This thesis presents an assessment of historic seismic performance of the New Zealand stopbank network from the 1968 Inangahua earthquake through to the 2016 Kaikōura earthquake. An overview of the types of stopbanks and the main aspects of the design and construction of earthen stopbanks was presented. Stopbanks are structures that are widely used on the banks of rivers and other water bodies to protect against the impact of flood events. Earthen stopbanks are found to be the most used for such protection measures. Different stopbank damage or failure modes that may occur due to flooding or earthquake excitation were assessed with a focus on past earthquakes internationally, and examples of these damage and failure modes were presented. Stopbank damage and assessment reports were collated from available reconnaissance literature to develop the first geospatial database of stopbank damage observed in past earthquakes in New Zealand. Damage was observed in four earthquakes over the past 50 years, with a number of earthquakes resulting in no stopbank damage. The damage database therefore focussed on the Edgecumbe, Darfield, Christchurch and Kaikōura earthquakes. Cracking of the crest and liquefaction-induced settlement were the most common forms of damage observed. To understand the seismic demand on the stopbank network in past earthquakes, geospatial analyses were undertaken to approximate the peak ground acceleration (PGA) across the stopbank network for ten large earthquakes that have occurred in New Zealand over the past 50 years. The relationship between the demand, represented by the peak ground acceleration (PGA) and damage is discussed and key trends identified. Comparison of the seismic demand and the distribution of damage suggested that the seismic performance of the New Zealand stopbank network has been generally good across all events considered. Although a significant length of the stopbank networks were exposed to high levels of shaking in past events, the overall damage length was a small percentage of this. The key aspect controlling performance was the performance of the underlying foundation soils and the effect of this on the stopbank structure and stability.
Asset management in power systems is exercised to improve network reliability to provide confidence and security for customers and asset owners. While there are well-established reliability metrics that are used to measure and manage business-as-usual disruptions, an increasing appreciation of the consequences of low-probability high-impact events means that resilience is increasingly being factored into asset management in order to provide robustness and redundancy to components and wider networks. This is particularly important for electricity systems, given that a range of other infrastructure lifelines depend upon their operation. The 2010-2011 Canterbury Earthquake Sequence provides valuable insights into electricity system criticality and resilience in the face of severe earthquake impacts. While above-ground assets are relatively easy to monitor and repair, underground assets such as cables emplaced across wide areas in the distribution network are difficult to monitor, identify faults on, and repair. This study has characterised in detail the impacts to buried electricity cables in Christchurch resulting from seismically-induced ground deformation caused primarily by liquefaction and lateral spread. Primary modes of failure include cable bending, stretching, insulation damage, joint braking and, being pulled off other equipment such as substation connections. Performance and repair data have been compiled into a detailed geospatial database, which in combination with spatial models of peak ground acceleration, peak ground velocity and ground deformation, will be used to establish rigorous relationships between seismicity and performance. These metrics will be used to inform asset owners of network performance in future earthquakes, further assess component criticality, and provide resilience metrics.
Validation is an essential step to assess the applicability of simulated ground motions for utilization in engineering practice, and a comprehensive analysis should include both simple intensity measures (PGA, SA, etc), as well as the seismic response of a range of complex systems obtained by response history analysis. In order to enable a spectrum of complex structural systems to be considered in systematic validation of ground motion simulations in a routine fashion, an automated workflow was developed. Such a workflow enables validation of simulated ground motions in terms of different complex model responses by considering various ground motion sets and different ground motion simulation methods. The automated workflow converts the complex validation process into a routine one by providing a platform to perform the validation process promptly as a built-in process of simulation post-processing. As a case study, validation of simulated ground motions was investigated via the automated workflow by comparing the dynamic responses of three steel special moment frame (SMRF) subjected to the 40 observed and 40 simulated ground motions of 22 February 2011 Christchurch earthquake. The seismic responses of the structures are principally quantified via the peak floor acceleration and maximum inter-storey drift ratio. Overall, the results indicate a general agreement in seismic demands obtained using the recorded and simulated ensembles of ground motions and provide further evidence that simulated ground motions can be used in code-based structural performance assessments in-place of, or in combination with, ensembles of recorded ground motions.
This thesis presents the application of data science techniques, especially machine learning, for the development of seismic damage and loss prediction models for residential buildings. Current post-earthquake building damage evaluation forms are developed for a particular country in mind. The lack of consistency hinders the comparison of building damage between different regions. A new paper form has been developed to address the need for a global universal methodology for post-earthquake building damage assessment. The form was successfully trialled in the street ‘La Morena’ in Mexico City following the 2017 Puebla earthquake. Aside from developing a framework for better input data for performance based earthquake engineering, this project also extended current techniques to derive insights from post-earthquake observations. Machine learning (ML) was applied to seismic damage data of residential buildings in Mexico City following the 2017 Puebla earthquake and in Christchurch following the 2010-2011 Canterbury earthquake sequence (CES). The experience showcased that it is readily possible to develop empirical data only driven models that can successfully identify key damage drivers and hidden underlying correlations without prior engineering knowledge. With adequate maintenance, such models have the potential to be rapidly and easily updated to allow improved damage and loss prediction accuracy and greater ability for models to be generalised. For ML models developed for the key events of the CES, the model trained using data from the 22 February 2011 event generalised the best for loss prediction. This is thought to be because of the large number of instances available for this event and the relatively limited class imbalance between the categories of the target attribute. For the CES, ML highlighted the importance of peak ground acceleration (PGA), building age, building size, liquefaction occurrence, and soil conditions as main factors which affected the losses in residential buildings in Christchurch. ML also highlighted the influence of liquefaction on the buildings losses related to the 22 February 2011 event. Further to the ML model development, the application of post-hoc methodologies was shown to be an effective way to derive insights for ML algorithms that are not intrinsically interpretable. Overall, these provide a basis for the development of ‘greybox’ ML models.
The full scale, in-situ investigations of instrumented buildings present an excellent opportunity to observe their dynamic response in as-built environment, which includes all the real physical properties of a structure under study and its surroundings. The recorded responses can be used for better understanding of behavior of structures by extracting their dynamic characteristics. It is significantly valuable to examine the behavior of buildings under different excitation scenarios. The trends in dynamic characteristics, such as modal frequencies and damping ratios, thus developed can provide quantitative data for the variations in the behavior of buildings. Moreover, such studies provide invaluable information for the development and calibration of realistic models for the prediction of seismic response of structures in model updating and structural health monitoring studies. This thesis comprises two parts. The first part presents an evaluation of seismic responses of two instrumented three storey RC buildings under a selection of 50 earthquakes and behavioral changes after Ms=7.1 Darfield (2010) and Ms=6.3 Christchurch (2011) earthquakes for an instrumented eight story RC building. The dynamic characteristics of the instrumented buildings were identified using state-of-the-art N4SID system identification technique. Seismic response trends were developed for the three storey instrumented buildings in light of the identified frequencies and the peak response accelerations (PRA). Frequencies were observed to decrease with excitation level while no trends are discernible for the damping ratios. Soil-structure interaction (SSI) effects were also determined to ascertain their contribution in the seismic response. For the eight storey building, it was found through system identification that strong nonlinearities in the structural response occurred and manifested themselves in all identified natural frequencies of the building that exhibited a marked decrease during the strong motion duration compared to the pre-Darfield earthquakes. Evidence of foundation rocking was also found that led to a slight decrease in the identified modal frequencies. Permanent stiffness loss was also observed after the strong motion events. The second part constitutes developing and calibrating finite element model (FEM) of the instrumented three storey RC building with a shear core. A three dimensional FEM of the building is developed in stages to analyze the effect of structural, non-structural components (NSCs) and SSI on the building dynamics. Further to accurately replicate the response of the building following the response trends developed in the first part of the thesis, sensitivity based model updating technique was applied. The FEMs were calibrated by tuning the updating parameters which are stiffnesses of concrete, NSCs and soil. The updating parameters were found to generally follow decreasing trends with the excitation level. Finally, the updated FEM was used in time history analyses to assess the building seismic performance at the serviceability limit state shaking. Overall, this research will contribute towards better understanding and prediction of the behavior of structures subjected to ground motion.
