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Research papers, University of Canterbury Library

Research following the 2010-2011 Canterbury earthquakes investigated the minimum vertical reinforcement required in RC walls to generate well distributed cracking in the plastic hinge region. However, the influence of the loading sequence and rate has not been fully addressed. The new minimum vertical reinforcement limits in NZS 3101:2006 (Amendment 3) include consideration of the material strengths under dynamic load rates, but these provisions have not been validated at a member or system level. A series of tests were conducted on RC prisms to investigate the effect of loading rate and sequence on the local behaviour of RC members. Fifteen axially loaded RC prisms with the designs representing the end region of RC walls were tested under various loading rates to cover the range of pseudo-static and earthquake loading scenarios. These tests will provide substantial data for understanding the local behaviour of RC members, including hysteretic load-deformation behaviour, crack patterns, failure mode, steel strain, strain rate and ductility. Recommendations will be made regarding the effect of loading rate and reinforcement content on the cracking behaviour and ductility of RC members.

Research papers, University of Canterbury Library

We measure the longer-term effect of a major earthquake on the local economy, using night-time light intensity measured from space, and investigate whether insurance claim payments for damaged residential property affected the local recovery process. We focus on the destructive Canterbury Earthquake Sequence (CES) 2010 -2011 as our case study. Uniquely for this event, more than 95% of residential housing units were covered by insurance, but insurance payments were staggered over 5 years, enabling us to identify their local impact. We find that night-time luminosity can capture the process of recovery and describe the recovery’s determinants. We also find that insurance payments contributed significantly to the process of economic recovery after the earthquake, but delayed payments were less affective and cash settlement of claims were more effective than insurance-managed repairs in contributing to local recovery.

Research papers, University of Canterbury Library

Knowing how to rapidly rebuild disaster-damaged infrastructure, while deciding appropriate recovery strategies and catering for future investment is a matter of core interest to government decision makers, utility providers, and business sectors. The purpose of this research is to explore the effects of decisions and outcomes for physical reconstruction on the overall recovery process of horizontal infrastructure in New Zealand using the Canterbury and Kaikoura earthquakes as cases. A mixed approach including a systematic review, questionnaire survey and semi-structured interviews is used to capture perspectives of those involved in reconstruction process and gain insights into the effect of critical elements on infrastructure downtime. Findings from this research will contribute towards advancements of a systems dynamics model considering critical decision-making variables across phases of the reconstruction process to assess how these variables affect the rebuild process and the corresponding downtime. This project will improve the ability to explore alternative resilience improvement pathways and test the efficacy of alternative means for facilitating a faster and better reconstruction process.

Research papers, University of Canterbury Library

The Canterbury Earthquake Sequence 2010-2011 (CES) induced widespread liquefaction in many parts of Christchurch city. Liquefaction was more commonly observed in the eastern suburbs and along the Avon River where the soils were characterised by thick sandy deposits with a shallow water table. On the other hand, suburbs to the north, west and south of the CBD (e.g. Riccarton, Papanui) exhibited less severe to no liquefaction. These soils were more commonly characterised by inter-layered liquefiable and non-liquefiable deposits. As part of a related large-scale study of the performance of Christchurch soils during the CES, detailed borehole data including CPT, Vs and Vp have been collected for 55 sites in Christchurch. For this subset of Christchurch sites, predictions of liquefaction triggering using the simplified method (Boulanger & Idriss, 2014) indicated that liquefaction was over-predicted for 94% of sites that did not manifest liquefaction during the CES, and under-predicted for 50% of sites that did manifest liquefaction. The focus of this study was to investigate these discrepancies between prediction and observation. To assess if these discrepancies were due to soil-layer interaction and to determine the effect that soil stratification has on the develop-ment of liquefaction and the system response of soil deposits.

Research papers, University of Canterbury Library

During the 2011 M7.8 Kaikōura earthquake, ground motions recorded near the epicentre showed a significant spatial variation. The Te Mara farm (WTMC) station, the nearest to the epicentre, recorded 1g and 2.7g of horizontal and vertical peak ground accelerations (PGA), respectively. The nearby Waiu Gorge (WIGC) station recorded a horizontal PGA of 0.8g. Interestingly, however, the Culverden Airlie Farm (CULC) station that was very closely located to WIGC recorded a horizontal PGA of only 0.25g. This poster demonstrates how the local geological condition could have contributed to the spatially variable ground motions observed in the North Canterbury, based on the results of recently conducted geophysical investigations. The surficial geology of this area is dominated by alluvial gravel deposits with traces of silt. A borehole log showed that the thickness of the sediments at WTMC is over 76 metres. Interestingly, the shear wave velocity (Vs) profiles obtained from the three strong motion sites suggest unusually high shear wave velocity of the gravelly sediments. The velocity of sediments and the lack of clear peaks in the horizontal-to-vertical (H/V) spectral ratio at WTMC suggest that the large ground motion observed at this station was likely caused by the proximity of the station to the causative fault itself; the site effect was likely insignificant. Comparisons of H/V spectral ratios and Vs profiles suggest that the sediment thickness is much smaller at WIGC compared with CULC; the high PGA at WIGC was likely influenced by the high-frequency amplification caused by the response of shallow sediments.

Research papers, University of Canterbury Library

Despite the relatively low seismicity, a large earthquake in the Waikato region is expected to have a high impact, when the fourth-largest regional population and economy and the high density critical infrastructure systems in this region are considered. Furthermore, Waikato has a deep soft sedimentary basin, which increases the regional seismic hazard due to trapping and amplification of seismic waves and generation of localized surface waves within the basin. This phenomenon is known as the “Basin Effect”, and has been attributed to the increased damage in several historic earthquakes, including the 2010-2011 Canterbury earthquakes. In order to quantitatively model the basin response and improve the understanding of regional seismic hazard, geophysical methods will be used to develop shear wave velocity profiles across the Waikato basin. Active surface wave methods involve the deployment of linear arrays of geophones to record the surface waves generated by a sledge hammer. Passive surface wave methods involve the deployment of two-dimensional seismometer arrays to record ambient vibrations. At each site, the planned testing includes one active test and two to four passive arrays. The obtained data are processed to develop dispersion curves, which describe surface wave propagation velocity as a function of frequency (or wavelength). Dispersion curves are then inverted using the Geopsy software package to develop a suite of shear wave velocity profiles. Currently, more than ten sites in Waikato are under consideration for this project. This poster presents the preliminary results from the two sites that have been tested. The shear wave velocity profiles from all sites will be used to produce a 3D velocity model for the Waikato basin, a part of QuakeCoRE flagship programme 1.

Research papers, University of Canterbury Library

Geospatial liquefaction models aim to predict liquefaction using data that is free and readily-available. This data includes (i) common ground-motion intensity measures; and (ii) geospatial parameters (e.g., among many, distance to rivers, distance to coast, and Vs30 estimated from topography) which are used to infer characteristics of the subsurface without in-situ testing. Since their recent inception, such models have been used to predict geohazard impacts throughout New Zealand (e.g., in conjunction with regional ground-motion simulations). While past studies have demonstrated that geospatial liquefaction-models show great promise, the resolution and accuracy of the geospatial data underlying these models is notably poor. As an example, mapped rivers and coastlines often plot hundreds of meters from their actual locations. This stems from the fact that geospatial models aim to rapidly predict liquefaction anywhere in the world and thus utilize the lowest common denominator of available geospatial data, even though higher quality data is often available (e.g., in New Zealand). Accordingly, this study investigates whether the performance of geospatial models can be improved using higher-quality input data. This analysis is performed using (i) 15,101 liquefaction case studies compiled from the 2010-2016 Canterbury Earthquakes; and (ii) geospatial data readily available in New Zealand. In particular, we utilize alternative, higher-quality data to estimate: locations of rivers and streams; location of coastline; depth to ground water; Vs30; and PGV. Most notably, a region-specific Vs30 model improves performance (Figs. 3-4), while other data variants generally have little-to-no effect, even when the “standard” and “high-quality” values differ significantly (Fig. 2). This finding is consistent with the greater sensitivity of geospatial models to Vs30, relative to any other input (Fig. 5), and has implications for modeling in locales worldwide where high quality geospatial data is available.