Sunyong Kim

Bridge System Performance Assessment from Structural Health Monitoring: A Case Study

Based on the long-term monitored strain data induced by heavy vehicle traffic on an existing bridge, this paper presents an efficient approach to assessing the bridge system performance through a series-parallel system model consisting of bridge component reliabilities. The correlations among the bridge component safety margins are obtained by using actual traffic and strain data from structural health monitoring SHM. The prediction of bridge system reliability in the future is dependent on the performance functions of components. Sensitivity studies with respect to system modeling, correlations, extreme value probability distributions, measurement errors, and number of observations are carried out. A case study of the proposed approach is provided on an existing highway bridge in Wisconsin, which was monitored in 2004 by the Advanced Technology for Large Structural Systems Center, a National Engineering Research Center at Lehigh University, Bethlehem, Pa, USA. This study provides a solid basis for integrating SHM data into practical assessment of bridge system performance. DOI: 10.1061/ASCEST.1943-541X.0000014 CE Database subject headings: Bridges; Structural reliability; Structural safety; Monitoring; Assessments.

Generalized Probabilistic Framework for Optimum Inspection and Maintenance Planning

This paper proposes a generalized probabilistic framework for optimum inspection and maintenance planning of deteriorating structures. The proposed framework covers (1) the damage occurrence and propagation and service life prediction under uncertainty, (2) the relation between degree of damage and probability of damage detection of an inspection method, and (3) the effects of inspection and maintenance on service life and life-cycle cost. Optimum inspection and maintenance types and times are obtained through an optimization formulation by maximizing the expected service life and minimizing the expected total life-cycle cost consisting of inspection and maintenance costs. The service life, life-cycle cost, and maintenance delay, along with inspection and maintenance actions, are formulated using a decision tree model. The selection of the appropriate maintenance type depends on the degree of damage. The proposed framework is general and can be applied to any types of deteriorating structures or materials. Applications of the proposed framework may include, but are not limited to, bridges, buildings, aircrafts, and naval ships.

Maintenance, management, life-cycle design and performance of structures and infrastructures: a brief review

The optimal decisions to maintain or improve the reliability and functionality of structures and infrastructure systems can only be achieved through proper integrated management planning in a life-cycle comprehensive framework. Structure and Infrastructure Engineering (SIE) is an international journal dedicated to recent advances inmaintenance, management, and life-cycle performance of a wide range of infrastructures. The purpose of this article is to provide a brief review of the recent research accomplishments in the field of design, maintenance, life-cycle management, and optimisation of structures and infrastructures reported in papers published in SIE during the period 2005–2011. The papers are categorised under main topics and very briefly discussed.

Probabilistic Optimum Inspection/Repair Planning to Extend Lifetime of Deteriorating Structures

Repair actions are generally used to prevent failures and to maintain or extend the lifetime of deteriorating structures. To establish optimum inspection/repair planning for a structure, its performance under uncertainty should be assessed and predicted using probabilistic concepts and methods. This paper presents such an approach applied to deteriorating reinforced concrete (RC) structures under pitting corrosion. The inspection/repair plan is obtained from a probabilistic optimization process. Formulation of the extended lifetime for a given number of inspections is based on a decision tree analysis considering probability of damage detection. A damage detectability function is used to quantify the relation among damage intensity, quality of an inspection method, and probability of damage detection. The probability of repair representing the decision maker’s willingness to make a repair is also considered in the decision analysis. Effects of probabilities of inspection/repair and number of inspections on extended lifetime of an RC structure are investigated. To establish a cost-effective inspection/repair planning process, the formulation proposed is a biobjective optimization problem under uncertainty considering maximization of expected extended lifetime and minimization of expected total cost. The proposed approach is applied to an existing bridge.

Cost-Based Optimum Scheduling of Inspection and Monitoring for Fatigue-Sensitive Structures under Uncertainty

Inspection and monitoring of deteriorating structures are generally performed to assess structural integrity and predict the remaining service life. For deteriorating structures, a reliable prediction of damage occurrence and the time-dependent damage evaluation depend on the accuracy of deterioration models under uncertainty. A probabilistic approach to establish optimum cost-based inspection and monitoring schedules of fatigue-sensitive structures is proposed in this paper. The inspection schedule is the solution of an optimization problem to minimize the expected total cost, including the costs of inspections or monitorings, and the expected failure cost. The failure criterion uses damage detection time and time for damage to reach the critical state. The uncertainties associated with damage occurrence/propagation and damage detection time are both considered. The solution of the optimization provides the inspection times and quality of inspections. The formulation of the optimization for inspection scheduling is extended to monitoring scheduling. Effects of the failure cost on inspection and monitoring scheduling are also studied. The proposed approach is applied to a fatigue-sensitive structure.

Probabilistic bicriterion optimum inspection/monitoring planning: applications to naval ships and bridges under fatigue

Initiation and propagation of fatigue cracks in steel structures induced by repetitive actions are highly random due to both aleatory and epistemic uncertainties related to material properties, loads, damage, modelling and other factors. For this reason, a probabilistic approach is necessary to predict the fatigue crack growth damage. This study presents a probabilistic approach for combined inspection/monitoring planning for fatigue-sensitive structures considering uncertainties associated with fatigue crack initiation, propagation and damage detection. This combined inspection/monitoring planning is the solution of an optimisation formulation, where the objective is minimising theexpected damage detection delay. Furthermore, this formulation is extended to a bicriterion optimisation considering the conflicting relation between expected damage detection delay and cost. A set of Pareto solutions is obtained by solving this bicriterion optimisation problem. From this set, a solution can be selected balancing in an optimum manner inspection and monitoring times, quality of inspections, monitoring duration, and number of inspections and monitorings. The proposed approach is applied to a naval ship and a bridge subjected to fatigue.

Cost-Effective Lifetime Structural Health Monitoring Based on Availability

The state of a structural system subjected to deterioration processes is changing continuously. This state cannot be reliably predicted without considering both aleatory and epistemic uncertainties. To reduce the epistemic uncertainty, inspection and structural health monitoring (SHM) should be performed, and the performance prediction model should be updated periodically. Continuous monitoring is needed to reliably assess and predict the performance of structures. However, due to limited financial resources, continuous monitoring is not practical. Therefore, a cost-effective SHM strategy is necessary. In this paper, the probability that the performance prediction model based on monitoring data is usable in the future is computed by using the statistics of extremes and availability theory. This probability represents the availability of the monitoring data over nonmonitoring periods. The monitoring cost and availability can be found by solving a biobjective optimization problem. This problem consists in simultaneously minimizing the total monitoring cost and maximizing the availability of the monitoring data for performance prediction. Pareto solutions associated with monitoring duration and prediction duration are obtained. The proposed approach is applied to an existing bridge.

Fatigue performance assessment and service life prediction of high-speed ship structures based on probabilistic lifetime sea loads

This article focuses on estimating probabilistic lifetime sea loads for high-speed ship structures with the aim of assessing fatigue performance and predicting service life from available data. Performance assessment and service life prediction for naval ship structures are extremely important issues. In particular, understanding the effect of sea loading on naval high-speed vessels is still a challenge. Potential lifetime load effects including low frequency wave-induced and high frequency slam-induced whipping loadings are investigated in this article by using a probabilistic approach. Clearly, integration of probabilistic sea loads into structural reliability assessment and service life prediction will provide a more reliable estimation of the long-term structural performance. Accordingly, this article presents an approach for fatigue reliability evaluation of ship structures based on the estimated lifetime sea loads. Loading information associated with sea states, ship speeds and relative wave headings is obtained from a joint high-speed sealift ship monohull structural seakeeping trials, while the S–N curves are established based on the British Standards.

Service life, reliability and maintenance of civil structures

Abstract: Application of maintenance to extend the service life of civil structures is an important issue for civil structure managers. In order to establish an optimal maintenance strategy under uncertainty, it is essential to understand the concept of service life based on reliability of structures. In this chapter, concepts and applications of structural reliability and service life considering uncertainty are discussed. In addition, the general concept of optimization with conflicting objectives is introduced in order to extend the service life of structures more efficiently.

Efficient multi-objective optimisation of probabilistic service life management

Abstract The inspection and maintenance plans to ensure the structural safety and extend the service life of deteriorating structures can be established effectively through an optimisation process. When several objectives are required for inspection and maintenance strategies, a multi-objective optimisation process needs to be used in order to consider all objectives simultaneously and to rationally select a well-balanced solution. However, as the number of objectives increases, additional computational efforts are required to obtain the Pareto solutions, for decision-making to select well-balanced solutions, and for visualisation of the solutions. This paper presents a novel approach to multi-objective optimisation process of probabilistic service life management with four objectives: minimising the damage detection delay, minimising the probability of failure, maximising the extended service life and minimising the expected total life-cycle cost. With these four objectives, the single, bi-, tri- and quad-objective optimisation processes are investigated using the weighted sum method and genetic algorithms. The objective reduction approach with the Pareto optimal solutions is applied to estimate the degree of conflict among the objectives, and to identify the redundant objectives and minimum essential objective set. As a result, the efficiency in decision-making and visualisation for service life management can be improved by removing the redundant objectives.