Predicting building collapse due to seismic motion is critical in design and more so after a major event. Damaged structures can appear sound, but collapse under following major events. There can thus be significant risk in decision making after a major seismic event concerning the safe occupation of a building or surrounding areas, versus the unknown impact of unknown major aftershocks. Model-based pushover analyses are effective if the structural properties are well understood, which is not valid post-event when this risk information is most useful. This research combines Hysteresis Loop Analysis (HLA) structural health monitoring (SHM) and Incremental Dynamic Analysis (IDA) methods to determine collapse capacity and probability of collapse for a specific structure, at any time, a range of earthquake excitations to ensure robustness. The nonlinear dynamic analysis method presented enables constant updating of building performance predictions using post-event SHM results. The resulting combined methods provide near real-time updating of collapse fragility curves as events progress, quantifying the change of collapse probability or seismic induced losses for decision-making - a novel, higher resolution risk analysis than previously available. The methods are not computationally expensive and there is no requirement for a validated numerical model. Results show significant potential benefits and a clear evolution of risk. They also show clear need for extending SHM toward creating improved predictive models for analysis of subsequent events, where the Christchurch series of 2010-2011 had significant post-event aftershocks after each main event. Finally, the overall method is generalisable to any typical engineering demand parameter.
Recent earthquakes in New Zealand proved that a shift is necessary in the current design practice of structures to achieve better seismic performance. Following such events, the number of new buildings using innovative technical solutions (e.g. base isolation, controlled rocking systems, damping devices, etc.), has increased, especially in Christchurch. However, the application of these innovative technologies is often restricted to medium-high rise buildings due to the maximum benefit to cost ratio. In this context, to address this issue, a multi-disciplinary geo-structural-environmental engineering project funded by the Ministry of Business Innovation and Employment (MBIE) is being carried out at the University of Canterbury. The project aims at developing a foundation system which will improve the seismic performance of medium-density low-rise buildings. Such foundation is characterized by two main elements: 1) granulated tyre rubber mixed with gravelly soils to be placed beneath the structure, with the goal of damping part of the seismic energy before it reaches the superstructure; and 2) a basement raft made of steel-fibre rubberised concrete to enhance the flexibility of the foundation under differential displacement demand. In the first part of this paper, the overarching objectives, scope and methodology of the project will be briefly described. Then, preliminary findings on the materials characterization, i.e., the gravel-rubber mixtures and steel-fibre rubberised concrete mixes, will be presented and discussed with focus on the mechanical behaviour.
One of the failure modes that got the attention of researchers in the 2011 February New Zealand earthquake was the collapse of a key supporting structural wall of Grand Chancellor Hotel in Christchurch which failed in a brittle manner. However, until now this failure mode has been still a bit of a mystery for the researchers in the field of structural engineering. Moreover, there is no method to identify, assess and design the walls prone to such failure mode. Following the recent break through regarding the mechanism of this failure mode based on experimental observations (out-of-plane shear failure), a numerical model that can capture this failure was developed using the FE software DIANA. A comprehensive numerical parametric study was conducted to identify the key parameters contributing to the development of out-of-plane shear failure in reinforced concrete (RC) walls. Based on the earthquake observations, experimental and numerical studies conducted by the authors of this paper, an analytical method to identify walls prone to out-of-plane shear failure that can be used in practice by engineers is proposed. The method is developed based on the key parameters affecting the seismic performance of RC walls prone to out-of-plane shear failure and can be used for both design and assessment purposes
Welcome to the Recover newsletter Issue 4 from the Marine Ecology Research Group (MERG) of the University of Canterbury. Recover is designed to keep you updated on our MBIE-funded earthquake recovery project called RECOVER (Reef Ecology, Coastal Values & Earthquake Recovery). This 4th instalment covers recent work on seaweed recovery in the subtidal zone, ecological engineering in Waikoau / Lyell Creek, and a sneak preview of drone survey results!
This dissertation addresses a diverse range of topics in the physics-based broadband ground motion simulation, with a focus on New Zealand applications. In particular the following topics are addressed: the methodology and computational implementation of a New Zealand Velocity Model for broadband ground motion simulation; generalised parametric functions and spatial correlations for seismic velocities in the Canterbury, New Zealand region from surface-wave-based site characterisation; and ground motion simulations of Hope Fault earthquakes. The paragraphs below outline each contribution in more detail. A necessary component in physics-based ground motion simulation is a 3D model which details the seismic velocities in the region of interest. Here a velocity model construction methodology, its computational implementation, and application in the construction of a New Zealand velocity model for use in physics-based broadband ground motion simulation are presented. The methodology utilises multiple datasets spanning different length scales, which is enabled via the use of modular sub-regions, geologic surfaces, and parametric representations of crustal velocity. A number of efficiency-related workflows to decrease the overall computational construction time are employed, while maintaining the flexibility and extensibility to incorporate additional datasets and re- fined velocity parameterizations as they become available. The model comprises explicit representations of the Canterbury, Wellington, Nelson-Tasman, Kaikoura, Marlborough, Waiau, Hanmer and Cheviot sedimentary basins embedded within a regional travel-time tomography-based velocity model for the shallow crust and provides the means to conduct ground motion simulations throughout New Zealand for the first time. Recently developed deep shear-wave velocity profiles in Canterbury enabled models that better characterise the velocity structure within geologic layers of the Canterbury sedimentary basin to be developed. Here the development of depth- and Vs30-dependent para-metric velocity and spatial correlation models to characterise shear-wave velocities within the geologic layers of the Canterbury sedimentary basin are presented. The models utilise data from 22 shear-wave velocity profiles of up to 2.5km depth (derived from surface wave analysis) juxtaposed with models which detail the three-dimensional structure of the geologic formations in the Canterbury sedimentary basin. Parametric velocity equations are presented for Fine Grained Sediments, Gravels, and Tertiary layer groupings. Spatial correlations were developed and applied to generate three-dimensional stochastic velocity perturbations. Collectively, these models enable seismic velocities to be realistically represented for applications such as 3D ground motion and site response simulations. Lastly the New Zealand velocity model is applied to simulate ground motions for a Mw7.51 rupture of the Hope Fault using a physics-based simulation methodology and a 3D crustal velocity model of New Zealand. The simulation methodology was validated for use in the region through comparison with observations for a suite of historic small magnitude earthquakes located proximal to the Hope Fault. Simulations are compared with conventionally utilised empirical ground motion models, with simulated peak ground velocities being notably higher in regions with modelled sedimentary basins. A sensitivity analysis was undertaken where the source characteristics of magnitude, stress parameter, hypocentre location and kinematic slip distribution were varied and an analysis of their effect on ground motion intensities is presented. It was found that the magnitude and stress parameter strongly influenced long and short period ground motion amplitudes, respectively. Ground motion intensities for the Hope Fault scenario are compared with the 2016 Kaikoura Mw7.8 earthquake, it was found that the Kaikoura earthquake produced stronger motions along the eastern South Island, while the Hope Fault scenario resulted in stronger motions immediately West of the near-fault region. The simulated ground motions for this scenario complement prior empirically-based estimates and are informative for mitigation and emergency planning purposes.
© 2019, Springer-Verlag GmbH Germany, part of Springer Nature. Prediction of building collapse due to significant seismic motion is a principle objective of earthquake engineers, particularly after a major seismic event when the structure is damaged and decisions may need to be made rapidly concerning the safe occupation of a building or surrounding areas. Traditional model-based pushover analyses are effective, but only if the structural properties are well understood, which is not the case after an event when that information is most useful. This paper combines hysteresis loop analysis (HLA) structural health monitoring (SHM) and incremental dynamic analysis (IDA) methods to identify and then analyse collapse capacity and the probability of collapse for a specific structure, at any time, a range of earthquake excitations to ensure robustness. This nonlinear dynamic analysis enables constant updating of building performance predictions following a given and subsequent earthquake events, which can result in difficult to identify deterioration of structural components and their resulting capacity, all of which is far more difficult using static pushover analysis. The combined methods and analysis provide near real-time updating of the collapse fragility curves as events progress, thus quantifying the change of collapse probability or seismic induced losses very soon after an earthquake for decision-making. Thus, this combination of methods enables a novel, higher-resolution analysis of risk that was not previously available. The methods are not computationally expensive and there is no requirement for a validated numerical model, thus providing a relatively simpler means of assessing collapse probability immediately post-event when such speed can provide better information for critical decision-making. Finally, the results also show a clear need to extend the area of SHM toward creating improved predictive models for analysis of subsequent events, where the Christchurch series of 2010–2011 had significant post-event aftershocks.
The aim of this poster is to examine the seismic response of two structural systems when subjected to observed and simulated ground motions (GMs) for the 22 February 2011 (22Feb2011) Christchurch earthquake (Razafindrakoto et al. (2018)) via an automated workflow. The layout and technical details of the automated workflow are described at Motha et. al. (2019).
Meeting the Sustainable Development Goals by 2030 involves transformational change in the business of business, and social enterprises can lead the way in such change. We studied Cultivate, one such social enterprise in Christchurch, New Zealand, a city still recovering from the 2010/11 Canterbury earthquakes. Cultivate works with vulnerable youth to transform donated compost into garden vegetables for local restaurants and businesses. Cultivate’s objectives align with SDG concerns with poverty and hunger (1 & 2), social protection (3 & 4), and sustainable human settlements (6 & 11). Like many grant-supported organisations, Cultivate is required to track and measure its progress. Given the organisation’s holistic objectives, however, adequately accounting for its impact reporting is not straightforward. Our action research project engaged Cultivate staff and youth-workers to generate meaningful ways of measuring impact. Elaborating the Community Economy Return on Investment tool (CEROI), we explore how participatory audit processes can capture impacts on individuals, organisations, and the wider community in ways that extend capacities to act collectively. We conclude that Cultivate and social enterprises like it offer insights regarding how to align values and practices, commercial activity and wellbeing in ways that accrue to individuals, organisations and the broader civic-community.
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