On the Robustness of Correlation Network Models in Predicting the Safety of Bridges

Prasad Chetti, Hesham Ali

2024

Abstract

The problem of assessing the safety of bridges and predicting potential unacceptable deterioration levels remains one of the major problems in civil engineering. This work provides a comprehensive evaluation of the Correlation Network Model (CNM) in safety assessment and the prediction of potential safety hazards of bridges. The study applies a population analysis approach to compare individual or cluster performance against a larger set of peers. The CNM outcomes were validated using a linear regression model and a robustness analysis, resulting in a high level of consistency in identifying bridge clusters with different deterioration rates, and thereby identifying clusters with high- risk and low risk bridges. This process allows for the detection of significant parameters affecting bridge deterioration. The findings affirm the CNM’s capability in capturing complex relationships between input parameters and bridge deck conditions, which exceeds the capabilities of simple linear regression models. Furthermore, the CNM’s robustness, under various conditions and assumptions, is confirmed. The study demonstrates the potential of CNM as an effective tool for strategic planning and for efficient resource allocation, enabling focused maintenance and repair interventions on bridge infrastructures that could potentially extend their service life.

Paper Citation

in Harvard Style

Chetti P. and Ali H. (2024). On the Robustness of Correlation Network Models in Predicting the Safety of Bridges. In Proceedings of the 9th International Conference on Complexity, Future Information Systems and Risk - Volume 1: COMPLEXIS; ISBN 978-989-758-698-9, SciTePress, pages 107-113. DOI: 10.5220/0012692800003708

in Bibtex Style

@conference{complexis24,
author={Prasad Chetti and Hesham Ali},
title={On the Robustness of Correlation Network Models in Predicting the Safety of Bridges},
booktitle={Proceedings of the 9th International Conference on Complexity, Future Information Systems and Risk - Volume 1: COMPLEXIS},
year={2024},
pages={107-113},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012692800003708},
isbn={978-989-758-698-9},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 9th International Conference on Complexity, Future Information Systems and Risk - Volume 1: COMPLEXIS
TI - On the Robustness of Correlation Network Models in Predicting the Safety of Bridges
SN - 978-989-758-698-9
AU - Chetti P.
AU - Ali H.
PY - 2024
SP - 107
EP - 113
DO - 10.5220/0012692800003708
PB - SciTePress