Buildings subject to earthquake shaking will tend to move not only horizontally but also rotate in plan. In-plan rotation is known as “building torsion” and it may occur for a variety of reasons, including stiffness and strength eccentricity and/or torsional effects from ground motions. Methods to consider torsion in structural design standards generally involve analysis of the structure in its elastic state. This is despite the fact that the structural elements can yield, thereby significantly altering the building response and the structural element demands. If demands become too large, the structure may collapse. While a number of studies have been conducted into the behavior of structures considering inelastic building torsion, there appears to be no consensus that one method is better than another and as a result, provisions within current design standards have not adopted recent proposals in the literature. However, the Canterbury Earthquakes Royal Commission recently made the recommendation that provisions to account for inelastic torsional response of buildings be introduced within New Zealand building standards. Consequently, this study examines how and to what extent the torsional response due to system eccentricity may affect the seismic performance of a building and considers what a simple design method should account for. It is concluded that new methods should be simple, be applicable to both the elastic and inelastic range of response, consider bidirectional excitation and include guidance for multi-story systems.
This study explicitly investigates uncertainties in physics-based ground motion simulation validation for earthquakes in the Canterbury region. The simulations utilise the Graves and Pitarka (2015) hybrid methodology, with separately quantified parametric uncertainties in the comprehensive physics and simplified physics components of the model. The study is limited to the simulation of 148 small magnitude (Mw 3.5 – 5) earthquakes, with a point source approximation for the source rupture representations, which also enables a focus on a small number of relevant uncertainties. The parametric uncertainties under consideration were selected through sensitivity analysis, and specifically include: magnitude, Brune stress parameter and high frequency rupture velocity. Twenty Monte Carlo realisations were used to sample parameter uncertainties for each of the 148 events. Residuals associated with the following intensity measures: spectral acceleration, peak ground velocity, arias intensity and significant duration, were ascertained. Using these residuals, validation was performed through assessment of systematic biases in site and source terms from mixed-effects regression. Based on the results to date, initial standard deviation recommendations for parameter uncertainties, based on the Canterbury simulations have been obtained. This work ultimately provides an initial step toward explicit incorporation of modelling uncertainty in simulated ground motion predictions for future events, which will improve the use of simulation models in seismic hazard analysis. We plan to subsequently assess uncertainties for larger magnitude events with more complex ruptures, and events across a larger geographic region, as well as uncertainties due to path attenuation, site effects, and more general model epistemic uncertainties.
Natural hazards continue to have adverse effects on communities and households worldwide, accelerating research on proactively identifying and enhancing characteristics associated with resilience. Although resilience is often characterized as a return to normal, recent studies of postdisaster recovery have highlighted the ways in which new opportunities can emerge following disruption, challenging the status quo. Conversely, recovery and reconstruction may serve to reinforce preexisting social, institutional, and development pathways. Our understanding of these dynamics is limited however by the small number of practice examples, particularly for rural communities in developed nations. This study uses a social–ecological inventory to document the drivers, pathways, and mechanisms of resilience following a large-magnitude earthquake in Kaikōura, a coastal community in Aotearoa New Zealand. As part of the planning and implementation phase of a multiyear project, we used the tool as the basis for indepth and contextually sensitive analysis of rural resilience. Moreover, the deliberate application of social–ecological inventory was the first step in the research team reengaging with the community following the event. The inventory process provided an opportunity for research partners to share their stories and experiences and develop a shared understanding of changes that had taken place in the community. Results provide empirical insight into reactions to disruptive change associated with disasters. The inventory also informed the design of targeted research collaborations, established a platform for longer-term community engagement, and provides a baseline for assessing longitudinal changes in key resilience-related characteristics and community capacities. Findings suggest the utility of social–ecological inventory goes beyond natural resource management, and that it may be appropriate in a range of contexts where institutional, social, and economic restructuring have developed out of necessity in response to felt or anticipated external stressors.
In this paper we apply Full waveform tomography (FWT) based on the Adjoint-Wavefield (AW) method to iteratively invert a 3-D geophysical velocity model for the Canterbury region (Lee, 2017) from a simple initial model. The seismic wavefields was generated using numerical solution of the 3-D elastodynamic/ visco- elastodynamic equations (EMOD3D was adopted (Graves, 1996)), and through the AW method, gradients of model parameters (compression and shear wave velocity) were computed by implementing the cross-adjoint of forward and backward wavefields. The reversed-in-time displacement residual was utilized as the adjoint source. For inversion, we also account for the near source/ station effects, gradient precondition, smoothening (Gaussian filter in spatial domain) and optimal step length. Simulation-to-observation misfit measurements based on 191 sources at 78 seismic stations in the Canterbury region (Figure 1) were used into our inversion. The inversion process includes multiple frequency bands, starting from 0-0.05Hz, and advancing to higher frequency bands (0-0.1Hz and 0-0.2Hz). Each frequency band was used for up to 10 iterations or no optimal step length found. After 3 FWT inversion runs, the simulated seismograms computed using our final model show a good matching with the observed seismograms at frequencies from 0 - 0.2 Hz and the normalized least-squared misfit error has been significantly reduced. Over all, the synthetic study of FWT shows a good application to improve the crustal velocity models from the existed geological models and the seismic data of the different earthquake events happened in the Canterbury region.
