Civil infrastructure systems play a crucial role in supporting economic and social welfare of communities. However, in the U.S., these systems are under continuous aging and deterioration hindering their ability to properly function. Changing climate may exacerbate this functionality problem. For the proper performance assessment of structural systems during their life-cycle, it is necessary to consider not only functionality but also economic, social and environmental indicators. Therefore, formulating methodologies to quantify the effects of changing climate on infrastructure vulnerability and to identify optimal life-cycle management strategies for civil infrastructure considering risk and sustainability is of paramount importance.

Most of the previous research on life-cycle management of civil infrastructure systems focused on formulating methodologies to enable understanding the effects of changing climate on the performance of these systems. Additionally, no clear integration of risk and sustainability metrics in the management of deteriorating infrastructure has been provided.  The project created a risk and sustainability-based decision-making framework capable of optimizing life-cycle management of civil infrastructure systems. The outputs of this framework are the optimized life-cycle intervention strategies considering conflicting budgetary and safety constraints. The developed risk and sustainability-based life-cycle management framework will facilitate the real-world implementation of life-cycle management methodologies.

The main novel contribution of the proposed research is the creation of a risk and sustainability-based decision-making framework capable of optimizing life-cycle management and adaptation activities for infrastructure under climate change. Formulating a systematic methodology to quantify consequences associated with infrastructure failure and management activities, suitable for risk and sustainability assessment under increasing threats due to climate change, is another major contribution.

There is an urgent need for developing and applying optimum life-cycle methodologies which can improve the resilience of our infrastructure to disasters. In this context, the results of this project will aid in reducing the adverse effects of natural disasters by solving the root cause of social disturbance (i.e., preventing structural failures) and improving the readiness of infrastructure systems to resist climate-related extreme events.

The results of the research reported in this project have profound societal, environmental, and economic benefits. The outcomes of this project will assist infrastructure managers in making the optimal decisions regarding climate change adaptation for bridges and buildings. Similarly, there are many long-life deteriorating systems, such as lifeline and power distribution networks, which will benefit from the results of this research.

The proposed risk- and sustainability-based performance assessment methodologies will advance the knowledge in the structural engineering field and the results of the proposed research will serve as the cornerstone for creating the next generation of risk-based assessment and design specifications for infrastructure systems subjected to harsh environmental conditions and climatic threats.

It was clearly demonstrated that within the context of climate change engineering, life-cycle loss, cost-benefit analysis, and optimization can provide decision makers important information necessary for assessment and adaptation of structural systems. This information can be used in design, maintenance, and management optimization processes of civil infrastructure considering extreme events and climate change. Faced with deep uncertainties stemming from future climate scenarios, it was also clearly demonstrated that life-cycle management based on robust optimization plays an essential role in the decision-making process of adapting civil infrastructure to a changing climate. The outcomes of this project enabled the identification of adaptation strategies that are both flexible and beneficial.

By leveraging global climate models and hydrologic modeling, the deep uncertainties conceptualized in this research were quantified for the first time, focusing on the flood hazards on riverine bridges. It was demonstrated that under different climate change scenarios and climate models, considerable spatial and model uncertainties are prevalent in terms of future flood frequency and intensity.

Based on the projection from global climate models, a network-level, risk-based framework was proposed to determine the optimal climate adaptation schedules for bridges in a transportation network. Bridge scour, one of the most common failure modes for bridges under floods, was investigated together with the effects of budget availability and risk perception during the decision-making process. A novel method was developed to efficiently compute network-level risk.

The outcomes of this project can be used to achieve climate change-informed design, maintenance, management, and optimization of civil infrastructure. This project provided needed knowledge for the development of an integrated risk and sustainability informed decision-making framework for optimum life-cycle management of civil infrastructure systems. Results from this research will benefit the U.S. economy and society. This research reported in this project involves several disciplines including structural reliability and risk, bridge engineering, life-cycle engineering, optimization, and decision theory. The multi-disciplinary approach will help broaden participation of underrepresented groups in research.  

Last Modified: 10/10/2020
Modified by: Dan M Frangopol