so far, concentrated on developing accurate response predictions of the bridge’s response to (daily and seasonal) temperature fluctuations. My PhD therefore also involves the implementation and improvement of structural health monitoring techniques and workflows.
Little is known of the long-term behaviour of metal produced using additive manufacturing, as its response to static loading differs from conventionally formed metal. For instance, the new manufactured components exhibit reduced strength, stiffness and ductility in the build direction.
Adequate monitoring of the bridge is therefore required to gain a better understanding of long-term response of additively manufactured metal. However, to enable health monitoring of the MX3D Bridge, through accurate structural change detection, the environmental and operational variations (such as temperature) which real-world structures are exposed to, first require modelling.
I have, so far, concentrated on developing accurate response predictions of the bridge’s response to (daily and seasonal) temperature fluctuations. My PhD therefore also involves the implementation and improvement of structural health monitoring techniques and workflows.
ACADEMIC POSITIONS
- Research Assistant in Large-scale Infrastructure MonitoringImperial College London, Civil and Environmental Engineering, London, United Kingdom1 Jul 2025 - present
- PhD studentImperial College London, Civil and Environmental Engineering, London, United Kingdom1 Mar 2021 - 15 Jun 2025
- MEng Mechanical EngineeringUniversity of Sheffield, Mechanical Engineering, Sheffield, United Kingdom1 Oct 2015 - 17 Jul 2019
NON-ACADEMIC POSITIONS
- E-monitoring engineerTotalEnergies, Exploration and Production, Pau, France1 Oct 2019 - 30 Sep 2020
DEGREES
- PhDImperial College London, London, United Kingdom1 Mar 2021 - 15 Jun 2025
- MEng Mechanical EngineeringUniversity of Sheffield, Sheffield, United Kingdom1 Oct 2015 - 1 Jul 2019
POSTGRADUATE TRAINING
- Introduction to machine learningImperial College London, Imperial College London, London, United Kingdom
- Data processing with Python PandasImperial College London, London, United Kingdom
- Machine learning with PythonImperial College London, Graduate School, London, United KingdomOther
LANGUAGES
- EnglishCan peer review
- FrenchCan peer review
FACULTY
- Faculty of Engineering
POSITION NAME
- Research Associate in Large-scale Infrastructure M