Research undertaken and literature reviewed show that major natural disasters present considerable risk to Governors Bay. Earthquakes, and resulting secondary hazards from natural disasters, could lead to the isolation of the Governors Bay community for an extended period. In particular, the rupture of the Alpine Fault and the resulting mega-quake could leave Governors Bay isolated for well over three weeks. Weaknesses in existing infrastructure in Governors Bay further places residents at risk. Therefore, it is essential that residents are prepared for a period of extended isolation, with little to no access to clean water, power, internet and cellular coverage. Ultimately, community preparedness will be the key to maintaining social cohesion and saving lives during an emergency event. The community hub in Governors Bay establishes a pre-determined locale for community co-ordination, collection, and distribution of supplies as well as a functional place to go when all else fails.
When researchers seek to understand community resilience, it often centres on individual agents and actors. They look at the traits individuals have in order to help recover from adverse events, as well as the decisionmaking processes required to plan and adapt. In Aotearoa New Zealand, Māori forms of organising can challenge these. This research was about uncovering Māori forms organising and practices in the context of resilience. The methodology I used was He Awa Whiria/Braided Rivers and storytelling analysis in kanohi ki te kanohi/semi-structured interviews to understand how Māori communities responded to and recovered from the 2010 Darfield (Canterbury), 2011 Ōtautahi/Christchurch, and 2016 Kaikōura earthquakes. Five themes emerged from the project: (i) the importance of marae as a powerful physical location, (ii) the value in building strong reciprocal connections and cultural relationships, (iii) the stronghold that kai/food has in helping to heal communities, (iv) the exchange and trading of resources, and (v) being practical when move forward after a disaster event. As a non-Māori researcher, I have been an outsider to te Ao Māori and to Aotearoa. In using this blended methodology, it became apparent that there are many socio-cultural and historical contentions from the effects of colonisation, assimilation, to grappling with Western norms. Notably, the findings pointed to more similarities than differences, such as taking care of family and communities, being community-driven, and ways of coping with adverse events. This revealed that there are similar ways of doing things regardless of having different customs. This research makes several contributions. It contributes to the field of management studies by addressing gaps in how the concept of resilience is viewed from a practical Māori perspective. The research presents emergency management professionals with similar blended and practical strategies to co-design approaches for collaborative readiness, response, and recovery plans and programmes. The study further demonstrates the localised and tangible benefits that can be gained from utilising a blended methodology and storying method. Ultimately, the purpose of the thesis was to start bridging the gap between agencies and communities, to shift to more Indigenous-led approaches, integrating local Indigenous practices and knowledges that lead to more prepared communities in managing, responding to, and recovering from earthquake hazard events.
According to TS 1170.5, designing a building to satisfy code-prescribed criteria (e.g., drift limit, member safety, P-Δ stability) at the ultimate limit state and relying on the inherent margins within the design code would lead to an acceptable mean annual frequency of collapse (λ꜀) in the range of 10−⁴ to 10−⁵. Modern performance objectives, such as λ꜀ and expected annual loss (EAL), are not explicitly considered. Although buckling-restrained braced frame (BRBF) buildings were widely adopted as lateral load-resisting systems for office and car park buildings in the Christchurch rebuild following the Canterbury earthquakes in New Zealand, there are currently no official guidelines for their design. The primary focus of this study is to develop a risk-targeted design framework for BRBF buildings that can achieve the performance objectives desired by stakeholders. To this extent, key factors influencing λ꜀ and EAL of BRBF buildings are identified. These factors include gusset plate design, number of storeys, design drift limit, BRBF beam-column connection, brace configuration, brace angle, brace material grade, and analysis method (equivalent lateral force vs. modal response spectrum). A novel 3D BRBF modelling approach capable of simulating out-of-plane buckling failure of buckling-restrained brace (BRB) gusset plates is developed. Prior experimental studies on sub-assemblies conducted elsewhere have demonstrated that gusset plates and end zones may buckle out of plane prematurely, before BRBs reach their maximum axial compression load carrying capacity. Current 2D BRBF macro models, typically used in research, cannot simulate this failure mode. A conventional 2D BRBF model underestimates the λ꜀ of a case-study 4-storey super-X configured steel BRBF building (designed according to NZS-3404) by a factor of two compared to the estimate from the proposed 3D model. These findings suggest that the current NZS-3404 gusset plate design method may undersize gusset plates and that using a 2D BRBF model in this case can significantly underestimate λ꜀. Three improved alternative gusset plate design methods that are easy to implement in practice are identified from the literature. Gusset plates in two case-study 4-storey steel BRBF buildings with super-X and diagonal configurations are designed using both the NZS-3404 method and alternative methods. All three alternative design methods are found to be conservative, resulting in an almost three-fold lower λ꜀ for both case-study BRBF buildings compared to those designed using the NZS-3404 method. Analysis results indicate that (i) bidirectional interaction has no significant effect on gusset plate buckling and (ii) mid-span gusset plates are more susceptible to buckling than corner gusset plates. A framework for seismic loss assessment using incremental dynamic analysis (IDA), called loss-oriented hazard-consistent incremental dynamic analysis (LOHC-IDA), is developed. IDA can be conducted with a generic record set, eliminating the arduous site-specific record selection required to conduct multiple stripe analysis (MSA). Traditional IDA, however, is limited in producing hazard-consistent estimates of engineering demand parameters (EDPs), which LOHC-IDA overcomes. LOHC-IDA improves upon existing methods by: (i) incorporating correlations among engineering demand parameters across intensity levels and (ii) using peak ground acceleration (PGA) to predict peak floor acceleration (PFA). For two case-study steel BRBF buildings, LOHC-IDA estimates the EAL and loss distributions conditioned on the intensity level that closely match the MSA results, with an average absolute error of 5%. The influence of factors beyond gusset plate design on the λ꜀ and EAL of 26 case-study steel BRBF buildings (designed in accordance with TS 1170.5) is examined. Hazard-consistent λ꜀ and EAL for these buildings are estimated using the FEMA P-58 loss and risk assessment framework. Among the 26 case-study buildings, 23 satisfy the maximum code-specified λ꜀ limit of 10−⁴. The EAL, normalised by the total building replacement cost, is highest for 2-storey BRBFs (0.22% on average), followed by 4-storey BRBFs (0.16% on average) and 8-storey BRBFs (0.11% on average). Reducing the design drift limit has the most significant effect on lowering λ꜀ (all BRBF designs were drift governed), followed by transitioning from pinned to moment-resisting beam-column connections, reducing the brace angle, and increasing brace strength. BRBF buildings designed using the equivalent lateral force method, on average, have a lower λ꜀ compared to those designed using the modal response spectrum method. Diagonally configured BRBFs exhibit the lowest λ꜀, followed by super- X and chevron configured BRBFs. Most design variables, apart from drift limit and beam-column connection, have limited influence on EAL. A simple method for EDP-targeted design of steel BRBF buildings is proposed. For this purpose, linear regression and CatBoost machine learning models are developed to predict steel BRBF building EDPs using peak storey drift ratio (PSDR) and PFA estimates from the 26 case-study buildings at intensity levels ranging from 80% to 0.5% probability of exceedance in 50 years. The R²ₐₔⱼ of these models is around 0.98, while the average prediction error is less than 10%. Fundamental period (T₁), total building height (Hₜ), and pseudospectral acceleration at T₁, denoted as Sₐ(T₁), are selected as the features to predict PSDR, while T₁, Hₜ, and PGA are the features selected to predict PFA. The EDP-targeted design has three steps: (i) for a given Hₜ value, the PSDR prediction model is used to identify a suitable T₁ that can achieve a desired PSDR target at the design intensity, (ii) a force-based design is then conducted iteratively to achieve the target T₁ by using an appropriate ductility factor and design drift limit, and (iii) based on the T₁ in the final design iteration, the PFA demand estimated by the PFA prediction models is used as a conservative input for the design of acceleration-sensitive non-structural elements. An equation to predict λ꜀ at the design stage is proposed for collapse risk-targeted seismic design of buildings. This equation comprises three principal components: reserve building strength, a proxy for effective structural stiffness, and reserve building deformation capacity. This equation is calibrated for the collapse risk-targeted design of BRBF buildings in New Zealand using results from 26 case-study BRBF buildings. The validity of this equation is demonstrated with three design verification examples designed to specific λ꜀ targets. Considering λ꜀ from hazard-consistent incremental dynamic analysis as the benchmark, the mean absolute percentage error in the design-stage prediction of λ꜀ of the verification buildings is approximately 10%.
