Research
Damage detection techniques through simulation of building response to damage with small-scale scenarios imposed in finite-element models of existing buildings that also have sensors deployed on multiple floors recording vibration data.
For pdfs and full reference, see full publication list.
Published Studies
- Filippitzis et al., Sparse Bayesian learning for damage identification using nonlinear models: Application to weld fractures of steel-frame buildings, Struct. Control and Health Monitoring, 2022.
- Abdelbarr et al., Decomposition approach for damage detection, localization, and quantification for a 52-story building in downtown Los Angeles, J. Eng. Mech., 2020.
- Filippitzis et al., Identification of sparse damage in steel-frame buildings using dense seismic array measurements, IWSHM 2019.
- Kohler et al., Detection of building damage using Helmholtz tomography, Bull. Seis. Soc. Am., 2018.
- Massari et al., Damage detection by template-matching of scattered waves, Bull. Seis. Soc. Am., 2018.
- Ebrahimian, et al., Parametric estimation of dispersive viscoe-lastic layered media with application to structural health monitoring, Soil Dynamics and Earthquake Engineering, 2018.
- Ebrahimian, et al., Parametric estimation of wave dispersion for system identification of building structures, EVACES2017, 2017
