The Screw Driving Sounding (SDS) method developed in Japan is a relatively new insitu testing technique to characterise soft shallow sites, typically those required for residential house construction. An SDS machine drills a rod into the ground in several loading steps while the rod is continuously rotated. Several parameters, such as torque, load and speed of penetration, are recorded at every rotation of the rod. The SDS method has been introduced in New Zealand, and the results of its application for characterising local sites are discussed in this study. A total of 164 SDS tests were conducted in Christchurch, Wellington and Auckland to validate/adjust the methodologies originally developed based on the Japanese practice. Most of the tests were conducted at sites where cone penetration tests (CPT), standard penetration tests (SPT) and borehole logs were available; the comparison of SDS results with existing information showed that the SDS method has great potential as an in-situ testing method for classifying the soils. By compiling the SDS data from 3 different cities and comparing them with the borehole logs, a soil classification chart was generated for identifying the soil type based on SDS parameters. Also, a correlation between fines content and SDS parameters was developed and a procedure for estimating angle of internal friction of sand using SDS parameters was investigated. Furthermore, a correlation was made between the tip resistance of the CPT and the SDS data for different percentages of fines content. The relationship between the SPT N value and a SDS parameter was also proposed. This thesis also presents a methodology for identifying the liquefiable layers of soil using SDS data. SDS tests were performed in both liquefied and non-liquefied areas in Christchurch to find a representative parameter and relationship for predicting the liquefaction potential of soil. Plots were drawn of the cyclic shear stress ratios (CSR) induced by the earthquakes and the corresponding energy of penetration during SDS tests. By identifying liquefied or unliquefied layers using three different popular CPT-based methods, boundary lines corresponding to the various probabilities of liquefaction happening were developed for different ranges of fines contents using logistic regression analysis, these could then be used for estimating the liquefaction potential of soil directly from the SDS data. Finally, the drilling process involved in screw driving sounding was simulated using Abaqus software. Analysis results proved that the model successfully captured the drilling process of the SDS machine in sand. In addition, a chart to predict peak friction angles of sandy sites based on measured SDS parameters for various vertical effective stresses was formulated. As a simple, fast and economical test, the SDS method can be a reliable alternative insitu test for soil and site characterisation, especially for residential house construction.
Abstract This study provides a simplified methodology for pre-event data collection to support a faster and more accurate seismic loss estimation. Existing pre-event data collection frameworks are reviewed. Data gathered after the Canterbury earthquake sequences are analysed to evaluate the relative importance of different sources of building damage. Conclusions drawns are used to explore new approaches to conduct pre-event building assessment.
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.
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.
Overview of SeisFinder SeisFinder is an open-source web service developed by QuakeCoRE and the University of Canterbury, focused on enabling the extraction of output data from computationally intensive earthquake resilience calculations. Currently, SeisFinder allows users to select historical or future events and retrieve ground motion simulation outputs for requested geographical locations. This data can be used as input for other resilience calculations, such as dynamic response history analysis. SeisFinder was developed using Django, a high-level python web framework, and uses a postgreSQL database. Because our large-scale computationally-intensive numerical ground motion simulations produce big data, the actual data is stored in file systems, while the metadata is stored in the database. The basic SeisFinder architecture is shown in Figure 1.
The 14 November 2016 Kaikōura earthquake had major impacts on New Zealand's transport system. Road, rail and port infrastructure was damaged, creating substantial disruption for transport operators, residents, tourists, and business owners in the Canterbury, Marlborough and Wellington regions, with knock-on consequences elsewhere. During both the response and recovery phases, a large amount of information and data relating to the transport system was generated, managed, analysed, and exchanged within and between organisations to assist decision making. To improve information and data exchanges and related decision making in the transport sector during future events and guide new resilience strategies, we present key findings from a recent post-earthquake assessment. The research involved 35 different stakeholder groups and was conducted for the Ministry of Transport. We consider what transport information was available, its usefulness, where it was sourced from, mechanisms for data transfer between organisations, and suggested approaches for continued monitoring.
Liquefaction-induced lateral spreading during the 2011 Christchurch earthquake in New Zealand was severe and extensive, and data regarding the displacements associated with the lateral spreading provides an excellent opportunity to better understand the factors that influence these movements. Horizontal displacements measured from optical satellite imagery and subsurface data from the New Zealand Geotechnical Database (NZGD) were used to investigate four distinct lateral spread areas along the Avon River in Christchurch. These areas experienced displacements between 0.5 and 2 m, with the inland extent of displacement ranging from 100 m to over 600 m. Existing empirical and semi-empirical displacement models tend to under estimate displacements at some sites and over estimate at others. The integrated datasets indicate that the areas with more severe and spatially extensive displacements are associated with thicker and more laterally continuous deposits of liquefiable soil. In some areas, the inland extent of displacements is constrained by geologic boundaries and geomorphic features, as expressed by distinct topographic breaks. In other areas the extent of displacement is influenced by the continuity of liquefiable strata or by the presence of layers that may act as vertical seepage barriers. These observations demonstrate the need to integrate geologic/geomorphic analyses with geotechnical analyses when assessing the potential for lateral spreading movements.
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.
Micro - electro - mechanical system (MEMS) based accelerometers are now frequently used in many different parts of our day - to - day lives. It is also increasingly being used for structural testing applications. Researchers have had res ervation of using these devices as they are relatively untested, but now with the wider adoption, it provides a much cheaper and more versatile tool for structural engineering researchers. A number of damaged buildings in the Christchurch Central Business District (CBD) were instrumented with a number of low - cost MEMS accelerometers after the major Christchurch earthquakes. The accelerometers captured extremely high quality building response data as the buildings experienced thousands of aftershocks. This d ata set was amongst one of only a handful of data set s available around the world which provides building response data subjected to real ground motion. Furthermore, due to technological advances, a much larger than usual number of accelerometers has been deployed making the data set one of the most comprehensive available. This data set is utilised to extract modal parameters of the buildings. This paper summarises the operating requirements and preference for using such accelerometers for experimental mod al analysis. The challenges for adapting MEMS based devices for successful modal parameters identification are also discussed.
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.
We present the initial findings from a study of adaptive resilience of lifelines organisations providing essential infrastructure services, in Christchurch, New Zealand following the earthquakes of 2010-2011. Qualitative empirical data was collected from 200 individuals in 11 organisations. Analysis using a grounded theory method identified four major factors that aid organisational response, recovery and renewal following major disruptive events. Our data suggest that quality of top and middle-level leadership, quality of external linkages, level of internal collaboration, ability to learn from experience, and staff well-being and engagement influence adaptive resilience. Our data also suggest that adaptive resilience is a process or capacity, not an outcome and that it is contextual. Post-disaster capacity/resources and post-disaster environment influence the nature of adaptive resilience.
Natural catastrophes are increasing worldwide. They are becoming more frequent but also more severe and impactful on our built environment leading to extensive damage and losses. Earthquake events account for the smallest part of natural events; nevertheless seismic damage led to the most fatalities and significant losses over the period 1981-2016 (Munich Re). Damage prediction is helpful for emergency management and the development of earthquake risk mitigation projects. Recent design efforts focused on the application of performance-based design engineering where damage estimation methodologies use fragility and vulnerability functions. However, the approach does not explicitly specify the essential criteria leading to economic losses. There is thus a need for an improved methodology that finds the critical building elements related to significant losses. The here presented methodology uses data science techniques to identify key building features that contribute to the bulk of losses. It uses empirical data collected on site during earthquake reconnaissance mission to train a machine learning model that can further be used for the estimation of building damage post-earthquake. The first model is developed for Christchurch. Empirical building damage data from the 2010-2011 earthquake events is analysed to find the building features that contributed the most to damage. Once processed, the data is used to train a machine-learning model that can be applied to estimate losses in future earthquake events.
This article argues that teachers deserve more recognition for their roles as first responders in the immediate aftermath of a disaster and for the significant role they play in supporting students and their families through post-disaster recovery. The data are drawn from a larger study, 'Christchurch Schools Tell Their Earthquake Stories' funded by the United Nations Educational, Scientific and Cultural Organisation and the University of Auckland, in which schools were invited to record their earthquake stories for themselves and for historical archives. Data were gathered from five primary schools between 2012 and 2014. Methods concerned mainly semi-structured individual or group interviews and which were analysed thematically. The approach was sensitive, flexible and participatory with each school being able to choose its focus, participants and outcome. Participants from each school generally included the principal and a selection of teachers, students and parents. In this study, the data relating to the roles of teachers were separated out for closer analysis. The findings are presented as four themes: immediate response; returning to (new) normal; care and support; and long term effects.
After the Christchurch earthquakes, the government declared about 8000 houses as Red Zoned, prohibiting further developments in these properties, and offering the owners to buy them out. The government provided two options for owners: the first was full payment for both land and dwelling at the 2007 property evaluation, the second was payment for land, and the rest to be paid by the owner’s insurance. Most people chose the second option. Using data from LINZ combined with data from StatNZ, this project empirically investigates what led people to choose this second option, and what were the implications of these choices for the owners’ wealth and income.
Semi-empirical models based on in-situ geotechnical tests have become the standard of practice for predicting soil liquefaction. Since the inception of the “simplified” cyclic-stress model in 1971, variants based on various in-situ tests have been developed, including the Cone Penetration Test (CPT). More recently, prediction models based soley on remotely-sensed data were developed. Similar to systems that provide automated content on earthquake impacts, these “geospatial” models aim to predict liquefaction for rapid response and loss estimation using readily-available data. This data includes (i) common ground-motion intensity measures (e.g., PGA), which can either be provided in near-real-time following an earthquake, or predicted for a future event; and (ii) geospatial parameters derived from digital elevation models, which are used to infer characteristics of the subsurface relevent to liquefaction. However, the predictive capabilities of geospatial and geotechnical models have not been directly compared, which could elucidate techniques for improving the geospatial models, and which would provide a baseline for measuring improvements. Accordingly, this study assesses the realtive efficacy of liquefaction models based on geospatial vs. CPT data using 9,908 case-studies from the 2010-2016 Canterbury earthquakes. While the top-performing models are CPT-based, the geospatial models perform relatively well given their simplicity and low cost. Although further research is needed (e.g., to improve upon the performance of current models), the findings of this study suggest that geospatial models have the potential to provide valuable first-order predictions of liquefaction occurence and consequence. Towards this end, performance assessments of geospatial vs. geotechnical models are ongoing for more than 20 additional global earthquakes.
Quick and reliable assessment of the condition of bridges in a transportation network after an earthquake can greatly assist immediate post-disaster response and long-term recovery. However, experience shows that available resources, such as qualified inspectors and engineers, will typically be stretched for such tasks. Structural health monitoring (SHM) systems can therefore make a real difference in this context. SHM, however, needs to be deployed in a strategic manner and integrated into the overall disaster response plans and actions to maximize its benefits. This study presents, in its first part, a framework of how this can be achieved. Since it will not be feasible, or indeed necessary, to use SHM on every bridge, it is necessary to prioritize bridges within individual networks for SHM deployment. A methodology for such prioritization based on structural and geotechnical seismic risks affecting bridges and their importance within a network is proposed in the second part. An example using the methodology application to selected bridges in the medium-sized transportation network of Wellington, New Zealand is provided. The third part of the paper is concerned with using monitoring data for quick assessment of bridge condition and damage after an earthquake. Depending on the bridge risk profile, it is envisaged that data will be obtained from either local or national seismic monitoring arrays or SHM systems installed on bridges. A method using artificial neural networks is proposed for using data from a seismic array to infer key ground motion parameters at an arbitrary bridges site. The methodology is applied to seismic data collected in Christchurch, New Zealand. Finally, how such ground motion parameters can be used in bridge damage and condition assessment is outlined. AM - Accepted manuscript
The University of Canterbury is known internationally for the Origins of New Zealand English (ONZE) corpus (see Gordon et al 2004). ONZE is a large collection of recordings from people born between 1851 and 1984, and it has been widely utilised for linguistic and sociolinguistic research on New Zealand English. The ONZE data is varied. The recordings from the Mobile Unit (MU) are interviews and were collected by members of the NZ Broadcasting service shortly after the Second World War, with the aim of recording stories from New Zealanders outside the main city centres. These were supplemented by interview recordings carried out mainly in the 1990s and now contained in the Intermediate Archive (IA). The final ONZE collection, the Canterbury Corpus, is a set of interviews and word-list recordings carried out by students at the University of Canterbury. Across the ONZE corpora, there are different interviewers, different interview styles and a myriad of different topics discussed. In this paper, we introduce a new corpus – the QuakeBox – where these contexts are much more consistent and comparable across speakers. The QuakeBox is a corpus which consists largely of audio and video recordings of monologues about the 2010-2011 Canterbury earthquakes. As such, it represents Canterbury speakers’ very recent ‘danger of death’ experiences (see Labov 2013). In this paper, we outline the creation and structure of the corpus, including the practical issues involved in storing the data and gaining speakers’ informed consent for their audio and video data to be included.
Nowadays the telecommunication systems’ performance has a substantial impact on our lifestyle. Their operationality becomes even more substantial in a post-disaster scenario when these services are used in civil protection and emergency plans, as well as for the restoration of all the other critical infrastructure. Despite the relevance of loss of functionality of telecommunication networks on seismic resilience, studies on their performance assessment are few in the literature. The telecommunication system is a distributed network made up of several components (i.e. ducts, utility holes, cabinets, major and local exchanges). Given that these networks cover a large geographical area, they can be easily subjected to the effects of a seismic event, either the ground shaking itself, or co-seismic events such as liquefaction and landslides. In this paper, an analysis of the data collected after the 2010-2011 Canterbury Earthquake Sequence (CES) and the 2016 Kaikoura Earthquake in New Zealand is conducted. Analysing these data, information gaps are critically identified regarding physical and functional failures of the telecommunication components, the timeline of repair/reconstruction activities and service recovery, geotechnical tests and land planning maps. Indeed, if these missing data were presented, they could aid the assessment of the seismic resilience. Thus, practical improvements in the post-disaster collection from both a network and organisational viewpoints are proposed through consultation of national and international researchers and highly experienced asset managers from Chorus. Finally, an outline of future studies which could guide towards a more resilient seismic performance of the telecommunication network is presented.
The operation of telecommunication networks is critical during business as usual times, and becomes most vital in post-disaster scenarios, when the services are most needed for restoring other critical lifelines, due to inherent interdependencies, and for supporting emergency and relief management tasks. In spite of the recognized critical importance, the assessment of the seismic performance for the telecommunication infrastructure appears to be underrepresented in the literature. The FP6 QuakeCoRE project “Performance of the Telecommunication Network during the Canterbury Earthquake Sequence” will provide a critical contribution to bridge this gap. Thanks to an unprecedented collaboration between national and international researchers and highly experienced asset managers from Chorus, data and evidences on the physical and functional performance of the telecommunication network after the Canterbury Earthquakes 2010-2011 have been collected and collated. The data will be processed and interpreted aiming to reveal fragilities and resilience of the telecommunication networks to seismic events
The 2010-2011 Canterbury earthquake sequence, and the resulting extensive data sets on damaged buildings that have been collected, provide a unique opportunity to exercise and evaluate previously published seismic performance assessment procedures. This poster provides an overview of the authors’ methodology to perform evaluations with two such assessment procedures, namely the P-58 guidelines and the REDi Rating System. P-58, produced by the Federal Emergency Management Agency (FEMA) in the United States, aims to facilitate risk assessment and decision-making by quantifying earthquake ground shaking, structural demands, component damage and resulting consequences in a logical framework. The REDi framework, developed by the engineering firm ARUP, aids stakeholders in implementing resilience-based earthquake design. Preliminary results from the evaluations are presented. These have the potential to provide insights on the ability of the assessment procedures to predict impacts using “real-world” data. However, further work remains to critically analyse these results and to broaden the scope of buildings studied and of impacts predicted.
The Global Earthquake Model’s (GEM) Earthquake Consequences Database (GEMECD) aims to develop, for the first time, a standardised framework for collecting and collating geocoded consequence data induced by primary and secondary seismic hazards to different types of buildings, critical facilities, infrastructure and population, and relate this data to estimated ground motion intensity via the USGS ShakeMap Atlas. New Zealand is a partner of the GEMECD consortium and to-date has contributed with 7 events to the database, of which 4 are localised in the South Pacific area (Newcastle 1989; Luzon 1990; South of Java 2006 and Samoa Islands 2009) and 3 are NZ-specific events (Edgecumbe 1987; Darfield 2010 and Christchurch 2011). This contribution to GEMECD represented a unique opportunity for collating, comparing and reviewing existing damage datasets and harmonising them into a common, openly accessible and standardised database, from where the seismic performance of New Zealand buildings can be comparatively assessed. This paper firstly provides an overview of the GEMECD database structure, including taxonomies and guidelines to collect and report on earthquake-induced consequence data. Secondly, the paper presents a summary of the studies implemented for the 7 events, with particular focus on the Darfield (2010) and Christchurch (2011) earthquakes. Finally, examples of specific outcomes and potentials for NZ from using and processing GEMECD are presented, including: 1) the rationale for adopting the GEM taxonomy in NZ and any need for introducing NZ-specific attributes; 2) a complete overview of the building typological distribution in the Christchurch CBD prior to the Canterbury earthquakes and 3) some initial correlations between the level and extent of earthquake-induced physical damage to buildings, building safety/accessibility issues and the induced human casualties.
Following the 22 February 2011 Christchurch earthquake a comprehensive damage survey of the unreinforced masonry (URM) building stock of Christchurch city, New Zealand was undertaken. Because of the large number of aftershocks associated with both the 2011 Christchurch earthquake and the earlier 4 September 2010 Darfield earthquake, and the close proximity of their epicentres to Christchurch city, this earthquake sequence presented a unique opportunity to assess the performance of URM buildings and the various strengthening methods used in New Zealand to increase the performance of these buildings in earthquakes. Because of the extent of data that was collected, a decision was made to initially focus exclusively on the earthquake performance of URM buildings located in the central business district (CBD) of Christchurch city. The main objectives of the data collection exercise were to document building characteristics and any seismic strengthening methods encountered, and correlate these attributes with observed earthquake damage. In total 370 URM buildings in the CBD were surveyed. Of the surveyed buildings, 62% of all URM buildings had received some form of earthquake strengthening and there was clear evidence that installed earthquake strengthening techniques in general had led to reduced damage levels. The procedure used to collect and process information associated with earthquake damage, general analysis and interpretation of the available survey data for the 370 URM buildings, the performance of earthquake strengthening techniques, and the influence of earthquake strengthening levels on observed damage are reported within. http://15ibmac.com/home/
During many years the analysis of some geophysical results of Charles Darwin was being carried out in Department. Darwin has connected almost 200 years ago results of catastrophic earthquakes with vertical movement of a surface of the Earth. Usually this movement less horizontal movement and its influence on destruction of cities is not considered. Earthquake hazard assessment studies were focused usually on the horizontal ground motion. Effects of the strong vertical motion were not, practically, discussed. The margins of safety against gravity-induced static vertical forces in constructed buildings usually provide adequate resistance to dynamic forces induced by the vertical acceleration during an earthquake. However, the earthquake in Christchurch is an example of the vertical seismic shock . The earthquake magnitude was rather small - nearby 6.3. However, the result was catastrophic. The same took place in 1835. It allowed to Darwin to formulate a few great ideas. Charles Darwin has explained qualitatively results of an interaction of huge seismic waves with volcanoes and the nature of volcanism and seismicity of our planet. These important data of Charles Darwin became very actual recently. It is possible to tell also the same about tsunami and extreme ocean waves described by Charles Darwin. Therefore this data were analyzed using modern mechanics, mathematics and physics in Department. In particular, the theory of catastrophic waves was developed based on Darwin's data. The theory tried to explain occurrence, evolution and distribution the catastrophic waves in various natural systems, since atoms, oceans, surfaces of the Earth and up to the very early Universe. Some results of the research were published in prestigious magazines. Later they were presented in two books devoted to Charles Darwin's anniversary (2009). Last from them was published in Russian (2011). We give here key ideas of this research which is a part of interdisciplinary researches of Department. Some ideas are discussed. Not less important purpose is very short historical review of some researches of Darwin. In particular, we underline Darwin' priority in the formulation of the bases of Dynamics Earth.
Following the devastation of the Canterbury earthquake sequence a unique opportunity exists to rebuild and restructure the city of Christchurch, ensuring that its infrastructure is constructed better than before and is innovative. By installing an integrated grid of modern sensor technologies into concrete structures during the rebuild of the Christchurch CBD, the aim is to develop a network of self-monitored ‘digital buildings’. A diverse range of data will be recorded, potentially including parameters such as concrete stresses, strains, thermal deformations, acoustics and the monitoring of corrosion of reinforcement bars. This procedure will allow an on-going complete assessment of the structure’s performance and service life, both before and after seismic activity. The data generated from the embedded and surface mounted sensors will be analysed to allow an innovative and real-time health monitoring solution where structural integrity is continuously known. This indication of building performance will allow the structure to alert owners, engineers and asset managers of developing problems prior to failure thresholds being reached. A range of potential sensor technologies for monitoring the performance of existing and newly constructed concrete buildings is discussed. A description of monitoring work conducted on existing buildings during the July 2013 Cook Strait earthquake sequence is included, along with details of current work that investigates the performance of sensing technologies for detecting crack formation in concrete specimens. The potential market for managing the real-time health of installed infrastructure is huge. Civil structures all over the world require regular visual inspections in order to determine their structural integrity. The information recorded during the Christchurch rebuild will generate crucial data sets that will be beneficial in understanding the behaviour of concrete over the complete life cycle of the structure, from construction through to operation and building repairs until the time of failure. VoR - Version of Record
It is well known that buildings constructed using unreinforced masonry (URM) are susceptible to damage from earthquake induced lateral forces that may result in partial or full building collapse. The 2010/2011 Canterbury earthquakes are the most recent New Zealand example of destructive earthquakes, which have drawn people's attention to the inherent seismic weaknesses of URM buildings and anchored masonry veneer systems in New Zealand. A brief review of the data collected following the 2010 Darfield earthquake and more comprehensive documentation of data that was collected following the 2011 Christchurch earthquake is presented, along with the findings from subsequent data interrogation. Large stocks of earthquake prone vintage URM buildings that remain in New Zealand and in other seismically active parts of the world result in the need for minimally invasive and cost effective seismic retrofit techniques. The principal objective of the doctoral research reported herein was to investigate the applicability of near surface mounted (NSM) carbon fibre reinforced polymer (CFRP) strips as a seismic improvement technique. A comprehensive experimental program consisting of 53 pull tests is presented and is used to assess the accuracy of existing FRP-to-masonry bond models, with a modified model being proposed. The strength characteristics of vintage clay brick URM wall panels from two existing URM buildings was established and used as a benchmark when manufacturing replica clay brick test assemblages. The applicability of using NSM CFRP strips as a retrofitting technique for improving the shear strength and the ductility capacity of multi-leaf URM walls constructed using solid clay brick masonry is investigated by varying CFRP reinforcement ratios. Lastly, an experimental program was undertaken to validate the proposed design methodology for improving the strength capacity of URM walls. The program involved testing full-scale walls in a laboratory setting and testing full-scale walls in-situ in existing vintage URM buildings. Experimental test results illustrated that the NSM CFRP technique is an effective method to seismically strengthen URM buildings.
Disasters, either man-made or natural, are characterised by a multiplicity of factors including loss of property, life, environmental degradation, and psychosocial malfunction of the affected community. Although much research has been undertaken on proactive disaster management to help reduce the impacts of natural and man-made disasters, many challenges still remain. In particular, the desire to re-house the affected as quickly as possible can affect long-term recovery if a considered approach is not adopted. Promoting recovery activities, coordination, and information sharing at national and international levels are crucial to avoid duplication. Mannakkara and Wilkinson’s (2014) modified “Build Back Better” (BBB) concept aims for better resilience by incorporating key resilience elements in post-disaster restoration. This research conducted an investigation into the effectiveness of BBB in the recovery process after the 2010–2011 earthquakes in greater Christchurch, New Zealand. The BBB’s impact was assessed in terms of its five key components: built environment, natural environment, social environment, economic environment, and implementation process. This research identified how the modified BBB propositions can assist in disaster risk reduction in the future, and used both qualitative and quantitative data from both the Christchurch and Waimakariri recovery processes. Semi-structured interviews were conducted with key officials from the Christchurch Earthquake Recovery Authority, and city councils, and supplemented by reviewing of the relevant literature. Collecting data from both qualitative and quantitative sources enabled triangulation of the data. The interviewees had directly participated in all phases of the recovery, which helped the researcher gain a clear understanding of the recovery process. The findings led to the identification of best practices from the Christchurch and Waimakariri recovery processes and underlined the effectiveness of the BBB approach for all recovery efforts. This study contributed an assessment tool to aid the measurement of resilience achieved through BBB indicators. This tool provides systematic and structured approach to measure the performance of ongoing recovery.
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
This research aims to explore how business models of SMEs revolve in the face of a crisis to be resilient. The business model canvas was used as a tool to analyse business models of SMEs in Greater Christchurch. The purpose was to evaluate the changes SMEs brought in their business models after hit by a series of earthquake in 2010 and 2011. The idea was to conduct interviews of business owners and analyse using grounded theory methods. Because this method is iterative, a tentative theoretical framework was proposed, half way through the data collection. It was realised that owner specific characteristics were more prominent in the data than the elements business model. Although, SMEs in this study experienced several operational changes in their business models such as change of location and modification of payment terms. However, the suggested framework highlights how owner specific attributes influence the survival of a small business. Small businesses and their owners are extremely interrelated that the business models personify the owner specific characteristics. In other words, the adaptation of the business model reflects the extent to which the owner possess these attributes. These attributes are (a) Mindsets – the attitude and optimism of business owner; (b) Adaptive coping – the ability of business owner to take corrective actions; and (c) Social capital – the network of a business owner, including family, friends, neighbours and business partners.
Unreinforced masonry churches in New Zealand, similarly to everywhere else in the word have proven to be highly vulnerable to earthquakes, because of their particular construction features. The Canterbury (New Zealand) earthquake sequence, 2010-2011 caused an invaluable loss of local architectural heritage and of churches, as regrettably, some of them were demolished instead of being repaired. It is critical for New Zealand to advance the data collection, research and understanding pertaining to the seismic performance and protection of church buildings, with the aim to:
Unreinforced masonry (URM) cavity-wall construction is a form of masonry where two leaves of clay brick masonry are separated by a continuous air cavity and are interconnected using some form of tie system. A brief historical introduction is followed by details of a survey undertaken to determine the prevalence of URM cavity-wall buildings in New Zealand. Following the 2010/2011 Canterbury earthquakes it was observed that URM cavity-walls generally suffered irreparable damage due to a lack of effective wall restraint and deficient cavity-tie connections, combined with weak mortar strength. It was found that the original cavity-ties were typically corroded due to moisture ingress, resulting in decreased lateral loadbearing capacity of the cavity-walls. Using photographic data pertaining to Christchurch URM buildings that were obtained during post-earthquake reconnaissance, 252 cavity-walls were identified and utilised to study typical construction details and seismic performance. The majority (72%, 182) of the observed damage to URM cavity-wall construction was a result of out-of-plane type wall failures. Three types of out-of-plane wall failure were recognised: (1) overturning response, (2) one-way bending, and (3) two-way bending. In-plane damage was less widely observed (28%) and commonly included diagonal shear cracking through mortar bed joints or bricks. The collected data was used to develop an overview of the most commonly-encountered construction details and to identify typical deficiencies in earthquake response that can be addressed via the selection and implementation of appropriate mitigation interventions. http://www.journals.elsevier.com/structures
