USGS Science⌕ Search

USGS · 70188342

System identification based on deconvolution and cross correlation: An application to a 20‐story instrumented building in Anchorage, Alaska

Abstract

Deconvolution and cross‐correlation techniques are used for system identification of a 20‐story steel, moment‐resisting frame building in downtown Anchorage, Alaska. This regular‐plan midrise structure is instrumented with a 32‐channel accelerometer array at 10 levels. The impulse response functions (IRFs) and correlation functions (CFs) are computed based on waveforms recorded from ambient vibrations and five local and regional earthquakes. The earthquakes occurred from 2005 to 2014 with moment magnitudes between 4.7 and 6.2 over a range of azimuths at epicenter distances of 13.3–183 km. The building’s fundamental frequencies and mode shapes are determined using a complex mode indicator function based on singular value decomposition of multiple reference frequency‐response functions. The traveling waves, identified in IRFs with a virtual source at the roof, and CFs are used to estimate the intrinsic attenuation associated with the fundamental modes and shear‐wave velocity in the building. Although the cross correlation of the waveforms at various levels with the corresponding waveform at the first floor provides more complicated wave propagation than that from the deconvolution with virtual source at the roof, the shear‐wave velocities identified by both techniques are consistent—the largest difference in average values is within 8%. The median shear‐wave velocity from the IRFs of five earthquakes is 191 m/s for the east–west (E‐W), 205 m/s for the north–south (N‐S), and 176 m/s for the torsional responses. The building’s average intrinsic‐damping ratio is estimated to be 3.7% and 3.4% in the 0.2–1 Hz frequency band for the E‐W and N‐S directions, respectively. These results are intended to serve as reference for the undamaged condition of the building, which may be used for tracking changes in structural integrity during and after future earthquakes.

Explore related subjects

90° N90° S · 180° W ← longitude → 180° E
Source-reported bounding extent: 61.20793488105243° to 61.21661483933352° latitude; -149.90917682647705° to -149.88252639770508° longitude. This indicates report coverage, not an exact sampling location. View area on OpenStreetMap.

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Weiping Wen, Erol Kalkan. 2017-02-14. System identification based on deconvolution and cross correlation: An application to a 20‐story instrumented building in Anchorage, Alaska. https://doi.org/10.1785/0120160069

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related USGS reports

Re-evaluation of shaking, dynamic strain, and the source of the 1886 Charleston, South Carolina, earthquake

As the largest historical event in the eastern United States, the 1886 Charleston, South Carolina, earthquake, plays a prominent role in our nation’s seismological and human history and an outsized role in our probabilistic ground‐motion hazard estimates, affecting building codes, insurance rates, and geophysical monitoring. Thus, constraining the characteristics of the 1886 earthquake source, as well as the nature of its shaking distribution and impacts to the extent possible, is essential. Given its vintage, however, societal, geological, and geophysical datasets are limited compared with those used in modern seismological analyses. Because of these limitations, some characteristics of the rupture model are fundamentally nonunique. Still, by re‐evaluating all available data, I can constrain several key aspects of this earthquake. I show that several interpretations in recent analyses are inconsistent regarding the inferred source; shaking; ground failure; and, particularly, railway impacts. Importantly, I have shown that although dynamic strain caused the ground failure that led to track deformation, without the intermediate liquefaction step, dynamic strain alone was unlikely to be the source of rail deformation, contrary to earlier studies. Had earlier pronouncements that dynamic strain is a real concern for bending railways held true, there would be serious ramifications for railway engineering as well as for other above‐ and below‐ground linear infrastructure.

South Carolina↗

ETAS-positive: Extracting unbiased epidemic-type aftershock models from incomplete earthquake catalogs

Earthquake catalogs are inherently incomplete, and short-term fluctuations in catalog completeness can strongly bias estimates of seismicity parameters. Here, we extend the positive statistics framework recently introduced for estimating Gutenberg–Richter a and b values to the Epidemic-Type Aftershock Sequence (ETAS) model. The approach focuses on complete magnitude–time intervals defined by pairs of earthquakes in which the second event is larger than the first. Comprehensive synthetic tests demonstrate that the proposed ETAS + method retrieves nearly unbiased parameter estimates even from highly incomplete catalogs, whereas parameters obtained using classical estimation approaches are strongly biased. Application to Southern California reveals a similar trend, with the productivity scaling parameter α approaching the b value, consistent with self-similar earthquake triggering within estimation uncertainties. Owing to its robustness against catalog incompleteness and computational efficiency, the ETAS + method provides a powerful new tool for seismicity analysis and earthquake forecasting.

California↗