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 region in and around Christchurch, encompassing Christchurch city and the Selwyn and Waimakariri districts, contains more than 800 road, rail, and pedestrian bridges. Most of these bridges are reinforced concrete, symmetric, and have small to moderate spans (15–25 m). The 22 February 2011 moment magnitude (Mw) 6.2 Christchurch earthquake induced high levels of localized ground shaking (Bradley and Cubrinovski 2011, page 853 of this issue; Guidotti et al. 2011, page 767 of this issue; Smyrou et al. 2011, page 882 of this issue), with damage to bridges mainly confined to the central and eastern parts of Christchurch. Liquefaction was evident over much of this part of the city, with lateral spreading affecting bridges spanning both the Avon and Heathcote rivers.
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
The paper proposes a simple method for quick post-earthquake assessment of damage and condition of a stock of bridges in a transportation network using seismic data recorded by a strong motion array. The first part of the paper is concerned with using existing free field strong motion recorders to predict peak ground acceleration (PGA) at an arbitrary bridge site. Two methods are developed using artificial neural networks (a single network and a committee of neural networks) considering influential parameters, such as seismic magnitude, hypocentral depth and epicentral distance. The efficiency of the proposed method is explored using actual strong motion records from the devastating 2010 Darfield and 2011 Christchurch earthquakes in New Zealand. In the second part, two simple ideas are outlined how to infer the likely damage to a bridge using either the predicted PGA and seismic design spectrum, or a broader set of seismic metrics, structural parameters and damage indices.
On 14 November 2016 a magnitude Mw 7.8 earthquake struck the upper South Island of New Zealand with effects also being observed in the capital city, Wellington. The affected area has low population density but is the largest wine production region in New Zealand and also hosts the main national highway and railway routes connecting the country’s three largest cities of Auckland, Wellington and Christchurch, with Marlborough Port in Picton providing connection between the South and North Islands. These transport facilities sustained substantial earthquake related damage, causing major disruptions. Thousands of landslides and multiple new faults were counted in the area. The winery facilities and a large number of commercial buildings and building components (including brick masonry veneers, historic masonry construction, and chimneys), sustained damage due to the strong vertical and horizontal acceleration. Presented herein are field observations undertaken the day immediately after the earthquake, with the aim to document earthquake damage and assess access to the affected area.
Though generally considered “natural” disasters, cyclones and earthquakes are increasingly being associated with human activities, incubated through urban settlement patterns and the long-term redistribution of natural resources. As society is becoming more urbanized, the risk of human exposure to disasters is also rising. Architecture often reflects the state of society’s health: architectural damage is the first visible sign of emergency, and reconstruction is the final response in the process of recovery. An empirical assessment of architectural projects in post-disaster situations can lead to a deeper understanding of urban societies as they try to rebuild. This thesis offers an alternative perspective on urban disasters by looking at the actions and attitudes of disaster professionals through the lens of architecture, situated in recent events: the 2010 Christchurch earthquake, the 2010 Haiti earthquake, and the 2005 Hurricane Katrina. An empirical, multi-hazard, cross-sectional case study methodology was used, employing grounded theory method to build theory, and a critical constructivist strategy to inform the analysis. By taking an interdisciplinary approach to understanding disasters, this thesis positions architecture as a conduit between two divergent approaches to disaster research: the hazards approach, which studies the disaster cycles from a scientific perspective; and the sociological approach, which studies the socially constructed vulnerabilities that result from disasters, and the elements of social change that accompany such events. Few studies to date have attempted to integrate the multi-disciplinary perspectives that can advance our understanding of societal problems in urban disasters. To bridge this gap, this thesis develops what will be referred to as the “Rittelian framework”—based on the work of UC Berkeley’s architecture professor Horst Rittel (1930-1990). The Rittelian framework uses the language of design to transcend the multiple fields of human endeavor to address the “design problems” in disaster research. The processes by which societal problems are addressed following an urban disaster involve input by professionals from multiple fields—including economics, sociology, medicine, and engineering—but the contribution from architecture has been minimal to date. The main impetus for my doctoral thesis has been the assertion that most of the decisions related to reconstruction are made in the early emergency recovery stages where architects are not involved, but architects’ early contribution is vital to the long-term reconstruction of cities. This precipitated in the critical question: “How does the Rittelian framework contribute to the critical design decisions in modern urban disasters?” Comparative research was undertaken in three case studies of recent disasters in New Orleans (2005), Haiti (2010) and Christchurch (2010), by interviewing 51 individuals who were selected on the basis of employing the Rittelian framework in their humanitarian practice. Contextualizing natural disaster research within the robust methodological framework of architecture and the analytical processes of sociology is the basis for evaluating the research proposition that architectural problem solving is of value in addressing the ‘Wicked Problems’ of disasters. This thesis has found that (1) the nuances of the way disaster agents interpret the notion of “building back better” can influence the extent to which architectural professionals contribute in urban disaster recovery, (2) architectural design can be used to facilitate but also impede critical design decisions, and (3) framing disaster research in terms of design decisions can lead to innovation where least expected. This empirical research demonstrates how the Rittelian framework can inform a wider discussion about post-disaster human settlements, and improve our resilience through disaster research.
