Detection of Building Damage Using Helmholtz Tomography

High-rise buildings with dense permanent installations of continuously recording accelerometers offer a unique opportunity to observe temporal and spatial variations in the propagation properties of seismic waves. When precise, floor-by-floor measurements of frequency-dependent travel times can be made, accurate models of material properties (e.g., stiffness or rigidity) can be determined using seismic tomographic imaging techniques. By measuring changes in the material properties, damage to the structure can be detected and localized after shaking events such as earthquakes. Here, seismic Helmholtz tomography is applied to simulated waveform data from a high-rise building, and its feasibility is demonstrated. A 52-story dual system building-braced-frame core surrounded by an outrigger steel moment frame-in downtown Los Angeles is used for the computational basis. It is part of the Community Seismic Network and has a three-component accelerometer installed on every floor. A finite-element model of the building based on structural drawings is used for the computation of synthetic seismograms for 60 damage scenarios in which the stiffness of the building is perturbed in different locations across both adjacent and distributed floors and to varying degrees. The dynamic analysis loading function is a Gaussian pulse applied to the lowest level fixed boundary condition, producing a broadband response on all floors. After narrowband filtering the synthetic seismograms and measuring the maximum amplitude, the frequency-dependent travel times and differential travel times are computed. The travel-time and amplitude measurements are converted to shear-wave velocity at each floor via the Helmholtz wave equation whose solutions can be used to track perturbations to wavefronts through densely sampled wavefields. These results provide validation of the method's application to recorded data from real buildings to detect and locate structural damage using earthquake, explosion, or ambient seismic noise data in near-real time.