Back to results list
Show full item record
Please use this identifier to cite or link to this item:
|Title:||Risk- and resilience-based life-cycle analysis of engineering structures under multiple hazards||Authors:||Li, Yaohan||Degree:||Ph.D.||Issue Date:||2021||Abstract:||In recent decades, the devastating effects that hazards have on societies worldwide have intermittently raised the attention of governments and the public to hazard risk assessment and management. For civil infrastructure, various hazards (e.g., earthquakes, hurricanes, and progressive deterioration) can lead to damage and failure of the system. They may impair structural functionality and result in severe social disruption and economic losses. Additionally, due to various sources of uncertainty, multiple hazards may interact and cause amplification of the adverse effects on the system. In a life-cycle context, the hazard-induced losses can be accumulated, thus resulting in a considerable reduction in the resilience of civil infrastructure. Therefore, it is of paramount importance to assess the risk and enhance the resilience of civil infrastructure subjected to multi-hazard scenarios in a life-cycle context. This thesis aims to develop a risk- and resilience-based life-cycle analysis framework for engineering structures under multiple hazards. The proposed framework consists of different segments: scenario-based multi-hazard analysis, structural vulnerability assessment, quantification of long-term loss and resilience, and life-cycle management of civil infrastructure subjected to multiple hazards. The uncertainties springing from each segment are considered and evaluated. The probabilistic hazard analysis and structural vulnerability assessment play fundamental roles in the life-cycle analysis. Most previous studies paid attention to the impact of the single hazard and neglected the compound effects of multi-hazard effects. For instance, neglecting the compounding effect of hurricane events may lead to underestimation of the structural vulnerability and provide inappropriate inputs for the life-cycle analysis. In this thesis, a copula-based multivariate approach is proposed to model the correlation between hazard parameters based on historical records. By identifying the correlation between hazard parameters, the structural vulnerability subjected to the multi-hazard scenarios can be assessed.
Given the hazard analysis and structural vulnerability, risk and resilience can be employed to assess the performance of the engineering structures under hazards. Different from previous studies focusing on a single hazard, this thesis proposes two indicators (i.e., long-term resilience and loss) to assess the long-term performance of systems under stationary and nonstationary hazards. A general approach is developed to quantify long-term loss (i.e., damage cost) and resilience considering uncertainties associated with hazard frequency and intensity. Specifically, the renewal theory is used to assess the performance under stationary hazards, and the moment generating function approach is developed to address uncertainty resulting from the nonstationary occurrence. In addition to uncertainties of hazards, uncertainties in terms of long-term loss cannot be ignored. Though the minimum expectation of long-term loss has been applied as a standard criterion, uncertainties associated with the other statistical moments, especially the higher-order moments (i.e., skewness and kurtosis) have been neglected in previous research. Therefore, in addition to the lower-order moments (i.e., mean and standard deviation), this thesis provides a higher-order analysis for the long-term loss assessment. The higher-order moments can be significant parameters in the decision-making process during life-cycle management. Subsequently, a probabilistic life-cycle management framework can be proposed to incorporate various performance indicators and uncertainties. As the performance of civil infrastructure degrades with time due to exposure to multiple hazards, a reliability-based approach is proposed to describe structural performance. Gradual deterioration caused by environmental exposure and extreme events are taken into account. The combined effects and the interaction between different deterioration processes are also explored in the proposed life-cycle framework. Based on the time-dependent reliability assessment, the maintenance policy can be developed. Herein, the impact of correlated maintenance interval and cost on the life-cycle cost is highlighted. Such correlation has been commonly neglected in previous studies. A copula-based renewal model is proposed to quantify statistical moments of the life-cycle maintenance cost analytically and numerically. The proposed model delivers an effective approach for data-based decision-making and life-cycle management of ageing engineering structures. Illustrative examples are presented to demonstrate the proposed framework. Results reveal the significance of considering interactions among deterioration processes, correlated maintenance interval and cost, and higher-order moments during the life-cycle analysis. Overall, this thesis provides methodologies to address risk- and resilience-based life-cycle assessment and management of engineering structures. A life-cycle analysis framework of ageing civil infrastructure under multiple hazards is proposed. Multi-hazard effects are considered in the proposed framework including continuous deterioration and external extreme hazards (e.g., earthquakes and hurricanes). The proposed framework is applied and illustrated by several engineering applications focusing on highway bridges. The proposed framework can be applied to assist decision-makers in planning risk mitigation strategies and enhancing infrastructural resilience in a life-cycle context.
Service life (Engineering)
Building materials -- Service life
Hong Kong Polytechnic University -- Dissertations
|Pages:||xxiv, 229 pages : color illustrations|
|Appears in Collections:||Thesis|
View full-text via https://theses.lib.polyu.edu.hk/handle/200/11547
Citations as of May 15, 2022
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.