Deformational properties of soil, in terms of modulus and damping, exert a great influence on seismic response of soil sites. However, these properties for sands containing some portion of fines particles have not been systematically addressed. In addition, simultaneous modelling of the modulus and damping behaviour of soils during cyclic loading is desirable. This study presents an experimental and computational investigation into the deformational properties of sands containing fines content in the context of site response analysis. The experimental investigation is carried on sandy soils sourced from Christchurch, New Zealand using a dynamic triaxial apparatus while the computational aspect is based on the framework of total-stress one-dimensional (1D) cyclic behaviour of soil. The experimental investigation focused on a systematic study on the deformational behaviour of sand with different amounts of fines content (particle diameter ≤ 75µm) under drained conditions. The silty sands were prepared by mixing clean sand with three different percentages of fines content. A series of bender element tests at small-strain range and stress-controlled dynamic triaxial tests at medium to high-strain ranges were conducted on samples of clean sand and silty sand. This allowed measurements of linear and nonlinear deformational properties of the same specimen for a wide strain range. The testing program was designed to quantify the effects of void ratio and fines content on the low-strain stiffness of the silty sand as well as on the nonlinear stress-strain relationship and corresponding shear modulus and damping properties as a function of cyclic shear strains. Shear wave velocity, Vs, and maximum shear modulus, Gmax, of silty sand was shown to be significantly smaller than the respective values for clean sands measured at the same void ratio, e, or same relative density, Dr. However, the test results showed that the difference in the level of nonlinearity between clean sand and silty sands was small. For loose samples prepared at an identical relative density, the behaviour of clean sand was slightly less nonlinear as compared to sandy soils with higher fines content. This difference in the nonlinear behaviour of clean sand and sandy soils was negligible for dense soils. Furthermore, no systematic influence of fines content on the material damping curve was observed for sands with fines content FC = 0 to 30%. In order to normalize the effects of fines on moduli of sands, equivalent granular void ratio, e*, was employed. This was done through quantifying the participation of fines content in the force transfer chain of the sand matrix. As such, a unified framework for modelling of the variability of shear wave velocity, Vs, (or shear modulus, Gmax) with void ratio was achieved for clean sands and sands with fines, irrespective of their fines content. Furthermore, modelling of the cyclic stress-strain behaviour based on this experimental program was investigated. The modelling effort focused on developing a simple constitutive model which simultaneously models the soil modulus and damping relationships with shear strains observed in laboratory tests. The backbone curve of the cyclic model was adopted based on a modified version of Kondner and Zelasko (MKZ) hyperbolic function, with a curvature coefficient, a. In order to simulate the hysteretic cycles, the conventional Masing rules (Pyke 1979) were revised. The parameter n, in the Masing’s criteria was assumed to be a function of material damping, h, measured in the laboratory. As such the modulus and damping produced by the numerical model could match the stress-strain behaviour observed in the laboratory over the course of this study. It was shown that the Masing parameter n, is strain-dependent and generally takes values of n ≤ 2. The model was then verified through element test simulations under different cyclic loadings. It was shown that the model could accurately simulate the modulus and the damping simultaneously. The model was then incorporated within the OpenSees computational platform and was used to scrutinize the effects of damping on one-dimensional seismic site response analysis. For this purpose, several strong motion stations which recorded the Canterbury earthquake sequence were selected. The soil profiles were modelled as semi-infinite horizontally layered deposits overlying a uniform half-space subjected to vertically propagating shear waves. The advantages and limitations of the nonlinear model in terms of simulating soil nonlinearity and associated material damping were further scrutinized. It was shown that generally, the conventional Masing criteria unconservatively may underestimate some response parameters such as spectral accelerations. This was shown to be due to larger hysteretic damping modelled by using conventional Masing criteria. In addition, maximum shear strains within the soil profiles were also computed smaller in comparison to the values calculated by the proposed model. Further analyses were performed to study the simulation of backbone curve beyond the strain ranges addressed in the experimental phase of this study. A key issue that was identified was that relying only on the modulus reduction curves to simulate the stress-strain behaviour of soil may not capture the actual soil strength at larger strains. Hence, strength properties of the soil layer should also be incorporated to accurately simulate the backbone curve.
In this thesis, focus is given to develop methodologies for rapidly estimating specific components of loss and downtime functions. The thesis proposes methodologies for deriving loss functions by (i) considering individual component performance; (ii) grouping them as per their performance characteristics; and (iii) applying them to similar building usage categories. The degree of variation in building stock and understanding their characteristics are important factors to be considered in the loss estimation methodology and the field surveys carried out to collect data add value to the study. To facilitate developing ‘downtime’ functions, this study investigates two key components of downtime: (i) time delay from post-event damage assessment of properties; and (ii) time delay in settling the insurance claims lodged. In these two areas, this research enables understanding of critical factors that influence certain aspects of downtime and suggests approaches to quantify those factors. By scrutinising the residential damage insurance claims data provided by the Earthquake Commission (EQC) for the 2010- 2011 Canterbury Earthquake Sequence (CES), this work provides insights into various processes of claims settlement, the time taken to complete them and the EQC loss contributions to building stock in Christchurch city and Canterbury region. The study has shown diligence in investigating the EQC insurance claim data obtained from the CES to get new insights and build confidence in the models developed and the results generated. The first stage of this research develops contribution functions (probabilistic relationships between the expected losses for a wide range of building components and the building’s maximum response) for common types of claddings used in New Zealand buildings combining the probabilistic density functions (developed using the quantity of claddings measured from Christchurch buildings), fragility functions (obtained from the published literature) and cost functions (developed based on inputs from builders) through Monte Carlo simulations. From the developed contribution functions, glazing, masonry veneer, monolithic and precast concrete cladding systems are found to incur 50% loss at inter-storey drift levels equal to 0.027, 0.003, 0.005 and 0.011, respectively. Further, the maximum expected cladding loss for glazing, masonry veneer, monolithic, precast concrete cladding systems are found to be 368.2, 331.9, 365.0, and 136.2 NZD per square meter of floor area, respectively. In the second stage of this research, a detailed cost breakdown of typical buildings designed and built for different purposes is conducted. The contributions of structural and non- structural components to the total building cost are compared for buildings of different usages, and based on the similar ratios of non-structural performance group costs to the structural performance group cost, four-building groups are identified; (i) Structural components dominant group: outdoor sports, stadiums, parkings and long-span warehouses, (ii) non- structural drift-sensitive components dominant group: houses, single-storey suburban buildings (all usages), theatres/halls, workshops and clubhouses, (iii) non-structural acceleration- sensitive components dominant group: hospitals, research labs, museums and retail/cold stores, and (iv) apartments, hotels, offices, industrials, indoor sports, classrooms, devotionals and aquariums. By statistically analysing the cost breakdowns, performance group weighting factors are proposed for structural, and acceleration-sensitive and drift-sensitive non-structural components for all four building groups. Thus proposed building usage groupings and corresponding weighting factors facilitate rapid seismic loss estimation of any type of building given the EDPs at storey levels are known. A model for the quantification of post-earthquake inspection duration is developed in the third stage of this research. Herein, phase durations for the three assessment phases (one rapid impact and two rapid building) are computed using the number of buildings needing inspections, the number of engineers involved in inspections and a phase duration coefficient (which considers the median building inspection time, efficiency of engineer and the number of engineers involved in each assessment teams). The proposed model can be used: (i) by national/regional authorities to decide the length of the emergency period following a major earthquake, and estimate the number of engineers required to conduct a post-earthquake inspection within the desired emergency period, and (ii) to quantify the delay due to inspection for the downtime modelling framework. The final stage of this research investigates the repair costs and insurance claim settlement time for damaged residential buildings in the 2010-2011 Canterbury earthquake sequence. Based on the EQC claim settlement process, claims are categorized into three groups; (i) Small Claims: claims less than NZD15,000 which were settled through cash payment, (ii) Medium Claims: claims less than NZD100,000 which were managed through Canterbury Home Repair Programme (CHRP), and (iii) Large Claims: claims above NZD100,000 which were managed by an insurance provider. The regional loss ratio (RLR) for greater Christchurch for three events inducing shakings of approximate seismic intensities 6, 7, and 8 are found to be 0.013, 0.066, and 0.171, respectively. Furthermore, the claim duration (time between an event and the claim lodgement date), assessment duration (time between the claim lodgement day and the most recent assessment day), and repair duration (time between the most recent assessment day and the repair completion day) for the insured residential buildings in the region affected by the Canterbury earthquake sequence is found to be in the range of 0.5-4 weeks, 1.5- 5 months, and 1-3 years, respectively. The results of this phase will provide useful information to earthquake engineering researchers working on seismic risk/loss and insurance modelling.
Ongoing climate change triggers increasing temperature and more frequent extreme events which could limit optimal performance of haliotids, affect their physiology and biochemistry as well as influencing their population structure. Haliotids are a valuable nearshore fishery in a number of countries and many are showing a collapse of stocks because of overexploitation, environmental changes, loss of habitat, and disease. The haliotid in New Zealand commonly referred to as the blackfoot pāua (Haliotis iris) contribute a large and critical cultural, recreational and economic resource. Little was known about pāua responses to increasing temperature and acute environmental factors, as well as information about population size structure in Kaikoura after the earthquake 2016 and in Banks Peninsula. The aims of this study were to investigate the effects of temperature on scope for growth (SfG); physiological and biochemical responses of pāua subjected to different combined stressors including acute temperature, acute salinity and progressive hypoxia; and describe population size structure and shell morphology in different environments in Kaikoura and Banks Peninsula. The main findings of the present study found that population size structures of pāua were site-specific, and the shell length and shell height ratio of 3.25 could distinguish between stunted and non-stunted populations. The study found that high water temperature resulted in a reduction in absorbed energy from food, an increase in respiration energy, and ammonia excretion energy. Surveys were conducted at six study sites around the Canterbury Region over three years in order to better understand the population size structure and shell morphology of pāua. The findings found that the population size structure at 6 sites differed. Both juveniles and adults were found in intertidal areas at five sites. However, at Cape Three Points, pāua were found only in subtidal zones. One of the sites, Little Port Cooper, had a stunted population where only two pāua reached 125 mm in length over three years. In addition, most pāua in Little Port Cooper and Cape Three Points were adults, while Seal Reef had mostly juveniles. Wakatu Quay and Omihi had a full size range of pāua. Oaro population was dominated with juveniles and sub-adults. Recruitment and growth of pāua were successful after the earthquake in 2016. Research into pāua shell morphologies also determined that shell dimensions differed between sites. The relationships of shell length to shell width were linear and the relationship of shell length to shell height was curvilinear. Interestingly, SL:SH ratio of 3.25 is able to be used to identify stunted and non-stunted populations for pāua larger than 90 mm in length. Little Port Cooper was a stunted population with mean SL:SH ratio being 3.16. In the laboratory, scope for growth of pāua was investigated at four different temperatures of 12oC, 15oC, 18oC and 21oC over four weeks’ acclimation. The current study has found that SfG of pāua highly depended on temperature. Absorbed energy and respiration energy accounted for the highest proportion of the SfG of pāua. The respiration energy of pāua accounted for approximately 36%, 40%, 49% and 69% of the absorbed energy at 12°C, 15°C, 18°C and 21°C, respectively. The pāua at all acclimation temperatures had a positive scope for growth. The study suggested that the SfG was highest at 15°C, while the value at 21°C was the lowest. However, SfG at 18°C and 21°C decreased after 14 days of acclimation. Because of maintaining almost unchanged oxygen consumption over four weeks’ acclimation, pāua showed their poor abilities to acclimate to an increase in temperature. Therefore, they may be more vulnerable in future warming scenarios. The physiological and biochemical responses of pāua toward different combined stressors included three experiments. In terms of the acute temperature experiment, pāua were acclimated at 12oC, 15oC, 18oC or 21oC for two weeks before stepwise exposure to four temperatures of 12oC, 15oC, 18oC and 21oC every 4 hours. The acute salinity change, pāua were acclimated at 12oC, 15oC or 18oC over two weeks. Pāua were then exposed to a stepwise decrease of salinity of 2‰ every two hours from 34 – 22‰. Regarding the declining oxygen level, pāua were acclimated at 15 oC or 18oC for two weeks before exposure to one of four temperatures at 12oC, 15oC, 18oC or 21oC in one hour. After that acute progressive hypoxia was studied in closed respirometers for around six hours. The findings showed that there were interactions between combined stressors, affecting physiology of pāua (metabolism and heart rate). This suggests that environmental factors do not have a separate effect, but they also have interactions that enhance negative effects on pāua. Also, both oxygen uptake and heart rate responded quickly to temperature change and increased with rising temperature. On the other hand, oxygen uptake and heart rate decreased with reducing salinity and progressive hypoxia (before critical oxygen tension - Pcrit). Pcrit over four acute temperature exposures, ranged between 30.2 and 80.0 mmHg, depending on the exposure temperature. Acclimation temperature, combined with acute temperature, salinity or hypoxia stress affected the biochemistry of pāua. Pāua are osmoconformers so decreased salinity resulted in reducing haemolymph ionic concentration and increasing body volume. They were hypo-ionic with respect to sodium and potassium over the salinity ranges of 34 - 22‰. Haemocyanin accounts for a large pecentage of haemolymph protein, so trends of protein followed haemocyanin. Pāua tended to store oxygen in haemocyanin under extreme salinity stress at 22‰ and extreme hypoxia around 10 mmHg, rather than in oxygen transport. In conclusion, pāua at different sites had different population structures and morphologies. Pāua are sensitive to environmental stressors. They consumed more oxygen at high temperatures because they do not have thermal acclimation capacity. They are also osmoconformers with haemolymph sodium and potassium decreasing with salinity medium. Under progressive hypoxia, pāua could regulate oxygen and heart rate until Pcrit depending on temperature. Acute environmental changes also disturbed haemolyph parameters. 12°C and 15°C could be in the range of optimal temperature with higher SfG and less stress when exposed to acute environmental changes. Meanwhile long term exposure to 21°C is likely to be outside of the optimal range for the pāua. With ongoing climate change, pāua populations are more vulnerable so conservation is necessary. The research contributes to improving fishery management, providing insights into different environmental stressors affecting the energy demand and physiological and biochemical responses of pāua. It also allow to predicting the growth patterns and responses of pāua to adapt to climate change.
