Authors:
Prasad Chetti
1
and
Hesham Ali
2
Affiliations:
1
Northwest Missouri State University, U.S.A.
;
2
University of Nebraska at Omaha, U.S.A.
Keyword(s):
Bridge Safety, National Bridge Inventory, Correlation Network Model, Deterioration Rates, Risk Management.
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 reg
ression 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.
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