Bridge-vehicle interaction for structural health monitoring: potentials, applications, and limitations

Structural Health Monitoring (SHM) is an integral part of infrastructure maintenance and management systems due to socio-economic, safety and security reasons. The behaviour of a structure under vibration depends on structure characteristics. The change of structure characteristics may suggest the change in system behaviour due to the presence of damage(s) within. Therefore the consistent, output signal guided, and system dependable markers would be convenient tool for the online monitoring, the maintenance, rehabilitation strategies, and optimized decision making policies as required by the engineers, owners, managers, and the users from both safety and serviceability aspects. SHM has a very significant advantage over traditional investigations where tangible and intangible costs of a very high degree are often incurred due to the disruption of service. Additionally, SHM through bridge-vehicle interaction opens up opportunities for continuous tracking of the condition of the structure. Research in this area is still in initial stage and is extremely promising. This PhD focuses on using bridge-vehicle interaction response for SHM of damaged or deteriorating bridges to monitor or assess them under operating conditions. In the present study, a number of damage detection markers have been investigated and proposed in order to identify the existence, location, and the extent of an open crack in the structure. The theoretical and experimental investigation has been conducted on Single Degree of Freedom linear system, simply supported beams. The novel Delay Vector Variance (DVV) methodology has been employed for characterization of structural behaviour by time-domain response analysis. Also, the analysis of responses of actual bridges using DVV method has been for the first time employed for this kind of investigation.

The influence of thermal plasma profiles on low-frequency Alfvén eigenmode dynamics in a tokamak

The confinement of fast particles, present in a tokamak plasma as nuclear fusion products and through external heating, will be essential for any future fusion reactor. Fast particles can be expelled from the plasma through their interaction with Alfvén eigenmode (AE) instabilities. AEs can exist in gaps in the Alfvén continuum created by plasma equilibrium non-uniformities. In the ASDEX Upgrade tokamak, low-frequency modes in the frequency range from f ≈ 10 − 90kHz, including beta-induced Alfvén eigenmodes (BAEs) and lower frequency modes with mixed Alfvén and acoustic polarisations, have been observed. These exist in gaps in the Alfvén continuum opened up by geodesic curvature and finite plasma compressibility. In this thesis, a kinetic dispersion relation is solved numerically to investigate the influence of thermal plasma profiles on the evolution of these low-frequency modes during the sawtooth cycle. Using information gained from various experimental sources to constrain the equilibrium reconstructions, realistic safety factor profiles are obtained for the analysis using the CLISTE code. The results for the continuum accumulation point evolution are then compared with experimental results from ASDEX Upgrade during periods of ICRH only as well as for periods with both ICRH and ECRH applied simultaneously. It is found that the diamagnetic frequency plays an important role in influencing the dynamics of BAEs and low-frequency acoustic Alfvén eigenmodes, primarily through the presence of gradients in the thermal plasma profiles. Different types of modes that are observed during discharges heated almost exclusively by ECRH were also investigated. These include electron internal transport barrier (eITB) driven modes, which are observed to coincide with the occurrence of an eITB in the plasma during the low-density phase of the discharge. Also observed are BAE-like modes and edge-TAEs, both of which occur during the H-mode phase of the discharge.