Search

found 468 results

Images for loss; more images...

Research papers, University of Canterbury Library

Low Damage Seismic Design (LDSD) guidance material being developed by Engineering NZ is considering a design drift limit for multi-storey buildings of 0.5% at a new damage control limit state (DCLS). The impact of this new design requirement on the expected annual loss due to repair costs is investigated for a four-storey office building with reinforced concrete walls located in Christchurch. The LDSD guidance material aims to reduce the expected annual loss of complying buildings to below 0.1% of building replacement cost. The research tested this expectation. Losses were estimated in accordance with FEMA P58, using building responses from non-linear time history analyses (performed with OpenSees using lumped plasticity models). The equivalent static method, in line with NZS 1170.5 and NZS 3101, was used to design the building to LDSD specifications, representing a future state-of-practice design. The building designed to low-damage specification returned an expected annual loss of 0.10%, and the building designed conventionally returned an expected annual loss of 0.13%. Limitations with the NZS 3101 method for determining wall stiffness were identified, and a different method acknowledging the relationship between strength and stiffness was used to redesign the building. Along with improving this design assumption, the study finds that LDSD design criteria could be an effective way of limiting damage and losses.

Research papers, University of Canterbury Library

The article asks whether disasters that destroy life but leave the material infrastructure relatively intact tend to prompt communal coping focussing on loss, while disasters that destroy significant material infrastructure tend to prompt coping through restoration / re-building. After comparing memorials to New Zealand’s Christchurch earthquake and Pike River mine disasters, we outline circumstances in which collective restorative endeavour may be grassroots, organised from above, or manipulated, along with limits to effective restoration. We conclude that bereavement literature may need to take restoration more seriously, while disaster literature may need to take loss more seriously.

Research papers, University of Canterbury Library

This paper presents the probabilistic seismic performance and loss assessment of an actual bridge– foundation–soil system, the Fitzgerald Avenue twin bridges in Christchurch, New Zealand. A two-dimensional finite element model of the longitudinal direction of the system is modelled using advanced soil and structural constitutive models. Ground motions at multiple levels of intensity are selected based on the seismic hazard deaggregation at the site. Based on rigorous examination of several deterministic analyses, engineering demand parameters (EDP’s), which capture the global and local demand, and consequent damage to the bridge and foundation are determined. A probabilistic seismic loss assessment of the structure considering both direct repair and loss of functionality consequences was performed to holistically assess the seismi risk of the system. It was found that the non-horizontal stratification of the soils, liquefaction, and soil–structure interaction had pronounced effects on the seismic demand distribution of the bridge components, of which the north abutment piles and central pier were critical in the systems seismic performance. The consequences due to loss of functionality of the bridge during repair were significantly larger than the direct repair costs, with over a 2% in 50 year probability of the total loss exceeding twice the book-value of the structure.

Research papers, University of Canterbury Library

The earthquake engineering community is currently grappling with the need to improve the post-earthquake reparability of buildings. As part of this, proposals exist to change design criteria for the serviceability limit state (SLS). This paper reviews options for change and considers how these could impact the expected repair costs for typical New Zealand buildings. The expected annual loss (EAL) is selected as a relevant measure or repair costs and performance because (i) EAL provides information on the performance of a building considering a range of intensity levels, (ii) the insurance industry refers to EAL when setting premiums, and (iii) monetary losses are likely to be correlated with loss of building functionality. The paper argues that because the expected annual loss is affected by building performance over a range of intensity levels, the definition of SLS criteria alone may be insufficient to effectively limit losses. However, it is also explained that losses could be limited effectively if the loadings standard were to set the SLS design intensity considering the potential implications on EAL. It is shown that in order to achieve similar values of EAL in Wellington and Christchurch, the return period intensity for SLS design would need to be higher in Christchurch owing to differences in local hazard conditions. The observations made herein are based on a simplified procedure for EAL estimation and hence future research should aim to verify the findings using a detailed loss assessment approach applied to a broad range of case study buildings.

Research papers, University of Canterbury Library

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.

Research papers, University of Canterbury Library

The Canterbury Earthquake Sequence (CES), induced extensive damage in residential buildings and led to over NZ$40 billion in total economic losses. Due to the unique insurance setting in New Zealand, up to 80% of the financial losses were insured. Over the CES, the Earthquake Commission (EQC) received more than 412,000 insurance claims for residential buildings. The 4 September 2010 earthquake is the event for which most of the claims have been lodged with more than 138,000 residential claims for this event only. This research project uses EQC claim database to develop a seismic loss prediction model for residential buildings in Christchurch. It uses machine learning to create a procedure capable of highlighting critical features that affected the most buildings loss. A future study of those features enables the generation of insights that can be used by various stakeholders, for example, to better understand the influence of a structural system on the building loss or to select appropriate risk mitigation measures. Previous to the training of the machine learning model, the claim dataset was supplemented with additional data sourced from private and open access databases giving complementary information related to the building characteristics, seismic demand, liquefaction occurrence and soil conditions. This poster presents results of a machine learning model trained on a merged dataset using residential claims from the 4 September 2010.

Research papers, University of Canterbury Library

In the last century, seismic design has undergone significant advancements. Starting from the initial concept of designing structures to perform elastically during an earthquake, the modern seismic design philosophy allows structures to respond to ground excitations in an inelastic manner, thereby allowing damage in earthquakes that are significantly less intense than the largest possible ground motion at the site of the structure. Current performance-based multi-objective seismic design methods aim to ensure life-safety in large and rare earthquakes, and to limit structural damage in frequent and moderate earthquakes. As a result, not many recently built buildings have collapsed and very few people have been killed in 21st century buildings even in large earthquakes. Nevertheless, the financial losses to the community arising from damage and downtime in these earthquakes have been unacceptably high (for example; reported to be in excess of 40 billion dollars in the recent Canterbury earthquakes). In the aftermath of the huge financial losses incurred in recent earthquakes, public has unabashedly shown their dissatisfaction over the seismic performance of the built infrastructure. As the current capacity design based seismic design approach relies on inelastic response (i.e. ductility) in pre-identified plastic hinges, it encourages structures to damage (and inadvertently to incur loss in the form of repair and downtime). It has now been widely accepted that while designing ductile structural systems according to the modern seismic design concept can largely ensure life-safety during earthquakes, this also causes buildings to undergo substantial damage (and significant financial loss) in moderate earthquakes. In a quest to match the seismic design objectives with public expectations, researchers are exploring how financial loss can be brought into the decision making process of seismic design. This has facilitated conceptual development of loss optimisation seismic design (LOSD), which involves estimating likely financial losses in design level earthquakes and comparing against acceptable levels of loss to make design decisions (Dhakal 2010a). Adoption of loss based approach in seismic design standards will be a big paradigm shift in earthquake engineering, but it is still a long term dream as the quantification of the interrelationships between earthquake intensity, engineering demand parameters, damage measures, and different forms of losses for different types of buildings (and more importantly the simplification of the interrelationship into design friendly forms) will require a long time. Dissecting the cost of modern buildings suggests that the structural components constitute only a minor portion of the total building cost (Taghavi and Miranda 2003). Moreover, recent research on seismic loss assessment has shown that the damage to non-structural elements and building contents contribute dominantly to the total building loss (Bradley et. al. 2009). In an earthquake, buildings can incur losses of three different forms (damage, downtime, and death/injury commonly referred as 3Ds); but all three forms of seismic loss can be expressed in terms of dollars. It is also obvious that the latter two loss forms (i.e. downtime and death/injury) are related to the extent of damage; which, in a building, will not just be constrained to the load bearing (i.e. structural) elements. As observed in recent earthquakes, even the secondary building components (such as ceilings, partitions, facades, windows parapets, chimneys, canopies) and contents can undergo substantial damage, which can lead to all three forms of loss (Dhakal 2010b). Hence, if financial losses are to be minimised during earthquakes, not only the structural systems, but also the non-structural elements (such as partitions, ceilings, glazing, windows etc.) should be designed for earthquake resistance, and valuable contents should be protected against damage during earthquakes. Several innovative building technologies have been (and are being) developed to reduce building damage during earthquakes (Buchanan et. al. 2011). Most of these developments are aimed at reducing damage to the buildings’ structural systems without due attention to their effects on non-structural systems and building contents. For example, the PRESSS system or Damage Avoidance Design concept aims to enable a building’s structural system to meet the required displacement demand by rocking without the structural elements having to deform inelastically; thereby avoiding damage to these elements. However, as this concept does not necessarily reduce the interstory drift or floor acceleration demands, the damage to non-structural elements and contents can still be high. Similarly, the concept of externally bracing/damping building frames reduces the drift demand (and consequently reduces the structural damage and drift sensitive non-structural damage). Nevertheless, the acceleration sensitive non-structural elements and contents will still be very vulnerable to damage as the floor accelerations are not reduced (arguably increased). Therefore, these concepts may not be able to substantially reduce the total financial losses in all types of buildings. Among the emerging building technologies, base isolation looks very promising as it seems to reduce both inter-storey drifts and floor accelerations, thereby reducing the damage to the structural/non-structural components of a building and its contents. Undoubtedly, a base isolated building will incur substantially reduced loss of all three forms (dollars, downtime, death/injury), even during severe earthquakes. However, base isolating a building or applying any other beneficial technology may incur additional initial costs. In order to provide incentives for builders/owners to adopt these loss-minimising technologies, real-estate and insurance industries will have to acknowledge the reduced risk posed by (and enhanced resilience of) such buildings in setting their rental/sale prices and insurance premiums.

Research papers, University of Canterbury Library

Recently developed performance-based earthquake engineering framework, such as one provided by PEER (Deierlein et al. 2003), assist in the quantification in terms of performance such as casualty, monetary losses and downtime. This opens up the opportunity to identify cost-effective retrofit/rehabilitation strategies by comparing upfront costs associated with retrofit with the repair costs that can be expected over time. This loss assessment can be strengthened by learning from recent earthquakes, such as the 2010 Canterbury and 2016 Kaikoura earthquakes. In order to investigate which types of retrofit/rehabilitation strategies may be most cost-effective, a case study building was chosen for this research. The Pacific Tower, a 22-storey EBF apartment located within the Christchurch central business district (CBD), was damaged and repaired during the 2010 Canterbury earthquake series. As such, by taking hazard levels accordingly (i.e. to correspond to the Christchurch CBD), modelling and analysing the structure, and considering the vulnerability and repair costs of its different components, it is possible to predict the expected losses of the aforementioned building. Using this information, cost-effective retrofit/rehabilitation strategy can be determined. This research found that more often than not, it would be beneficial to improve the performance of valuable non-structural components, such as partitions. Although it is true that improving such elements will increase the initial costs, over time, the benefits gained from reduced losses should be expected to overcome the initial costs. Aftershocks do increase the predicted losses of a building even in lower intensities due to the fact that non-structural components can get damaged at such low intensities. By comparing losses computed with and without consideration of aftershocks for a range of historical earthquakes, it was found that the ratio between losses due to main shock with aftershocks to the losses due to the main shock only tended to increase with increasing main shock magnitude. This may be due to the fact that larger magnitude earthquakes tend to generate larger magnitude aftershocks and as those aftershocks happen within a region around the main shock, they are more likely to cause intense shaking and additional damage. In addition to this observation, it was observed that the most significant component of loss of the case study building was the non-structural partition walls.