You Dong

Sustainability of Highway Bridge Networks under Seismic Hazard

In order to evaluate the seismic risk of transportation networks, it is necessary to develop a methodology that integrates the probabilities of occurrence of seismic events in a region, the vulnerability of the civil infrastructure, and the consequences of the seismic hazard to the society, environment, and economy. In this article, a framework for the time-variant seismic sustainability and risk assessment of highway bridge networks is presented. The sustainability of the network is quantified in terms of its social, environmental, and economic metrics. These include the expected downtime, expected energy waste and carbon dioxide emissions, and the expected loss. The methodology considers the probability of occurrence of a set of seismic scenarios that reflect the seismic activity of the region. The performance of network links is quantified based on individual bridge performance evaluated through fragility analyses. The sustainability and risk depend on the damage states of both the links and the bridges within the network following an earthquake scenario. The time-variation of the sustainability metrics and risk due to structural deterioration is identified. The approach is illustrated on a transportation network located in Alameda County, California.

Assessment of Risk Using Bridge Element Condition Ratings

AbstractIn this paper, a methodology for quantifying lifetime risk of bridge superstructures is presented. The risk is quantified in terms of the expected direct and indirect losses. A scenario-based approach, which uses the Pontis element condition rating system, is used for identifying the expected losses. The deterioration process of bridge components regarding the transition between the condition states is modeled as a Markov process. In addition, a reliability-based approach is used to compute the probabilities of component and system failure, given the condition states. The methodology is illustrated on an existing bridge in Wisconsin. The expected losses associated with the flexural failure of girders are quantified in time. Furthermore, the time-variant risk-based robustness index is assessed.

Optimizing Bridge Network Retrofit Planning Based on Cost-Benefit Evaluation and Multi-Attribute Utility Associated with Sustainability

During their service life, bridge networks may be exposed to extreme events, including strong earthquakes, which pose an imminent threat to society, economy, and surrounding environment. This threat reinforces the need to implement updated sustainability assessment and optimal risk mitigation procedures. The sustainability-based seismic optimization of bridge networks considering the utility associated with cost and benefit of retrofit interventions is investigated. The ultimate aim of this framework is to reduce the extent of earthquake damage to society, economy, and environment, while simultaneously minimizing the total retrofit costs of bridge networks. The total benefit of a retrofit plan is quantified in terms of the reduction in the seismic loss during a given time interval using multi-attribute utility theory. Retrofit actions associated with varying improvement levels are considered herein. A genetic algorithm based optimization procedure is adopted to determine the optimal retrofit action for each bridge within an existing bridge network.

Pre-Earthquake Multi-Objective Probabilistic Retrofit Optimization of Bridge Networks Based on Sustainability

Planning retrofit actions on bridge networks under tight budget constraints is a challenging process. Because of the uncertainties associated with this process, a probabilistic approach is necessary. In this paper, a probabilistic methodology to establish optimum pre-earthquake retrofit plans for bridge networks based on sustainability is developed. A multicriteria optimization problem is formulated to find the optimum timing of retrofit actions for bridges within a network. The sustainability of a bridge network and the total cost of retrofit actions are considered as conflicting criteria. The sustainability is quantified in terms of the expected economic losses. The uncertainties associated with seismic hazard and structural vulnerability are considered. The methodology is illustrated on an existing bridge network. Genetic algorithms are used to solve the multicriteria optimization problem. The effects of deterioration on bridge seismic performance are considered. The effects of the time horizon on the Pareto optimal solutions are also investigated.

Life cycle utility-informed maintenance planning based on lifetime functions: optimum balancing of cost, failure consequences and performance benefit

Decision-making regarding the optimum maintenance of civil infrastructure systems under uncertainty is a topic of paramount importance. This topic is experiencing growing interest within the field of life cycle structural engineering. Embedded within the decision-making process and optimum management of engineering systems is the structural performance evaluation, which is facilitated through a comprehensive life cycle risk assessment. Lifetime functions including survivor, availability, and hazard at component and system levels are utilised herein to model, using closed-form analytical expressions, the time-variant effect of intervention actions on the performance of civil infrastructure systems. The presented decision support framework based on lifetime functions has the ability to quantify maintenance cost, failure consequences and performance benefit in terms of utility by considering correlation effects. This framework effectively employs tri-objective optimisation procedures in order to determine optimum maintenance strategies under uncertainty. It provides optimum lifetime intervention plans allowing for utility-informed decision-making regarding maintenance of civil infrastructure systems. The effects of the risk attitude, correlation among components and the number of maintenance interventions on the optimum maintenance strategies are investigated. The capabilities of the proposed decision support framework are illustrated on five configurations of a four-component system and an existing highway bridge.

A decision support system for mission-based ship routing considering multiple performance criteria

Abstract It is crucial to evaluate the risk associated with marine vessels subjected to inclement weather and sea conditions when developing a decision support system for ship routing. The generalized decision making framework developed in this paper performs a variety of tasks, including, but not limited to quantifying the flexural and fatigue performance of ship structures and employing multi-attribute utility theory to evaluate ship mission performance. A structural reliability approach is utilized to compute the probability of failure considering the uncertainties in structural capacity and load effects; specifically, effects of flexural and fatigue damage are investigated. The expected repair cost, cumulative fatigue damage, total travel time, and carbon dioxide emissions associated with ship routing are considered as consequences within the risk assessment procedure adopted in this paper. Additionally, the decision maker’s risk attitude is integrated into the presented approach by employing utility theory. The presented methodology can assist decision makers in making informed decisions concerning ship routing. In order to illustrate its capabilities the approach is applied to the Joint High-speed Sealift Ship.

Probabilistic Time-Dependent Multihazard Life-Cycle Assessment and Resilience of Bridges Considering Climate Change

AbstractClimate change and an increase in the number of hazards and/or their intensities may increase the probability of failure associated with civil infrastructure systems. Understanding how natural hazards affect the life-cycle performance of highway bridges can lead to improved preparedness prior to extreme disasters and can ultimately benefit society. In this paper, a framework for time-variant loss and resilience assessment of highway bridges under time-dependent multiple hazards is presented. The effects of earthquakes and floods on bridges are both investigated. The life-cycle hazard losses with and without aging effects and climate change are computed. Additionally, the probabilistic changes in the hazard intensity and frequency resulting from climate change on the total life-cycle hazard loss are also investigated. The proposed framework is applied to a highway bridge located in California.

Probabilistic assessment of an interdependent healthcare–bridge network system under seismic hazard

Abstract Strong earthquakes can destroy infrastructure systems and cause injuries and/or fatalities. Therefore, it is important to investigate seismic performance of interdependent infrastructure systems and guarantee their abilities to cope with earthquakes. This paper presents an integrated probabilistic framework for the healthcare–bridge network system performance analysis considering spatial seismic hazard, vulnerability of bridges and links in the network, and damage condition of a hospital at component and system levels. The system level performance is evaluated considering travel and waiting time based on the damage conditions of the components. The effects of correlation among the seismic intensities at different locations are investigated. Additionally, the correlations associated with damage of the investigated structures are also incorporated within the probabilistic assessment process. The conditional seismic performance of the hospital given the damage conditions of the bridge network and the effect of bridge retrofit actions are also investigated. The approach is illustrated on a healthcare system located near a bridge network in Alameda, California.

Efficient Uncertainty Quantification of Wharf Structures under Seismic Scenarios Using Gaussian Process Surrogate Model

ABSTRACT The scenario-based seismic assessment approach is illustrated within a large-scale pile-supported wharf structure (PSWS). As nonlinear seismic response analysis is computationally expensive, a novel and efficient method is developed to improve and update the traditional simulation methods. Herein, the Gaussian Process (GP) surrogate model is proposed to replace the time-consuming FE model of PSWS, which makes the quantification of uncertainty in seismic response of a large-scale PSWS resulting from structural parameter uncertainty more computationally-efficient. The feasibility of the proposed approach in seismic assessment of a large-scale PSWS under a given seismic scenario is verified by using Monte Carlo simulation.

Adaptation optimization of residential buildings under hurricane threat considering climate change in a lifecycle context

AbstractDue to urbanization, the number of residential buildings in coastal areas has increased significantly. Additionally, due to the increase in sea surface temperature associated with climate c...