On reliability assessment of existing structures

Diamantidis, Dimitris; Tanner, Peter; Holicky, Milan; Madsen, Henrik O.; Sykora, Miroslav

doi:10.1016/j.strusafe.2024.102452

Structural Safety

2025

DOI: 10.1016/j.strusafe.2024.102452

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On reliability assessment of existing structures

Dimitris Diamantidis,

Peter Tanner,

Milan Holicky

et al.

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Cited by 3 publications

References 28 publications

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Reliability‐based Allowances of Corrosion Losses for Weathering Steel Bridges

Sykora,

Kreislova,

Markova

2024

ce papers

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Low demands on maintenance and 100% recyclability cause the growing popularity of weathering steel bridges worldwide. Recent experimental results made it possible to derive generic probabilistic models describing long‐term corrosion losses for various types of weathering steels and exposures. In the contribution, these probabilistic models are applied in reliability assessment. For representative structural members and failure modes, the material allowances for the loss of thickness are derived to achieve a specified target reliability in exposures corresponding to Corrosivity Categories C2 and C3. Numerical analysis reveals that the allowances recommended by the ECCS guideline are generally conservative. For larger sections exposed in C2, a “no allowance” strategy might even be considered. For C3, design allowance of about 0.5‐0.6 mm is then determined by the probabilistic approach.

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Reliability‐based Allowances of Corrosion Losses for Weathering Steel Bridges

Sykora,

Kreislova,

Markova

2024

ce papers

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Target reliabilities for heritage structures derived from cost optimization

Van Den Hende,

Caspeele,

Sykora

et al. 2024

Structural Concrete

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In the last decade, structural reliability and safety efforts have been oriented toward the assessment of existing structures and the development of related target reliability levels. However, up‐to‐date there is no consensus on the reliability philosophy that should be followed when considering the assessment of heritage structures, and the level of reliability which is appropriate to them. In this study, a framework is proposed which derives new values for the economically optimal target reliability for the upgrade of a structure, , and the reliability threshold for upgrade, , considering the cultural heritage value of the structure. The total expected life cycle cost is minimized, assuming that the structure is given up after collapse, as heritage value is typically lost after failure. The target reliability values are based on three main parameters: the relative annual benefit of using the structure (affected by its heritage value), the relative cost of failure and the relative cost of increasing the reliability. Target reliability values are proposed specifically for heritage structures, considering a range of the main input parameters.

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Behavior Expectation‐Based Anomaly Detection in Bridge Deflection Using AOA‐BiLSTM‐TPA: Considering Temperature and Traffic‐Induced Temporal Patterns

Qu,

Xia,

Sun

et al. 2024

Structural Control and Health Monitoring

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In the realm of structural health monitoring (SHM), understanding the expected behavior of a structure is vital for the timely identification of anomalous activities. Existing methods often model only the physical quantities of monitoring data, neglecting the corresponding temporal information. To address this, this paper presents an innovative deep learning framework that synergistically combines a BiLSTM model, fortified by a temporal pattern attention (TPA) mechanism, with time-encoded temperature and traffic-induced deflection-temporal patterns. The arithmetic optimization algorithm (AOA) is employed for optimal hyperparameter tuning, and incremental learning was implemented to enable real-time updates of the model. Based on the proposed framework, an anomaly detection method was subsequently developed. This method is bidirectional: it uses quantile loss to provide expected ranges for structural behavior, identifying isolated anomalies, while the windowed normalized mutual information (WNMI) based on multivariate kernel density estimation (MKDE) helps detect trend variability caused by decreases in structural stiffness. This framework and the anomaly detection method were validated using data from an operational cable-stayed bridge. The results demonstrate that the method effectively predicts structural behavior and detects anomalies, highlighting the critical role of temporal information in SHM.

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On reliability assessment of existing structures

Cited by 3 publications

References 28 publications

Reliability‐based Allowances of Corrosion Losses for Weathering Steel Bridges

Reliability‐based Allowances of Corrosion Losses for Weathering Steel Bridges

Target reliabilities for heritage structures derived from cost optimization

Behavior Expectation‐Based Anomaly Detection in Bridge Deflection Using AOA‐BiLSTM‐TPA: Considering Temperature and Traffic‐Induced Temporal Patterns

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