Rapid, accurate structural health monitoring (SHM) assesses damage to optimise decision-making. Many SHM methods are designed to track nonlinear stiffness changes as damage. However, highly nonlinear pinched hysteretic systems are problematic in SHM. Model-based SHM often fails as any mismatch between model and measured response dynamics leads to significant error. Thus, modelfree methods of hysteresis loop tracking methods have emerged. This study compares the robustness and accuracy in the presence of significant measurement noise of the proven hysteresis loop analysis (HLA) SHM method with 3 emerging model-free methods and 2 further novel adaptations of these methods using a highly nonlinear, 6-story numerical structure to provide a known ground-truth. Mean absolute errors in identifying a known nonlinear stiffness trajectory assessed at four points over two successive ground motion inputs from September 2010 and February 2011 in Christchurch range from 1.71-10.52%. However, the variability is far wider with maximum errors ranging from 3.90-49.72%, where the second largest maximum absolute error was still 19.74%. The lowest mean and maximum absolute errors were for the HLA method. The next best method had mean absolute error of 2.92% and a maximum of 10.51%. These results show the clear superiority of the HLA method over all current emerging model-free methods designed to manage the highly nonlinear pinching responses common in reinforced concrete structures. These results, combined with high robustness and accuracy in scaled and fullscale experimental studies, provide further validation for using HLA for practical implementation.
The September 2010 Canterbury and February 2011 Christchurch earthquakes and associated aftershocks have shown that the isolator displacement in Christchurch Women's Hospital (Christchurch City's only base-isolated structure) was significantly less than expected. Occupant accounts of the events have also indicated that the accelerations within the hospital superstructure were larger than would usually be expected within a base-isolated structure and that residual low-level shaking lasts for a longer period of time following the strong-motion of an event than for non-isolated structures.
This work investigates the possibility of developing a non-contact, non-line of sight sensor to measure interstorey drift through simulation and experimental validation. • The method uses frequency-modulated continuous wave (FMCW) radar to measure displacement. This method is commonly in use in a number of modern applications, including aircraft altimeters and automotive parking sensors. • The technique avoids numerous problems found in contemporary structural health monitoring methods, namely integral drift errors and structural modification requirements. • The smallest achievable detection error in displacement was found to be as low as 0.26%, through simulated against the displacement response of a single degree of freedom structure subject to ground motion excitation. • This was verified during experimentation, when a corner-style reflector was placed on a shake table running ground motion data taken from the 4th September 2010 earthquake in Christchurch. These results confirmed the conclusions drawn from simulation.
© 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.
Rapid, reliable information on earthquake-affected structures' current damage/health conditions and predicting what would happen to these structures under future seismic events play a vital role in accelerating post-event evaluations, leading to optimized on-time decisions. Such rapid and informative post-event evaluations are crucial for earthquake-prone areas, where each earthquake can potentially trigger a series of significant aftershocks, endangering the community's health and wealth by further damaging the already-affected structures. Such reliable post-earthquake evaluations can provide information to decide whether an affected structure is safe to stay in operation, thus saving many lives. Furthermore, they can lead to more optimal recovery plans, thus saving costs and time. The inherent deficiency of visual-based post-earthquake evaluations and the importance of structural health monitoring (SHM) methods and SHM instrumentation have been highlighted within this thesis, using two earthquake-affected structures in New Zealand: 1) the Canterbury Television (CTV) building, Christchurch; 2) the Bank of New Zealand (BNZ) building, Wellington. For the first time, this thesis verifies the theoretically- and experimentally validated hysteresis loop analysis (HLA) SHM method for the real-world instrumented structure of the BNZ building, which was damaged severely due to three earthquakes. Results indicate the HLA-SHM method can accurately estimate elastic stiffness degradation for this reinforced concrete (RC) pinched structure across the three earthquakes, which remained unseen until after the third seismic event. Furthermore, the HLA results help investigate the pinching effects on the BNZ building's seismic response. This thesis introduces a novel digital clone modelling method based on the robust and accurate SHM results delivered by the HLA method for physical parameters of the monitored structure and basis functions predicting the changes of these physical parameters due to future earthquake excitations. Contrary to artificial intelligence (AI) based predictive methods with black-box designs, the proposed predictive method is entirely mechanics-based with an explicitly-understandable design, making them more trusted and explicable to stakeholders engaging in post-earthquake evaluations, such as building owners and insurance firms. The proposed digital clone modelling framework is validated using the BNZ building and an experimental RC test structure damaged severely due to three successive shake-table excitations. In both structures, structural damage intensifies the pinching effects in hysteresis responses. Results show the basis functions identified from the HLA-SHM results for both structures under Event 1 can online estimate structural damage due to subsequent Events 2-3 from the measured structural responses, making them valuable tool for rapid warning systems. Moreover, the digital twins derived for these two structures under Event 1 can successfully predict structural responses and damage under Events 2-3, which can be integrated with the incremental dynamic analysis (IDA) method to assess structural collapse and its financial risks. Furthermore, it enables multi-step IDA to evaluate earthquake series' impacts on structures. Overall, this thesis develops an efficient method for providing reliable information on earthquake-affected structures' current and future status during or immediately after an earthquake, considerably guaranteeing safety. Significant validation is implemented against both experimental and real data of RC structures, which thus clearly indicate the accurate predictive performance of this HLA-based method.
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.
Sewerage systems convey sewage, or wastewater, from residential or commercial buildings through complex reticulation networks to treatment plants. During seismic events both transient ground motion and permanent ground deformation can induce physical damage to sewerage system components, limiting or impeding the operability of the whole system. The malfunction of municipal sewerage systems can result in the pollution of nearby waterways through discharge of untreated sewage, pose a public health threat by preventing the use of appropriate sanitation facilities, and cause serious inconvenience for rescuers and residents. Christchurch, the second largest city in New Zealand, was seriously affected by the Canterbury Earthquake Sequence (CES) in 2010-2011. The CES imposed widespread damage to the Christchurch sewerage system (CSS), causing a significant loss of functionality and serviceability to the system. The Christchurch City Council (CCC) relied heavily on temporary sewerage services for several months following the CES. The temporary services were supported by use of chemical and portable toilets to supplement the damaged wastewater system. The rebuild delivery agency -Stronger Christchurch Infrastructure Rebuild Team (SCIRT) was created to be responsible for repair of 85 % of the damaged horizontal infrastructure (i.e., water, wastewater, stormwater systems, and roads) in Christchurch. Numerous initiatives to create platforms/tools aiming to, on the one hand, support the understanding, management and mitigation of seismic risk for infrastructure prior to disasters, and on the other hand, to support the decision-making for post-disaster reconstruction and recovery, have been promoted worldwide. Despite this, the CES in New Zealand highlighted that none of the existing platforms/tools are either accessible and/or readable or usable by emergency managers and decision makers for restoring the CSS. Furthermore, the majority of existing tools have a sole focus on the engineering perspective, while the holistic process of formulating recovery decisions is based on system-wide approach, where a variety of factors in addition to technical considerations are involved. Lastly, there is a paucity of studies focused on the tools and frameworks for supporting decision-making specifically on sewerage system restoration after earthquakes. This thesis develops a decision support framework for sewerage pipe and system restoration after earthquakes, building on the experience and learning of the organisations involved in recovering the CSS following the CES in 2010-2011. The proposed decision support framework includes three modules: 1) Physical Damage Module (PDM); 2) Functional Impact Module (FIM); 3) Pipeline Restoration Module (PRM). The PDM provides seismic fragility matrices and functions for sewer gravity and pressure pipelines for predicting earthquake-induced physical damage, categorised by pipe materials and liquefaction zones. The FIM demonstrates a set of performance indicators that are categorised in five domains: structural, hydraulic, environmental, social and economic domains. These performance indicators are used to assess loss of wastewater system service and the induced functional impacts in three different phases: emergency response, short-term recovery and long-term restoration. Based on the knowledge of the physical and functional status-quo of the sewerage systems post-earthquake captured through the PDM and FIM, the PRM estimates restoration time of sewer networks by use of restoration models developed using a Random Forest technique and graphically represented in terms of restoration curves. The development of a decision support framework for sewer recovery after earthquakes enables decision makers to assess physical damage, evaluate functional impacts relating to hydraulic, environmental, structural, economic and social contexts, and to predict restoration time of sewerage systems. Furthermore, the decision support framework can be potentially employed to underpin system maintenance and upgrade by guiding system rehabilitation and to monitor system behaviours during business-as-usual time. In conjunction with expert judgement and best practices, this framework can be moreover applied to assist asset managers in targeting the inclusion of system resilience as part of asset maintenance programmes.
Access to clean and safe drinking water is a fundamental human requirement. However, in many areas of the world natural water sources have been impacted by a variety of biological and chemical contaminants. The ingestion of these contaminants may cause acute or chronic health problems. To prevent such illnesses, many technologies have been developed to treat, disinfect and supply safe drinking water quality. However, despite these advancements, water supply distribution systems can adversely affect the drinking water quality before it is delivered to consumers. The primary aim of this research was to investigate the effect that water distribution systems may have on household drinking water quality in Christchurch, New Zealand and Addis Ababa, Ethiopia. Water samples were collected from the source water and household taps in both cities. The samples were then tested for various physical, chemical and biological water quality parameters. The data collected was also used to determine if water samples complied with national drinking water quality standards in both countries. Independent samples t-test statistical analyses were also performed to determine if water quality measured in the samples collected from the source and household taps was significantly different. Water quality did not vary considerably between the source and tap water samples collected in Christchurch City. No bacteria were detected in any sample. However, the pH and total iron concentrations measured in source and tap water samples were found to be significantly different. The lower pH values measured in tap water samples suggests that corrosion may be taking place in the distribution system. No water samples transgressed the Drinking Water Standards for New Zealand (DWSNZ) MAVs. Monitoring data collected by the Christchurch City Council (CCC) was also used for comparison. A number of pH, turbidity and total iron concentration measurements collected by the CCC in 2011 were found to exceed the guideline values. This is likely due to structural damage to the source wells and pump-stations that occurred during the 2011 earthquake events. Overall, it was concluded that the distribution system does not adversely affect the quality of Christchurch City’s household drinking water. The water quality measured in samples collected from the source (LTP) and household taps in Addis Ababa was found to vary considerably. The water collected from the source complied with the Ethiopian (WHO) drinking water quality standards. However, tap water samples were often found to have degraded water quality for the physical and chemical parameters tested. This was especially the case after supply interruption and reinstatement events. Bacteria were also often detected in household tap water samples. The results from this study indicate that water supply disruptions may result in degraded water quality. This may be due to a drop in pipeline pressure and the intrusion of contaminants through the leaky and cross-connected pipes in the distribution network. This adversely affects the drinking water quality in Addis Ababa.
