SHM strategy optimization and structural maintenance planning based on Bayesian joint modelling

In this contribution, an example is used to illustrate the application of Bayesian joint modelling in optimizing the SHM strategy and structural maintenance planning. The model parameters were evaluated first, using the Markov Chain Monte Carlo (MCMC) method. Then different parameters including expected SHM accuracy and risk acceptance criteria were investigated in order to give an insight on how the maintenance planning and life-cycle benefit are influenced. The optimal SHM strategy was then identified as the one that maximizes the benefit

Imperfect inspection characterization for gamma process structural deterioration model

The deterioration of infrastructure facilities such as bridges has raised concerns over objective methodology to quantify the changes in their safety levels during the service life. In this paper the novel modeling of existing reinforced concrete structures likely future deterioration of strength is of interest. It is assumed that inspection outcomes are the source of data about the deterioration process and should provide help with the updating of the deterioration model with respect to the current structural condition. However, the inspection outcomes are associated with uncertainties that need to be taken into account for deterioration modeling. Sample reinforced concrete structure deterioration process is characterized as a time-dependent, non-negative and incremental process. In this paper we follow recent developments and the continuous gamma process has been adopted to represent the mathematical model of the deterioration process. In the current study two data sources were considered, the expert opinion, which is considered to reflect 'perfect inspection' and data obtained through scheduled inspections as 'imperfect inspection'. This paper reports on early development of the model to quantify the measurement error as inspection uncertainty and to establish continuous gamma process parameters for future deterioration prediction

Performance updating of concrete structures using proactive health monitoring systems: a sytems approach

Uncertainties in predictive models for concrete structures performance can influence adversely the timing of management activities. A methodology has been developed that uses data obtained through proactive health monitoring to increase the confidence in predicted performance by reducing the associated uncertainties. Due to temporal and spatial variations associated with climatic changes, exposure conditions, workmanship, and concrete quality, the actual performance could vary at different locations of the member. In this respect, the use of multiple sensors may be beneficial, notwithstanding cost and other constraints. Two distinct cases are identified for which an updating methodology based on data from multiple sensors needs to be developed. In the first case the interest lies in improving the performance prediction for an entire member (or a structure) incorporating spatial and temporal effects. For this purpose, the member is divided into small zones with the assumption that a sensor can be located in each zone. In the second case, the objective is to minimise uncertainties in performance prediction, or to increase the redundancy of health monitoring systems, at critical locations. The development of updating methodologies for the above-mentioned scenarios is described in this paper. Its implications on the management activities, for example, establishing the timing of principal inspections, are evaluated and discussed.</jats:p

Seismic Reliability Assessment of Aging Highway Bridge Networks with Field Instrumentation Data and Correlated Failures. I: Methodology

The state-of-the-practice in seismic network reliability assessment of highway bridges often ignores bridge failure correlations imposed by factors such as the network topology, construction methods, and present-day condition of bridges, amongst others. Additionally, aging bridge seismic fragilities are typically determined using historical estimates of deterioration parameters. This research presents a methodology to estimate bridge fragilities using spatially interpolated and updated deterioration parameters from limited instrumented bridges in the network, while incorporating the impacts of overlooked correlation factors in bridge fragility estimates. Simulated samples of correlated bridge failures are used in an enhanced Monte Carlo method to assess bridge network reliability, and the impact of different correlation structures on the network reliability is discussed. The presented methodology aims to provide more realistic estimates of seismic reliability of aging transportation networks and potentially helps network stakeholders to more accurately identify critical bridges for maintenance and retrofit prioritization

Investigation of the Spatial Variability of Steel Weight Loss and Corrosion Cracking: A Novel X-ray Technique

The performance of corrosion-affected RC members depends strongly on localized damages of reinforcement. Therefore, modeling the spatial variability of steel corrosion is very important for the assessment of the remaining service life of corroded structures or time for maintenance. To study the changes of spatial variability of steel weight loss over time, a continuous monitoring is necessary. In this paper, a novel procedure of X-ray technique application in monitoring the spatial growth of a corroded bar in a RC specimen is demonstrated along with the digital image processing of X-ray images to estimate the steel weight loss. The relationship of steel weight loss and corrosion cracking is studied at different stages of corrosion. The validity of the estimation method of steel weight loss is also presented. In this study, a novel procedure of X-ray technique application in monitoring the spatial growth of corroded bars in RC specimens is demonstrated along with the digital image processing of X-ray images to estimate the steel weight loss. A single RC beam (80 mm × 140 mm × 1460 mm) reinforced with a longitudinal rebar and stirrups were fabricated for the investigation. The steel corrosion was accelerated via an electrochemical test. The relationship of steel weight loss and corrosion cracking was studied at different stages of corrosion. The validity of the method was also discussed. The outcome of spatial variability of steel weight loss might be used to validate analytical models for estimating non-uniform steel corrosion or incorporated with inspected corrosion levels of in-situ structures for the input data in a predicting model to estimate the long-term structural performance of corroded RC structures

Time-variant performance assessment and improvement of existing bridges

The serviceability and safety of buildings and bridges are expected to be maintained within a reasonable safety level throughout their lifetimes. However, the increase of the applied loads and degradation of structural performances reduce the safety of these structures over time. Therefore, the performance assessment of existing bridges with reliability theories is a worldwide problem in civil infrastructure systems. Theoretically, the bridge reliability, usually expressed by a reliability index, is quantified by comparing the structural capacity (R) with the load effects (Q), using the predefined limit state functions. A limit state function is a mathematical description of a boundary between the desired and undesired performance of a structure. The resistances of structures and live loads on the bridge are none stationary processes, where their statistic parameters, e.g., mean values and deviations, are time variant. Thus, traditional reliability analysis methods cannot be applied to the entire service life of bridges. In this research, the entire life cycle of bridges is treated as the sum of time series. During each time segment, both the load effect Q and the structural capacity R are assumed to be a stationary random process, and are expressed with a certain type of distribution. Thus, after obtaining the reliability probabilities for each time segments, the reliability probability for any length of mean recurrent intervals is obtained by the continued multiplication of the yearly reliability. The extreme structure response which reflects the extreme live load distribution for mean recurrence intervals is derived based on a short-term monitoring of a field bridge. The flexural capacity of bridge girders considering variation of concrete strength, corrosion of steel reinforcements in the concrete and steel components is discussed in details. The flexural capacity of bridge beams can be retrofitted with fiber reinforced polymers (FRP) materials. Finally, the flexural capacity of concrete bridge girders and steel girders strengthened with prestressed carbon fiber reinforced polymers (CFRP) are introduced. The time-variant reliability after the rehabilitation is calculated. The reliability of a bridge keeps decreasing all the time. There is a jump in the reliability when the bridge is strengthened. Rehabilitation of a bridge also slows down the rate of the performance degradation of the bridge

鉄筋腐食の空間変動性を考慮したRC部材の構造性能評価

早大学位記番号:新7806早稲田大

Parameterized Seismic Reliability Assessment and Life-Cycle Analysis of Aging Highway Bridges

The highway bridge infrastructure system within the United States is rapidly deteriorating and a significant percentage of these bridges are approaching the end of their useful service life. Deterioration mechanisms affect the load resisting capacity of critical structural components and render aging highway bridges more vulnerable to earthquakes compared to pristine structures. While past literature has traditionally neglected the simultaneous consideration of seismic and aging threats to highway bridges, a joint fragility assessment framework is needed to evaluate the impact of deterioration mechanisms on bridge vulnerability during earthquakes. This research aims to offer an efficient methodology for accurate estimation of the seismic fragility of aging highway bridges. In addition to aging, which is a predominant threat that affects lifetime seismic reliability, other stressors such as repeated seismic events or simultaneous presence of truck traffic are also incorporated in the seismic fragility analysis. The impact of deterioration mechanisms on bridge component responses are assessed for a range of exposure conditions following the nonlinear dynamic analysis of three-dimensional high-fidelity finite element aging bridge models. Subsequently, time-dependent fragility curves are developed at the bridge component and system level to assess the probability of structural damage given the earthquake intensity. In addition to highlighting the importance of accounting for deterioration mechanisms, these time-evolving fragility curves are used within an improved seismic loss estimation methodology to aid in efficient channeling of monetary resources for structural retrofit or seismic upgrade. Further, statistical learning methods are employed to derive flexible parameterized fragility models conditioned on earthquake hazard intensity, bridge design parameters, and deterioration affected structural parameters to provide significant improvements over traditional fragility models and aid in efficient estimation of aging bridge vulnerabilities. In order to facilitate bridge management decision making, a methodology is presented to demonstrate the applicability of the proposed multi-dimensional fragility models to estimate the in-situ aging bridge reliabilities with field-measurement data across a transportation network. Finally, this research proposes frameworks to offer guidance to risk analysts regarding the importance of accounting for supplementary threats stemming from multiple seismic shocks along the service life of the bridge structures and the presence of truck traffic atop the bridge deck during earthquake events

Health monitoring in proactive reliability management of deteriorating concrete bridges

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