The recent instances of seismic activity in Canterbury (2010/11) and Kaikōura (2016) in New Zealand have exposed an unexpected level of damage to non-structural components, such as buried pipelines and building envelope systems. The cost of broken buried infrastructure, such as pipeline systems, to the Christchurch Council was excessive, as was the cost of repairing building envelopes to building owners in both Christchurch and Wellington (due to the Kaikōura earthquake), which indicates there are problems with compliance pathways for both of these systems. Councils rely on product testing and robust engineering design practices to provide compliance certification on the suitability of product systems, while asset and building owners rely on the compliance as proof of an acceptable design. In addition, forensic engineers and lifeline analysts rely on the same product testing and design techniques to analyse earthquake-related failures or predict future outcomes pre-earthquake, respectively. The aim of this research was to record the actual field-observed damage from the Canterbury and Kaikōura earthquakes of seismic damage to buried pipeline and building envelope systems, develop suitable testing protocols to be able to test the systems’ seismic resilience, and produce prediction design tools that deliver results that reflect the collected field observations with better accuracy than the present tools used by forensic engineers and lifeline analysts. The main research chapters of this thesis comprise of four publications that describe the gathering of seismic damage to pipes (Publication 1 of 4) and building envelopes (Publication 2 of 4). Experimental testing and the development of prediction design tools for both systems are described in Publications 3 and 4. The field observation (discussed in Publication 1 of 4) revealed that segmented pipe joints, such as those used in thick-walled PVC pipes, were particularly unsatisfactory with respect to the joint’s seismic resilience capabilities. Once the joint was damaged, silt and other deleterious material were able to penetrate the pipeline, causing blockages and the shutdown of key infrastructure services. At present, the governing Standards for PVC pipes are AS/NZS 1477 (pressure systems) and AS/NZS 1260 (gravity systems), which do not include a protocol for evaluating the PVC pipes for joint seismic resilience. Testing methodologies were designed to test a PVC pipe joint under various different simultaneously applied axial and transverse loads (discussed in Publication 3 of 4). The goal of the laboratory experiment was to establish an easy to apply testing protocol that could fill the void in the mentioned standards and produce boundary data that could be used to develop a design tool that could predict the observed failures given site-specific conditions surrounding the pipe. A tremendous amount of building envelope glazing system damage was recorded in the CBDs of both Christchurch and Wellington, which included gasket dislodgement, cracked glazing, and dislodged glazing. The observational research (Publication 2 of 4) concluded that the glazing systems were a good indication of building envelope damage as the glazing had consistent breaking characteristics, like a ballistic fuse used in forensic blast analysis. The compliance testing protocol recognised in the New Zealand Building Code, Verification Method E2/VM1, relies on the testing method from the Standard AS/NZS 4284 and stipulates the inclusion of typical penetrations, such as glazing systems, to be included in the test specimen. Some of the building envelope systems that failed in the recent New Zealand earthquakes were assessed with glazing systems using either the AS/NZS 4284 or E2/VM1 methods and still failed unexpectedly, which suggests that improvements to the testing protocols are required. An experiment was designed to mimic the observed earthquake damage using bi-directional loading (discussed in Publication 4 of 4) and to identify improvements to the current testing protocol. In a similar way to pipes, the observational and test data was then used to develop a design prediction tool. For both pipes (Publication 3 of 4) and glazing systems (Publication 4 of 4), experimentation suggests that modifying the existing testing Standards would yield more realistic earthquake damage results. The research indicates that including a specific joint testing regime for pipes and positioning the glazing system in a specific location in the specimen would improve the relevant Standards with respect to seismic resilience of these systems. Improving seismic resilience in pipe joints and glazing systems would improve existing Council compliance pathways, which would potentially reduce the liability of damage claims against the government after an earthquake event. The developed design prediction tool, for both pipe and glazing systems, uses local data specific to the system being scrutinised, such as local geology, dimensional characteristics of the system, actual or predicted peak ground accelerations (both vertically and horizontally) and results of product-specific bi-directional testing. The design prediction tools would improve the accuracy of existing techniques used by forensic engineers examining the cause of failure after an earthquake and for lifeline analysts examining predictive earthquake damage scenarios.
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.
Having a quick but reliable insight into the likelihood of damage to bridges immediately after an earthquake is an important concern especially in the earthquake prone countries such as New Zealand for ensuring emergency transportation network operations. A set of primary indicators necessary to perform damage likelihood assessment are ground motion parameters such as peak ground acceleration (PGA) at each bridge site. Organizations, such as GNS in New Zealand, record these parameters using distributed arrays of sensors. The challenge is that those sensors are not installed at, or close to, bridge sites and so bridge site specific data are not readily available. This study proposes a method to predict ground motion parameters for each bridge site based on remote seismic array recordings. Because of the existing abundant source of data related to two recent strong earthquakes that occurred in 2010 and 2011 and their aftershocks, the city of Christchurch is considered to develop and examine the method. Artificial neural networks have been considered for this research. Accelerations recorded by the GeoNet seismic array were considered to develop a functional relationship enabling the prediction of PGAs. http://www.nzsee.org.nz/db/2013/Posters.htm
The objective of the study presented herein is to assess three commonly used CPT-based liquefaction evaluation procedures and three liquefaction severity index frameworks using data from the 2010–2011 Canterbury earthquake sequence. Specifically, post-event field observations, ground motion recordings, and results from a recently completed extensive geotechnical site investigation programme at selected strong motion stations (SMSs) in the city of Christchurch and surrounding towns are used herein. Unlike similar studies that used data from free-field sites, accelerogram characteristics at the SMS locations can be used to assess the performance of liquefaction evaluation procedures prior to their use in the computation of surficial manifestation severity indices. Results from this study indicate that for cases with evidence of liquefaction triggering in the accelerograms, the majority of liquefaction evaluation procedures yielded correct predictions, regardless of whether surficial manifestation of liquefaction was evident or not. For cases with no evidence of liquefaction in the accelerograms (and no observed surficial evidence of liquefaction triggering), the majority of liquefaction evaluation procedures predicted liquefaction was triggered. When all cases are used to assess the performance of liquefaction severity index frameworks, a poor correlation is shown between the observed severity of liquefaction surface manifestation and the calculated severity indices. However, only using those cases where the liquefaction evaluation procedures yielded correct predictions, there is an improvement in the correlation, with the Liquefaction Severity Number (LSN) being the best performing of the frameworks investigated herein. However scatter in the relationship between the observed and calculated surficial manifestation still remains for all liquefaction severity index frameworks.
Predictive modelling provides an efficient means to analyse the coastal environment and generate knowledge for long term urban planning. In this study, the numerical models SWAN and XBeach were incorporated into the ESRI ArcGIS interface by means of the BeachMMtool. This was applied to the Greater Christchurch coastal environment to simulate geomorphological evolution through hydrodynamic forcing. Simulations were performed using the recent sea level rise predictions by the Intergovernmental Panel on Climate Change (2013) to determine whether the statutory requirements outlined in the New Zealand Coastal Policy Statement 2010 are consistent with central, regional and district designations. Our results indicate that current land use zoning in Greater Christchurch is not consistent with these predictions. This is because coastal hazard risk has not been thoroughly quantified during the process of installing the Canterbury Earthquake Recovery Authority residential red zone. However, the Christchurch City Council’s flood management area does provide an extent to which managed coastal retreat is a real option. The results of this research suggest that progradation will continue to occur along the Christchurch foreshore due to the net sediment flux retaining an onshore direction and the current hydrodynamic activity not being strong enough to move sediment offshore. However, inundation during periods of storm surge poses a risk to human habitation on low lying areas around the Avon-Heathcote Estuary and the Brooklands lagoon.
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.
