This study explicitly investigates uncertainties in physics-based ground motion simulation validation for earthquakes in the Canterbury region. The simulations utilise the Graves and Pitarka (2015) hybrid methodology, with separately quantified parametric uncertainties in the comprehensive physics and simplified physics components of the model. The study is limited to the simulation of 148 small magnitude (Mw 3.5 – 5) earthquakes, with a point source approximation for the source rupture representations, which also enables a focus on a small number of relevant uncertainties. The parametric uncertainties under consideration were selected through sensitivity analysis, and specifically include: magnitude, Brune stress parameter and high frequency rupture velocity. Twenty Monte Carlo realisations were used to sample parameter uncertainties for each of the 148 events. Residuals associated with the following intensity measures: spectral acceleration, peak ground velocity, arias intensity and significant duration, were ascertained. Using these residuals, validation was performed through assessment of systematic biases in site and source terms from mixed-effects regression. Based on the results to date, initial standard deviation recommendations for parameter uncertainties, based on the Canterbury simulations have been obtained. This work ultimately provides an initial step toward explicit incorporation of modelling uncertainty in simulated ground motion predictions for future events, which will improve the use of simulation models in seismic hazard analysis. We plan to subsequently assess uncertainties for larger magnitude events with more complex ruptures, and events across a larger geographic region, as well as uncertainties due to path attenuation, site effects, and more general model epistemic uncertainties.
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.
Probabilistic Structural Fire Engineering (PSFE) has been introduced to overcome the limitations of current conventional approaches used for the design of fire-exposed structures. Current structural fire design investigates worst-case fire scenarios and include multiple thermal and structural analyses. PSFE permits buildings to be designed to a level of life safety or economic loss that may occur in future fire events with the help of a probabilistic approach. This thesis presents modifications to the adoption of a Performance-Based Earthquake Engineering (PBEE) framework in Probabilistic Structural Fire Engineering (PSFE). The probabilistic approach runs through a series of interrelationships between different variables, and successive convolution integrals of these interrelationships result in probabilities of different measures. The process starts with the definition of a fire severity measure (FSM), which best relates fire hazard intensity with structural response. It is identified by satisfying efficiency and sufficiency criteria as described by the PBEE framework. The relationship between a fire hazard and corresponding structural response is established by analysis methods. One method that has been used to quantify this relationship in PSFE is Incremental Fire Analysis (IFA). The existing IFA approach produces unrealistic fire scenarios, as fire profiles may be scaled to wide ranges of fire severity levels, which may not physically represent any real fires. Two new techniques are introduced in this thesis to limit extensive scaling. In order to obtain an annual rate of exceedance of fire hazard and structural response for an office building, an occurrence model and an attenuation model for office fires are generated for both Christchurch city and New Zealand. The results show that Christchurch city is 15% less likely to experience fires that have the potential to cause structural failures in comparison to all of New Zealand. In establishing better predictive relationships between fires and structural response, cumulative incident radiation (a fire hazard property) is found to be the most appropriate fire severity measure. This research brings together existing research on various sources of uncertainty in probabilistic structural fire engineering, such as elements affecting post-flashover fire development factors (fuel load, ventilation, surface lining and compartment geometry), fire models, analysis methods and structural reliability. Epistemic uncertainty and aleatory uncertainty are investigated in the thesis by examining the uncertainty associated with modelling and the factors that influence post-flashover development of fires. A survey of 12 buildings in Christchurch in combination with recent surveys in New Zealand produced new statistical data on post-flashover development factors in office buildings in New Zealand. The effects of these parameters on temperature-time profiles are evaluated. The effects of epistemic uncertainty due to fire models in the estimation of structural response is also calculated. Parametric fires are found to have large uncertainty in the prediction of post-flashover fires, while the BFD curves have large uncertainties in prediction of structural response. These uncertainties need to be incorporated into failure probability calculations. Uncertainty in structural modelling shows that the choices that are made during modelling have a large influence on realistic predictions of structural response.
Central Christchurch restaurant and bars say they could be heading into the "worst winter to date". Eight years on from the earthquakes there are more restaurants and bars in the city than ever before - but owners say there aren't enough customers. Now they're grappling with added uncertainty over the effect of the mosque attacks on visitor numbers.
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 increase of the world's population located near areas prone to natural disasters has given rise to new ‘mega risks’; the rebuild after disasters will test the governments’ capabilities to provide appropriate responses to protect the people and businesses. During the aftermath of the Christchurch earthquakes (2010-2012) that destroyed much of the inner city, the government of New Zealand set up a new partnership between the public and private sector to rebuild the city’s infrastructure. The new alliance, called SCIRT, used traditional risk management methods in the many construction projects. And, in hindsight, this was seen as one of the causes for some of the unanticipated problems. This study investigated the risk management practices in the post-disaster recovery to produce a specific risk management model that can be used effectively during future post-disaster situations. The aim was to develop a risk management guideline for more integrated risk management and fill the gap that arises when the traditional risk management framework is used in post-disaster situations. The study used the SCIRT alliance as a case study. The findings of the study are based on time and financial data from 100 rebuild projects, and from surveying and interviewing risk management professionals connected to the infrastructure recovery programme. The study focussed on post-disaster risk management in construction as a whole. It took into consideration the changes that happened to the people, the work and the environment due to the disaster. System thinking, and system dynamics techniques have been used due to the complexity of the recovery and to minimise the effect of unforeseen consequences. Based on an extensive literature review, the following methods were used to produce the model. The analytical hierarchical process and the relative importance index have been used to identify the critical risks inside the recovery project. System theory methods and quantitative graph theory have been used to investigate the dynamics of risks between the different management levels. Qualitative comparative analysis has been used to explore the critical success factors. And finally, causal loop diagrams combined with the grounded theory approach has been used to develop the model itself. The study identified that inexperienced staff, low management competency, poor communication, scope uncertainty, and non-alignment of the timing of strategic decisions with schedule demands, were the key risk factors in recovery projects. Among the critical risk groups, it was found that at a strategic management level, financial risks attracted the highest level of interest, as the client needs to secure funding. At both alliance-management and alliance-execution levels, the safety and environmental risks were given top priority due to a combination of high levels of emotional, reputational and media stresses. Risks arising from a lack of resources combined with the high volume of work and the concern that the cost could go out of control, alongside the aforementioned funding issues encouraged the client to create the recovery alliance model with large reputable construction organisations to lock in the recovery cost, at a time when the scope was still uncertain. This study found that building trust between all parties, clearer communication and a constant interactive flow of information, established a more working environment. Competent and clear allocation of risk management responsibilities, cultural shift, risk prioritisation, and staff training were crucial factors. Finally, the post-disaster risk management (PDRM) model can be described as an integrated risk management model that considers how the changes which happened to the environment, the people and their work, caused them to think differently to ease the complexity of the recovery projects. The model should be used as a guideline for recovery systems, especially after an earthquake, looking in detail at all the attributes and the concepts, which influence the risk management for more effective PDRM. The PDRM model is represented in Causal Loops Diagrams (CLD) in Figure 8.31 and based on 10 principles (Figure 8.32) and 26 concepts (Table 8.1) with its attributes.
