title: Development of Advanced Rate-Dependent Analytical Model of Lead Rubber Bearing and Seismic Resilience Assessment of a Highway Bridge Network
Creators: name: Aghaei Doost, Vahid
Publisher: name: Graduate Studies
Year: 2024
Subjects: subject: Lead Rubber Bearing
subject: Highway Bridge Network
subject: Isolated Bridge
subject: Resilience Assessment
subject: Earthquake
subject: Life-Cycle Analysis
subject: Machine Learning
subject: Engineering--Civil

description: Bridges serve as integral components of the transportation infrastructure, providing ongoing mobility and essential support to society. Within the realm of bridge engineering, a primary focus lies in the development of resilient bridges capable of withstanding multiple hazard events. Natural disasters can significantly impede transportation and emergency response efforts when bridges sustain damage. Recent events have demonstrated that highway bridges are highly susceptible components within transportation networks during various catastrophic events. In bridge construction, isolation bearings play a pivotal role by supporting the bridge superstructure and facilitating the transfer of forces to the substructure. Seismic isolation bearings exhibit the capacity to withstand substantial lateral displacements and effectively support axial loads induced by both gravity and earthquakes. Among various types of isolation bearings, lead rubber bearings (LRBs) have emerged as the prevailing choice for applications in both buildings and bridges. While several analytical models for LRBs have been developed to date, it is imperative to acknowledge that these existing modeling techniques do not encompass the loadings from various earthquake scenarios that represent a wide range of strain levels and rates. Therefore, it becomes imperative to ensure that LRB isolation systems exhibit predictable behavior under all possible loading conditions, coupled with the capability to maintain functionality even when subjected to hazards exceeding the design-level magnitude. The overarching objective of this research is to develop an advanced analytical model of LRB that can capture different characteristics of LRB nonlinear response that are currently not available in existing LRB models. To achieve this, a sensitivity analysis is conducted, employing different existing LRB analytical models to elucidate the critical features that significantly influence the seismic response of LRB-isolated bridges. Furthermore, this research embarks on the development of a high-fidelity advanced rate-dependent analytical model for LRBs that can account for rate-dependency, low-to-large strain levels, strength degradation of the lead core due to heating, rubber hardening, initial lead hardening, scragging, and Mullins damage parameters, and the influence of vertical loads within isolation systems. In addition, by implementing the developed LRB analytical model, a comprehensive evaluation of bridge seismic performance over the bridge life-cycle is conducted. The transportation network resiliency is crucial for ensuring the smooth functioning of a region, especially during and after a seismic event. Lastly, this research extends its scope to encompass seismic vulnerability and resilience assessment of a regional bridge network featuring LRB-isolated bridges. Comprehending the potential damages that may occur during seismic events enables engineers and policymakers to allocate resources strategically for retrofitting, maintenance, and disaster preparedness initiatives. By leveraging the Artificial Neural Network algorithm, finally, a framework for predicting the resilience and reliability indices of the regional bridge network is proposed. Through a comprehensive sensitivity analysis, the development of an advanced analytical model, and an evaluation of life-cycle resilience, this study contributes to the evolving field of bridge engineering and resilience assessment. Moreover, the exploration of multi-hazard vulnerability and resilience assessment extends the practical implications of this research, aiding in the creation of safer and more resilient transportation networks. In conclusion, this research provides an effective framework for vulnerability and resilience assessment that can be applied in both theoretical and practical applications.