Critical infrastructure networks are highly relied on by society such that any disruption to service can have major social and economic implications. Furthermore, these networks are becoming increasingly dependent on each other for normal operation such that an outage or asset failure in one system can easily propagate and cascade across others resulting in widespread disruptions in terms of both magnitude and spatial reach. It is the vulnerability of these networks to disruptions and the corresponding complexities in recovery processes which provide direction to this research. This thesis comprises studies contributing to two areas (i) the modelling of national scale in-terdependent infrastructure systems undergoing major disruptions, and (ii) the tracking and quantification of infrastructure network recovery trajectories following major disruptions. Firstly, methods are presented for identifying nationally significant systemic vulnerabilities and incorporating expert knowledge into the quantification of infrastructure interdependency mod-elling and simulation. With application to the interdependent infrastructures networks across New Zealand, the magnitudes and spatial extents of disruption are investigated. Results high-light the importance in considering interdependencies when assessing disruptive risks and vul-nerabilities in disaster planning applications and prioritising investment decisions for enhancing resilience of national networks. Infrastructure dependencies are further studied in the context of recovery from major disruptions through the analysis of curves measuring network functionality over time. Continued studies into the properties of recovery curves across a database of global natural disasters produce statistical models for predicting the trajectory and expected recovery times. Finally, the use of connectivity based metrics for quantifying infrastructure system functionality during recovery are considered with a case study application to the Christchurch Earthquake (February 22, 2011) wastewater network response.
This study uses 44 high quality liquefaction case histories taken from 22 locations affected by the 2010-2011 Canterbury earthquake sequence to evaluate four commonly used CPT-VS correlations (i.e., Robertson, 2009; Hegazy and Mayne, 2006; Andrus et al., 2007; McGann et al., 2015b). Co-located CPT soundings and VS profiles, developed from surface wave testing, were obtained at 22 locations and case histories were developed for the Mw 7.1, 4 September 2010 Darfield and Mw 6.2, 22 February 2011 Christchurch earthquakes. The CPT soundings are used to generate VS profiles using each of four CPT-VS correlations. These correlated VS profiles are used to estimate the factor of safety against liquefaction using the Kayen et al. (2013) VS-based simplified liquefaction evaluation procedure. An error index is used to quantify the predictive capabilities of these correlations in relation to the observations of liquefaction (or the lack thereof). Additionally, the error indices from the CPT-correlated VS profiles are compared to those obtained using: (1) the Kayen et al. (2013) procedure with surface wave-derived VS profiles, and (2) the Idriss and Boulanger (2008) CPT-based liquefaction evaluation procedure. Based on the error indices, the evaluation procedures based on direct measurements of either CPT or VS provided more accurate liquefaction triggering estimates than those obtained from any of the CPT-VS correlations. However, the performance of the CPT-VS correlations varied, with the Robertson (2009) and Hegazy and Mayne (2006) correlations performing relatively poorly for the Christchurch soils and the Andrus et al. (2007) and McGann et al. (2015b) correlations performing better. The McGann et al. (2015b) correlation had the lowest error indices of the CPT-VS correlations tested, however, none of the CPT-VS correlations provided accurate enough VS predictions to be used for the evaluation of liquefaction triggering using the VS-based liquefaction evaluation procedures.
Motivation This poster aims to present fragility functions for pipelines buried in liquefaction-prone soils. Existing fragility models used to quantify losses can be based on old data or use complex metrics. Addressing these issues, the proposed functions are based on the Christchurch network and soil and utilizes the Canterbury earthquake sequence (CES) data, partially represented in Figure 1. Figure 1 (a) presents the pipe failure dataset, which describes the date, location and pipe on which failures occurred. Figure 1 (b) shows the simulated ground motion intensity median of the 22nd February 2011 earthquake. To develop the model, the network and soil characteristics have also been utilized.
This poster aims to present fragility functions for pipelines buried in liquefaction-prone soils. Existing fragility models used to quantify losses can be based on old data or use complex metrics. Addressing these issues, the proposed functions are based on the Christchurch network and soil and utilizes the Canterbury earthquake sequence (CES) data, partially represented in Figure 1. Figure 1 (a) presents the pipe failure dataset, which describes the date, location and pipe on which failures occurred. Figure 1 (b) shows the simulated ground motion intensity median of the 22nd February 2011 earthquake. To develop the model, the network and soil characteristics have also been utilized
This report presents the simplified seismic assessment of a case study reinforced concrete (RC) building following the newly developed and refined NZSEE/MBIE guidelines on seismic assessment (NZSEE/MBIE, semi-final draft 26 October 2016). After an overview of the step-by-step ‘diagnostic’ process, including an holistic and qualitative description of the expected vulnerabilities and of the assessment strategy/methodology, focus is given, whilst not limited, to the implementation of a Detailed Seismic Assessment (DSA) (NZSEE/MBIE, 2016c). The DSA is intended to provide a more reliable and consistent outcome than what can be provided by an initial seismic assessment (ISA). In fact, while the Initial Seismic Assessment (ISA), of which the Initial Evaluation Procedure is only a part of, is the more natural and still recommended first step in the overall assessment process, it is mostly intended to be a coarse evaluation involving as few resources as reasonably possible. It is thus expected that an ISA will be followed by a Detailed Seismic Assessment (DSA) not only where the threshold of 33%NBS is not achieved but also where important decisions are intended that are reliant on the seismic status of the building. The use of %NBS (% New Building Standard) as a capacity/demand ratio to describe the result of the seismic assessment at all levels of assessment procedure (ISA through to DSA) is deliberate by the NZSEE/MBIE guidelines (Part A) (NZSEE/MBIE 2016a). The rating for the building needs only be based on the lowest level of assessment that is warranted for the particular circumstances. Discussion on how the %NBS rating is to be determined can be found in Section A3.3 (NZSEE/MBIE 2016a), and, more specifically, in Part B for the ISA (NZSEE/MBIE 2016b) and Part C for the DSA (NZSEE/MBIE 2016c). As per other international approaches, the DSA can be based on several analysis procedures to assess the structural behaviour (linear, nonlinear, static or dynamic, force or displacement-based). The significantly revamped NZSEE 2016 Seismic Assessment Guidelines strongly recommend the use of an analytical (basically ‘by hand’) method, referred to the Simple Lateral Mechanism Analysis (SLaMA) as a first phase of any other numerically-based analysis method. Significant effort has thus been dedicated to provide within the NZSEE 2016 guidelines (NZSEE/MBIE 2016c) a step-by-step description of the procedure, either in general terms (Chapter 2) or with specific reference to Reinforced Concrete Buildings (Chapter 5). More specifically, extract from the guidelines, NZSEE “recommend using the Simple Lateral Mechanism Analysis (SLaMA) procedure as a first step in any assessment. While SLaMA is essentially an analysis technique, it enables assessors to investigate (and present in a simple form) the potential contribution and interaction of a number of structural elements and their likely effect on the building’s global capacity. In some cases, the results of a SLaMA will only be indicative. However, it is expected that its use should help assessors achieve a more reliable outcome than if they only carried out a detailed analysis, especially if that analysis is limited to the elastic range For complex structural systems, a 3D dynamic analysis may be necessary to supplement the simplified nonlinear Simple Lateral Mechanism Analysis (SLaMA).” This report presents the development of a full design example for the the implementation of the SLaMA method on a case study buildings and a validation/comparison with a non-linear static (pushover) analysis. The step-by-step-procedure, summarized in Figure 1, will be herein demonstrated from a component level (beams, columns, wall elements) to a subassembly level (hierarchy of strength in a beam-column joint) and to a system level (frame, C-Wall) assuming initially a 2D behaviour of the key structural system, and then incorporating a by-hand 3D behaviour (torsional effects).
At 00:02 on 14th November 2016, a Mw 7.8 earthquake occurred in and offshore of the northeast of the South Island of New Zealand. Fault rupture, ground shaking, liquefaction, and co-seismic landslides caused severe damage to distributed infrastructure, and particularly transportation networks; large segments of the country’s main highway, State Highway 1 (SH1), and the Main North Line (MNL) railway line, were damaged between Picton and Christchurch. The damage caused direct local impacts, including isolation of communities, and wider regional impacts, including disruption of supply chains. Adaptive measures have ensured immediate continued regional transport of goods and people. Air and sea transport increased quickly, both for emergency response and to ensure routine transport of goods. Road diversions have also allowed critical connections to remain operable. This effective response to regional transport challenges allowed Civil Defence Emergency Management to quickly prioritise access to isolated settlements, all of which had road access 23 days after the earthquake. However, 100 days after the earthquake, critical segments of SH1 and the MNL remain closed and their ongoing repairs are a serious national strategic, as well as local, concern. This paper presents the impacts on South Island transport infrastructure, and subsequent management through the emergency response and early recovery phases, during the first 100 days following the initial earthquake, and highlights lessons for transportation system resilience.
At 00:02 on 14th November 2016, a Mw 7.8 earthquake occurred in and offshore of the northeast of the South Island of New Zealand. Fault rupture, ground shaking, liquefaction, and co-seismic landslides caused severe damage to distributed infrastructure, and particularly transportation networks; large segments of the country’s main highway, State Highway 1 (SH1), and the Main North Line (MNL) railway line, were damaged between Picton and Christchurch. The damage caused direct local impacts, including isolation of communities, and wider regional impacts, including disruption of supply chains. Adaptive measures have ensured immediate continued regional transport of goods and people. Air and sea transport increased quickly, both for emergency response and to ensure routine transport of goods. Road diversions have also allowed critical connections to remain operable. This effective response to regional transport challenges allowed Civil Defence Emergency Management to quickly prioritise access to isolated settlements, all of which had road access 23 days after the earthquake. However, 100 days after the earthquake, critical segments of SH1 and the MNL remain closed and their ongoing repairs are a serious national strategic, as well as local, concern. This paper presents the impacts on South Island transport infrastructure, and subsequent management through the emergency response and early recovery phases, during the first 100 days following the initial earthquake, and highlights lessons for transportation system resilience.
This dissertation addresses several fundamental and applied aspects of ground motion selection for seismic response analyses. In particular, the following topics are addressed: the theory and application of ground motion selection for scenario earthquake ruptures; the consideration of causal parameter bounds in ground motion selection; ground motion selection in the near-fault region where directivity effect is significant; and methodologies for epistemic uncertainty consideration and propagation in the context of ground motion selection and seismic performance assessment. The paragraphs below outline each contribution in more detail. A scenario-based ground motion selection method is presented which considers the joint distribution of multiple intensity measure (IM) types based on the generalised conditional intensity measure (GCIM) methodology (Bradley, 2010b, 2012c). The ground motion selection algorithm is based on generating realisations of the considered IM distributions for a specific rupture scenario and then finding the prospective ground motions which best fit the realisations using an optimal amplitude scaling factor. In addition, using different rupture scenarios and site conditions, two important aspects of the GCIM methodology are scrutinised: (i) different weight vectors for the various IMs considered; and (ii) quantifying the importance of replicate selections for ensembles with different numbers of desired ground motions. As an application of the developed scenario-based ground motion selection method, ground motion ensembles are selected to represent several major earthquake scenarios in New Zealand that pose a significant seismic hazard, namely, Alpine, Hope and Porters Pass ruptures for Christchurch city; and Wellington, Ohariu, and Wairarapa ruptures for Wellington city. A rigorous basis is developed, and sensitivity analyses performed, for the consideration of bounds on causal parameters (e.g., magnitude, source-to-site distance, and site condition) for ground motion selection. The effect of causal parameter bound selection on both the number of available prospective ground motions from an initial empirical as-recorded database, and the statistical properties of IMs of selected ground motions are examined. It is also demonstrated that using causal parameter bounds is not a reliable approach to implicitly account for ground motion duration and cumulative effects when selection is based on only spectral acceleration (SA) ordinates. Specific causal parameter bounding criteria are recommended for general use as a ‘default’ bounding criterion with possible adjustments from the analyst based on problem-specific preferences. An approach is presented to consider the forward directivity effects in seismic hazard analysis, which does not separate the hazard calculations for pulse-like and non-pulse-like ground motions. Also, the ability of ground motion selection methods to appropriately select records containing forward directivity pulse motions in the near-fault region is examined. Particular attention is given to ground motion selection which is explicitly based on ground motion IMs, including SA, duration, and cumulative measures; rather than a focus on implicit parameters (i.e., distance, and pulse or non-pulse classifications) that are conventionally used to heuristically distinguish between the near-fault and far-field records. No ad hoc criteria, in terms of the number of directivity ground motions and their pulse periods, are enforced for selecting pulse-like records. Example applications are presented with different rupture characteristics, source-to-site geometry, and site conditions. It is advocated that the selection of ground motions in the near-fault region based on IM properties alone is preferred to that in which the proportion of pulse-like motions and their pulse periods are specified a priori as strict criteria for ground motion selection. Three methods are presented to propagate the effect of seismic hazard and ground motion selection epistemic uncertainties to seismic performance metrics. These methods differ in their level of rigor considered to propagate the epistemic uncertainty in the conditional distribution of IMs utilised in ground motion selection, selected ground motion ensembles, and the number of nonlinear response history analyses performed to obtain the distribution of engineering demand parameters. These methods are compared for an example site where it is observed that, for seismic demand levels below the collapse limit, epistemic uncertainty in ground motion selection is a smaller uncertainty contributor relative to the uncertainty in the seismic hazard itself. In contrast, uncertainty in ground motion selection process increases the uncertainty in the seismic demand hazard for near-collapse demand levels.
