The KU Leuven Structural Mechanics Section is performing state-of-the-art research on, and has a strong track record in, vibration based structural identification and evaluation, combining both theoretical and experimental work.
The successful applicant is soon to obtain or has obtained a MSc degree (or equivalent) in Civil or Mechanical Engineering or a closely related field with very good to excellent grades.
Next to this, he or she must have a solid background and keen interest in structural dynamics and finite element analysis, strong communication, programming, and problem solving skills, proficiency in English, the ability to meet the admission requirements of the KU Leuven Arenberg Doctoral School, and the motivation to successfully complete the PhD project within 4 years.
An adequate and efficient assessment of structural performance after extreme events such as fire, an earthquake or flooding, is essential for increasing the resilience and sustainability of our infrastructure.
Unfortunately, current practice in post-fire structural condition assessment is far from this goal, as the many uncertainties associated with fire exposure and residual mechanical properties are not sufficiently taken into account, and appropriate non-destructive testing mechanisms are lacking.
As a result, refurbishmentand demolition are often needlessly pursued. In a new joint research project funded by the Research Foundation Flanders (FWO) which involves two PhD projects, the Structural Mechanics Section of KU Leuven and the Magnel Laboratory of Ghent University will join forces for developing a much more rational post-fire assessment methodology.
This PhD project focuses on the non-destructive identification of the residual load-bearing capacity of reinforced concrete structural elements and connections after a fire event.
The aim of the PhD project is to investigate the potential of dynamic quasi-distributed fiber optic strain sensing for obtaining global and cross-sectional stiffness properties, since for example neutral axis positions under pure bending deformation can be obtained from the bending modes in a subsequent modal analysis step.
The investigation will involve forward modelling using nonlinear finite element analysis, as well as inverse modelling with advanced signal processing and system identification techniques.
Due attention will be paid to the statistical assessment of identification errors as well as to optimal experiment design.
Based on the results, a new methodology for post-fire structural condition assessment will be developed, tested and implemented on beam and plate structures.