This dissertation addresses a diverse range of topics in the physics-based broadband ground motion simulation, with a focus on New Zealand applications. In particular the following topics are addressed: the methodology and computational implementation of a New Zealand Velocity Model for broadband ground motion simulation; generalised parametric functions and spatial correlations for seismic velocities in the Canterbury, New Zealand region from surface-wave-based site characterisation; and ground motion simulations of Hope Fault earthquakes. The paragraphs below outline each contribution in more detail. A necessary component in physics-based ground motion simulation is a 3D model which details the seismic velocities in the region of interest. Here a velocity model construction methodology, its computational implementation, and application in the construction of a New Zealand velocity model for use in physics-based broadband ground motion simulation are presented. The methodology utilises multiple datasets spanning different length scales, which is enabled via the use of modular sub-regions, geologic surfaces, and parametric representations of crustal velocity. A number of efficiency-related workflows to decrease the overall computational construction time are employed, while maintaining the flexibility and extensibility to incorporate additional datasets and re- fined velocity parameterizations as they become available. The model comprises explicit representations of the Canterbury, Wellington, Nelson-Tasman, Kaikoura, Marlborough, Waiau, Hanmer and Cheviot sedimentary basins embedded within a regional travel-time tomography-based velocity model for the shallow crust and provides the means to conduct ground motion simulations throughout New Zealand for the first time. Recently developed deep shear-wave velocity profiles in Canterbury enabled models that better characterise the velocity structure within geologic layers of the Canterbury sedimentary basin to be developed. Here the development of depth- and Vs30-dependent para-metric velocity and spatial correlation models to characterise shear-wave velocities within the geologic layers of the Canterbury sedimentary basin are presented. The models utilise data from 22 shear-wave velocity profiles of up to 2.5km depth (derived from surface wave analysis) juxtaposed with models which detail the three-dimensional structure of the geologic formations in the Canterbury sedimentary basin. Parametric velocity equations are presented for Fine Grained Sediments, Gravels, and Tertiary layer groupings. Spatial correlations were developed and applied to generate three-dimensional stochastic velocity perturbations. Collectively, these models enable seismic velocities to be realistically represented for applications such as 3D ground motion and site response simulations. Lastly the New Zealand velocity model is applied to simulate ground motions for a Mw7.51 rupture of the Hope Fault using a physics-based simulation methodology and a 3D crustal velocity model of New Zealand. The simulation methodology was validated for use in the region through comparison with observations for a suite of historic small magnitude earthquakes located proximal to the Hope Fault. Simulations are compared with conventionally utilised empirical ground motion models, with simulated peak ground velocities being notably higher in regions with modelled sedimentary basins. A sensitivity analysis was undertaken where the source characteristics of magnitude, stress parameter, hypocentre location and kinematic slip distribution were varied and an analysis of their effect on ground motion intensities is presented. It was found that the magnitude and stress parameter strongly influenced long and short period ground motion amplitudes, respectively. Ground motion intensities for the Hope Fault scenario are compared with the 2016 Kaikoura Mw7.8 earthquake, it was found that the Kaikoura earthquake produced stronger motions along the eastern South Island, while the Hope Fault scenario resulted in stronger motions immediately West of the near-fault region. The simulated ground motions for this scenario complement prior empirically-based estimates and are informative for mitigation and emergency planning purposes.
This study provides an initial examination of source parameter uncertainty in a New Zealand ground motion simulation model, by simulating multiple event realisations with perturbed source parameters. Small magnitude events in Canterbury have been selected for this study due to the small number of source input parameters, the wealth of recorded data, and the lack of appreciable off-fault non-linear effects. Which provides greater opportunity to identify systematic source, path and site effects, required to robustly investigate the causes of uncertainty.
This paper investigates the effects of variability in source rupture parameters on site-specific physics-based simulated ground motions, ascertained through the systematic analysis of ground motion intensity measures. As a preliminary study, we consider simulations of the 22 February 2011 Christchurch earthquake using the Graves and Pitarka (2015) methodology. The effects of source variability are considered via a sensitivity study in which parameters (hypocentre location, earthquake magnitude, average rupture velocity, fault geometry and the Brune stress parameter) are individually varied by one standard deviation. The sensitivity of simulated ground motion intensity measures are subsequently compared against observational data. The preliminary results from this study indicate that uncertainty in the stress parameter and the rupture velocity have the most significant effect on the high frequency amplitudes. Conversely, magnitude uncertainty was found to be most influential on the spectral acceleration amplitudes at low frequencies. Further work is required to extend this preliminary study to exhaustively consider more events and to include parameter covariance. The ultimate results of this research will assist in the validation of the overall simulation method’s accuracy in capturing various rupture parameters, which is essential for the use of simulated ground motion models in probabilistic seismic hazard analysis.
The aim of this poster is to examine the seismic response of two structural systems when subjected to observed and simulated ground motions (GMs) for the 22 February 2011 (22Feb2011) Christchurch earthquake (Razafindrakoto et al. (2018)) via an automated workflow. The layout and technical details of the automated workflow are described at Motha et. al. (2019).
This thesis documents the development and demonstration of an assessment method for analysing earthquake-related damage to concrete waste water gravity pipes in Christchurch, New Zealand, following the 2010-2011 Canterbury Earthquake Sequence (CES). The method is intended to be internationally adaptable to assist territorial local authorities with improving lifelines infrastructure disaster impact assessment and improvements in resilience. This is achieved through the provision of high-resolution, localised damage data, which demonstrate earthquake impacts along the pipe length. The insights gained will assist decision making and the prioritisation of resources following earthquake events to quickly and efficiently restore network function and reduce community impacts. The method involved obtaining a selection of 55 reinforced concrete gravity waste water pipes with available Closed-Circuit Television (CCTV) inspection footage filmed before and after the CES. The pipes were assessed by reviewing the recordings, and damage was mapped to the nearest metre along the pipe length using Geographic Information Systems. An established, systematic coding process was used for reporting the nature and severity of the observed damage, and to differentiate between pre-existing and new damage resulting from the CES. The damage items were overlaid with geospatial data such as Light Detection and Ranging (LiDAR)-derived ground deformation data, Liquefaction Resistance Index data and seismic ground motion data (Peak Ground acceleration and Peak Ground Velocity) to identify potential relationships between these parameters and pipe performance. Initial assessment outcomes for the pipe selection revealed that main pipe joints and lateral connections were more vulnerable than the pipe body during a seismic event. Smaller diameter pipes may also be more vulnerable than larger pipes during a seismic event. Obvious differential ground movement resulted in increased local damage observations in many cases, however this was not obvious for all pipes. Pipes with older installation ages exhibited more overall damage prior to a seismic event, which is likely attributable to increased chemical and biological deterioration. However, no evidence was found relating pipe age to performance during a seismic event. No evidence was found linking levels of pre-CES damage in a pipe with subsequent seismic performance, and seismic performance with liquefaction resistance or magnitude of seismic ground motion. The results reported are of limited application due to the small demonstration sample size, but reveal the additional level of detail and insight possible using the method presented in this thesis over existing assessment methods, especially in relation to high resolution variations along the length of the pipe such as localised ground deformations evidenced by LiDAR. The results may be improved by studying a larger and more diverse sample pool, automating data collection and input processes in order to improve efficiency and consider additional input such as pipe dip and cumulative damage over a large distance. The method is dependent on comprehensive and accurate pre-event CCTV assessments and LIDAR data so that post-event data could be compared. It is proposed that local territorial authorities should prioritise acquiring this information as a first important step towards improving the seismic resilience of a gravity waste water pipe network.
This thesis documents the development and demonstration of an assessment method for analysing earthquake-related damage to concrete waste water gravity pipes in Christchurch, New Zealand, following the 2010-2011 Canterbury Earthquake Sequence (CES). The method is intended to be internationally adaptable to assist territorial local authorities with improving lifelines infrastructure disaster impact assessment and improvements in resilience. This is achieved through the provision of high-resolution, localised damage data, which demonstrate earthquake impacts along the pipe length. The insights gained will assist decision making and the prioritisation of resources following earthquake events to quickly and efficiently restore network function and reduce community impacts. The method involved obtaining a selection of 55 reinforced concrete gravity waste water pipes with available Closed-Circuit Television (CCTV) inspection footage filmed before and after the CES. The pipes were assessed by reviewing the recordings, and damage was mapped to the nearest metre along the pipe length using Geographic Information Systems. An established, systematic coding process was used for reporting the nature and severity of the observed damage, and to differentiate between pre-existing and new damage resulting from the CES. The damage items were overlaid with geospatial data such as Light Detection and Ranging (LiDAR)-derived ground deformation data, Liquefaction Resistance Index data and seismic ground motion data (Peak Ground acceleration and Peak Ground Velocity) to identify potential relationships between these parameters and pipe performance. Initial assessment outcomes for the pipe selection revealed that main pipe joints and lateral connections were more vulnerable than the pipe body during a seismic event. Smaller diameter pipes may also be more vulnerable than larger pipes during a seismic event. Obvious differential ground movement resulted in increased local damage observations in many cases, however this was not obvious for all pipes. Pipes with older installation ages exhibited more overall damage prior to a seismic event, which is likely attributable to increased chemical and biological deterioration. However, no evidence was found relating pipe age to performance during a seismic event. No evidence was found linking levels of pre-CES damage in a pipe with subsequent seismic performance, and seismic performance with liquefaction resistance or magnitude of seismic ground motion. The results reported are of limited application due to the small demonstration sample size, but reveal the additional level of detail and insight possible using the method presented in this thesis over existing assessment methods, especially in relation to high resolution variations along the length of the pipe such as localised ground deformations evidenced by LiDAR. The results may be improved by studying a larger and more diverse sample pool, automating data collection and input processes in order to improve efficiency and consider additional input such as pipe dip and cumulative damage over a large distance. The method is dependent on comprehensive and accurate pre-event CCTV assessments and LIDAR data so that post-event data could be compared. It is proposed that local territorial authorities should prioritise acquiring this information as a first important step towards improving the seismic resilience of a gravity waste water pipe network.
Predicting building collapse due to seismic motion is critical in design and more so after a major event. Damaged structures can appear sound, but collapse under following major events. There can thus be significant risk in decision making after a major seismic event concerning the safe occupation of a building or surrounding areas, versus the unknown impact of unknown major aftershocks. Model-based pushover analyses are effective if the structural properties are well understood, which is not valid post-event when this risk information is most useful. This research combines Hysteresis Loop Analysis (HLA) structural health monitoring (SHM) and Incremental Dynamic Analysis (IDA) methods to determine collapse capacity and probability of collapse for a specific structure, at any time, a range of earthquake excitations to ensure robustness. The nonlinear dynamic analysis method presented enables constant updating of building performance predictions using post-event SHM results. The resulting combined methods provide near real-time updating of collapse fragility curves as events progress, quantifying the change of collapse probability or seismic induced losses for decision-making - a novel, higher resolution risk analysis than previously available. The methods are not computationally expensive and there is no requirement for a validated numerical model. Results show significant potential benefits and a clear evolution of risk. They also show clear need for extending SHM toward creating improved predictive models for analysis of subsequent events, where the Christchurch series of 2010-2011 had significant post-event aftershocks after each main event. Finally, the overall method is generalisable to any typical engineering demand parameter.
The Canterbury earthquake and aftershock sequence in New Zealand during 2010-2011 subjected the city’s structures to a significant accumulated cyclic demand and raised significant questions regarding the low-cycle fatigue demands imposed upon the structures. There is a significant challenge to quantify the level of cumulative demand imposed on structures and to assess the percentage of a structure's fatigue life that has been consumed as a result of this earthquake sequence. It is important to be able to quantify the cumulative demand to determine how a building will perform in a subsequent large earthquake and inform repair and re-occupancy decisions. This paper investigates the cumulative fatigue demand for a structure located within the Christchurch Central Business District (CBD). Time history analysis and equivalent cycle counting methods are applied across the Canterbury earthquake sequence, using key events from September 4th 2010 and February 22nd , 2011 main shocks. The estimate of the cumulative fatigue demand is then compared to the expected capacity of a case study reinforced concrete bridge pier, to undertake a structure-specific fatigue assessment. The analysis is undertaken to approximate the portion of the structural fatigue capacity that has been consumed, and how much residual capacity remains. Results are assessed for recordings at the four Christchurch central city strong motion recording sites installed by the GeoNet programme, to provide an estimate of variation in results. The computed cyclic demand results are compared to code-based design methods and as assessment of the inelastic displacement demand of the reinforcing steel. Results are also presented in a fragility context where a de minimis (inconsequential), irreparable damage and full fatigue fracture are defined to provide a probabilistic assessment of the fatigue damage incurred. This methodology can provide input into the overall assessment of fatigue demands and residual capacity.
© 2019, Springer-Verlag GmbH Germany, part of Springer Nature. Prediction of building collapse due to significant seismic motion is a principle objective of earthquake engineers, particularly after a major seismic event when the structure is damaged and decisions may need to be made rapidly concerning the safe occupation of a building or surrounding areas. Traditional model-based pushover analyses are effective, but only if the structural properties are well understood, which is not the case after an event when that information is most useful. This paper combines hysteresis loop analysis (HLA) structural health monitoring (SHM) and incremental dynamic analysis (IDA) methods to identify and then analyse collapse capacity and the probability of collapse for a specific structure, at any time, a range of earthquake excitations to ensure robustness. This nonlinear dynamic analysis enables constant updating of building performance predictions following a given and subsequent earthquake events, which can result in difficult to identify deterioration of structural components and their resulting capacity, all of which is far more difficult using static pushover analysis. The combined methods and analysis provide near real-time updating of the collapse fragility curves as events progress, thus quantifying the change of collapse probability or seismic induced losses very soon after an earthquake for decision-making. Thus, this combination of methods enables a novel, higher-resolution analysis of risk that was not previously available. The methods are not computationally expensive and there is no requirement for a validated numerical model, thus providing a relatively simpler means of assessing collapse probability immediately post-event when such speed can provide better information for critical decision-making. Finally, the results also show a clear need to extend the area of SHM toward creating improved predictive models for analysis of subsequent events, where the Christchurch series of 2010–2011 had significant post-event aftershocks.
