Though rare and unpredictable, earthquakes can and do cause catastrophic destruction when they impact unprepared and vulnerable communities. Extensive damage and failure of vulnerable buildings is a key factor which contributes to seismic-related disasters, making the proactive management of these buildings a necessity to reduce the risk of future disasters arising. The devastating Canterbury earthquakes of 2010 and 2011 brought the urgency of this issue to national importance in New Zealand. The national earthquake-prone building framework came into effect in 2017, obligating authorities to identify existing buildings with the greatest risk of collapse in strong earthquakes and for building owners to strengthen or demolish these buildings within a designated period of time. Though this framework is unique to New Zealand, the challenge of managing the seismic risk of such buildings is common amongst all seismically-active countries. Therefore, looking outward to examine how other jurisdictions legally manage this challenge is useful for reflecting on the approaches taken in New Zealand and understand potential lessons which could be adopted. This research compares the legal framework used to reduce the seismic risk of existing buildings in New Zealand with that of the similarly earthquake-prone countries of Japan and Italy. These legal frameworks are examined with a particular focus on the proactive goal of reducing risk and improving resilience, as is the goal of the international Sendai Framework for Disaster Risk Reduction 2015-2030. The Sendai Framework, which each of the case study countries have committed to and thus have obligations under, forms the legal basis of the need for states to reduce disaster risk in their jurisdictions. In particular, the states’ legal frameworks for existing building risk reduction are examined in the context of the Sendai priorities of understanding disaster risk, strengthening disaster risk governance, and investing in resilience. While this research illustrates that the case study countries have each adopted more proactive risk reduction frameworks in recent years in anticipation of future earthquakes, the frameworks currently focus on a very narrow range of existing buildings and thus are not currently sufficient for promoting the long-term resilience of building stocks. In order to improve resilience, it is argued, legal frameworks need to include a broader range of buildings subject to seismic risk reduction obligations and also to broaden the focus on long-term monitoring of potential risk to buildings.
In the last two decades, New Zealand (NZ) has experienced significant earthquakes, including the 2010 M 7.2 Darfield, 2011 M 6.2 Christchurch, and 2016 M 7.8 Kaikōura events. Amongst these large events, tens of thousands of smaller earthquakes have occurred. While previous event and ground-motion databases have analyzed these events, many events below M 4 have gone undetected. The goal of this study is to expand on previous databases, particularly for small magnitude (M<4) and low-amplitude ground motions. This new database enables a greater understanding of regional variations within NZ and contributes to the validity of internationally developed ground-motion models. The database includes event locations and magnitude estimates with uncertainty considerations, and tectonic type assessed in a hierarchical manner. Ground motions are extracted from the GeoNet FDSN server and assessed for quality using a neural network classification approach. A deep neural network approach is also utilized for picking P and S phases for determination of event hypocentres. Relative hypocentres are further improved by double-difference relocation and will contribute toward developing shallow (< 50 km) seismic tomography models. Analysis of the resulting database is compared with previous studies for discussion of implications toward national hazard prediction models.
To reduce seismic vulnerability and the economic impact of seismic structural damage, it is important to protect structures using supplemental energy dissipation devices. Several types of supplemental damping systems can limit loads transferred to structures and absorb significant response energy without sacrificial structural damage. Lead extrusion dampers are one type of supplemental energy dissipation devices. A smaller volumetric size with high force capacities, called high force to volume (HF2V) devices, have been employed in a large series of scaled and full-scaled experiments, as well as in three new structures in Christchurch and San Francisco. HF2V devices have previously been designed using very simple models with limited precision. They are then manufactured, and tested to ensure force capacities match design goals, potentially necessitating reassembly or redesign if there is large error. In particular, devices with a force capacity well above or below a design range can require more testing and redesign, leading to increased economic and time cost. Thus, there is a major need for a modelling methodology to accurately estimate the range of possible device force capacity values in the design phase – upper and lower bounds. Upper and lower bound force capacity estimates are developed from equations in the metal extrusion literature. These equations consider both friction and extrusion forces between the lead and the bulged shaft in HF2V devices. The equations for the lower and upper bounds are strictly functions of device design parameters ensuring easy use in the design phase. Two different sets of estimates are created, leading to estimates for the lower and upper bounds denoted FLB,1, FUB,1, FUB,2, respectively. The models are validated by comparing the bounds with experimental force capacity data from 15 experimental HF2V device tests. All lower bound estimates are below or almost equal to the experimental device forces, and all upper bound estimates are above. Per the derivation, the (FLB,1, FUB,1) pair provide narrower bounds. The (FLB,1, FUB,1) pair also had a mean lower bound gap of -34%, meaning the lower bound was 74% of device force on average, while the mean upper bound gap for FUB,1 was +23%. These are relatively tight bounds, within ~±2 SE of device manufacture, and can be used as a guide to ensure device forces are in range for the actual design use when manufactured. Therefore, they provide a useful design tool.
The overarching goal of this dissertation is to improve predictive capabilities of geotechnical seismic site response analyses by incorporating additional salient physical phenomena that influence site effects. Specifically, multidimensional wave-propagation effects that are neglected in conventional 1D site response analyses are incorporated by: (1) combining results of 3D regional-scale simulations with 1D nonlinear wave-propagation site response analysis, and (2) modelling soil heterogeneity in 2D site response analyses using spatially-correlated random fields to perturb soil properties. A method to combine results from 3D hybrid physics-based ground motion simulations with site-specific nonlinear site response analyses was developed. The 3D simulations capture 3D ground motion phenomena on a regional scale, while the 1D nonlinear site response, which is informed by detailed site-specific soil characterization data, can capture site effects more rigorously. Simulations of 11 moderate-to-large earthquakes from the 2010-2011 Canterbury Earthquake Sequence (CES) at 20 strong motion stations (SMS) were used to validate simulations with observed ground motions. The predictions were compared to those from an empirically-based ground motion model (GMM), and from 3D simulations with simplified VS30- based site effects modelling. By comparing all predictions to observations at seismic recording stations, it was found that the 3D physics-based simulations can predict ground motions with comparable bias and uncertainty as the GMM, albeit, with significantly lower bias at long periods. Additionally, the explicit modelling of nonlinear site-response improves predictions significantly compared to the simplified VS30-based approach for soft-soil or atypical sites that exhibit exceptionally strong site effects. A method to account for the spatial variability of soils and wave scattering in 2D site response analyses was developed and validated against a database of vertical array sites in California. The inputs required to run the 2D analyses are nominally the same as those required for 1D analyses (except for spatial correlation parameters), enabling easier adoption in practice. The first step was to create the platform and workflow, and to perform a sensitivity study involving 5,400 2D model realizations to investigate the influence of random field input parameters on wave scattering and site response. Boundary conditions were carefully assessed to understand their effect on the modelled response and select appropriate assumptions for use on a 2D model with lateral heterogeneities. Multiple ground-motion intensity measures (IMs) were analyzed to quantify the influence from random field input parameters and boundary conditions. It was found that this method is capable of scattering seismic waves and creating spatially-varying ground motions at the ground surface. The redistribution of ground-motion energy across wider frequency bands, and the scattering attenuation of high-frequency waves in 2D analyses, resemble features observed in empirical transfer functions (ETFs) computed in other studies. The developed 2D method was subsequently extended to more complicated multi-layer soil profiles and applied to a database of 21 vertical array sites in California to test its appropriate- ness for future predictions. Again, different boundary condition and input motion assumptions were explored to extend the method to the in-situ conditions of a vertical array (with a sensor embedded in the soil). ETFs were compared to theoretical transfer functions (TTFs) from conventional 1D analyses and 2D analyses with heterogeneity. Residuals of transfer-function- based IMs, and IMs of surface ground motions, were also used as validation metrics. The spatial variability of transfer-function-based IMs was estimated from 2D models and compared to the event-to-event variability from ETFs. This method was found capable of significantly improving predictions of median ETF amplification factors, especially for sites that display higher event-to-event variability. For sites that are well represented by 1D methods, the 2D approach can underpredict amplification factors at higher modes, suggesting that the level of heterogeneity may be over-represented by the 2D random field models used in this study.
