Structural Resilience through Model-Based Data Interpretation: From Building to City-Scale Post-Seismic Assessment

Earthquake-design approaches in regions with low to medium seismic hazard often focus on the protection of inhabitants. Therefore, some structural damage is accepted. In addition, large parts of the building stock have usually been built without considering seismic limit states. Thus, earthquake events lead to large-scale post-earthquake assessments in order to determine the safety for occupancy of damaged buildings. Applying model-based data interpretation to earthquake-hit buildings has potential to increase assessment speed and objectivity. By accounting for uncertainties arising from multiple sources, a multiple-model approach for interpretation of ambient-vibration measurements is proposed. While ambient vibrations provide the engineer with quick and cheap measurement data, they are measurements of elastic behavior and therefore, interpretation for post-earthquake assessment must be done with great care. Outcomes of visual inspection and ambient-vibration measurements are combined in order to increase the knowledge of earthquake vulnerability of deteriorated structures and this leads to a measure of structural resilience. First, the applicability and utility of such an approach are shown for a single building. Then, we discuss opportunities (such as additional comparisons with similar buildings in a district) and limitations (high numbers of buildings to assess may result in excessive simulation times) that result from scaling the methodology up to assess entire cities.

Measurement-supported performance assessment of earthquake-damaged concrete and masonry structures

Yves Sylvain Gilles Reuland

As demonstrated by recent events in Italy, New-Zealand, Haiti, and Nepal, earthquakes continue to pose threats to civil infrastructure, including buildings. For a long time seismic ultimate limit states have not been considered in design codes for regions with a low to moderate seismicity (for instance, earthquake hazard has been explicitly introduced into Swiss building codes in 1989). Therefore, earthquakes in such regions are likely to result in important post-earthquake assessment needs. Current post-earthquake assessment methodologies heavily rely on expert-conducted visual inspections, which are potentially subjective and often slow. By implementing model-based data-interpretation methodologies, improvements with regard to both main shortcomings are possible: speeding up integrity assessment and providing an objective complement to visual inspection. The main objective is to improve accuracy and precision of residual-capacity predictions for damaged concrete and masonry buildings. A reduction of the time between an earthquake event and the clearance for occupancy of buildings increases the resilience of cities by limiting the needs for provisional housing and the loss of business opportunities. Ambient-vibration measurements are an interesting data source for structural identification because they are inexpensive and fast to acquire. However, ambient vibrations are characterized by low acceleration amplitudes. Thus, modal properties are representative of the linear and elastic range of structural behavior. True behavior under earthquake-like loading may differ from the behavior under ambient vibrations. Civil-engineering behavior models are approximate and safe and therefore, they provide biased representations. Even sophisticated high-fidelity models omit several parameters such as nonlinear soil-structure interactions, environmental factors, as well as non-structural elements (windows, separation walls, heavy furniture). Therefore, a data-interpretation technique that is accurate in a context of biased and correlated uncertainties is included in the framework. In addition, post-earthquake situations are characterized by uncertain and unforeseen circumstances and gradual knowledge acquisition. Thus, a data-interpretation framework that allows transparent implementation of gradual knowledge acquisition is proposed, based on error-domain model falsification. Using data recorded on full-scale concrete and masonry structures, it is concluded that ambient-vibration measurements are practicable for structural identification. However, highly nonlinear boundary conditions need to be considered in the estimation of discrepancies between model predictions and measurements. A main challenge related to nonlinear behavior predictions based on linearly elastic measurements relies on model extrapolation. Model extrapolation is complicated by modeling uncertainties. The uncertainties that arise in predicting residual load-bearing capacities are reviewed and integrated into this framework in a transparent manner and are applied to illustrative case studies. The proposed framework for data interpretation provides accurate predictions of nonlinear load-bearing behavior, even based on scarce linear measurement data and in the absence of measurements and information related to the initial building condition. In addition, simplified models can provide accurate results by employing conservative estimates for systematic modelling uncertainties.

EPFL2017

Mapping seismic vulnerability at urban scale for disaster risk reduction

Lorenzo Diana, Yves Sylvain Gilles Reuland

Earthquakes do not kill people, buildings do. Transforming existing cities in earthquake resilient systems should be the main goal for researchers in the field of the seismic analysis of entire towns. Providing means for realistic disaster risk scenario can help decision makers in pre- and post-earthquake management and save lives and goods. Two main challenges regarding seismic resilience at urban scale are linked to determining seismic vulnerability before earthquakes and residual capacity following a seismic event. In this way, ambient-vibration measurement is an interesting and non-destructive data source for the seismic vulnerability assessment of towns. It can help in the detection of the real seismic behavior of structure and in the introduction and definition of new construction types in regions with very limited construction data prior to an earthquake. A second measurement after the shock provide information about the possibility of occupancy of damaged buildings.

2018

A model-based data-interpretation framework for post-earthquake building assessment with scarce measurement data

Pierino Lestuzzi, Yves Sylvain Gilles Reuland, Ian Smith

Recent earthquake events throughout the world have once again exposed the vulnerability of buildings with respect to earthquakes. It is unlikely and unsustainable to design and - especially in regions with low-to-moderate seismic hazard – to retrofit all buildings to remain within elastic displacement ranges during earthquakes with high return periods. Therefore, post-earthquake assessment plays a fundamental role in the resilience of cities, given the potential to reduce time between an earthquake event and the clearance for (renewed) occupancy of a building. In this paper, a framework for model-based data interpretation of measurements of earthquake-damaged structures is presented. The framework allows engineers to combine ambient-vibration measurements and visual inspection to reduce parametric uncertainty of a high-fidelity model using the error-domain model-falsification methodology. For building types that have limited stiffness contributions from non-structural elements (i.e. shear-wall buildings) and for which non-ductile failure modes (such as out-of-plane failure) can be excluded, reduction in natural frequency and damage grades derived from visual inspection provide global measurement sources for structural identification. The application of the proposed methodology to a shear-resisting building tested on a shake table illustrates that vulnerability-curve predictions provide accurate damage estimates for subsequent earthquakes with probabilities between 50% and 100% for five measured scenarios. In complete absence of baseline information regarding the initial building state and the earthquake signal, parametric uncertainty is reduced by up to 76%. This study thus demonstrates usefulness for certain building types to enhance post-seismic vulnerability predictions.

2019

Measurement-supported performance assessment of earthquake-damaged concrete and masonry structures

Yves Sylvain Gilles Reuland

EPFL2017