Abstract
Four Bayesian network models (SB-1, SB-2a, SB-2b, SB-2c) for assessing reinforcement corrosion probability in concrete were compared. Seven corrosion parameters were considered: potential; resistivity; chlorides; pH; corrosion current; charge transfer resistance; cracking. Monte Carlo simulations for three threat scenarios (low, medium, high) demonstrated the superiority of model SB-2c – highest accuracy and flexibility. Model SB-2c was identified as optimal for corrosion diagnostics of reinforced concrete.
| Translated title of the contribution | Wpływ struktury sieci bayesowskich na ocenę zagrożenia korozją stalowego zbrojenia w betonie |
|---|---|
| Original language | English |
| Pages (from-to) | 1-10 |
| Number of pages | 10 |
| Journal | Materialy Budowlane |
| Volume | 636 |
| Issue number | 8 |
| DOIs | |
| Publication status | Published - 2025 |
Keywords
- Bayesian networks
- concrete structures
- corrosion of reinforcement
- criteria for assessing corrosion in reinforced concrete
- diagnostics
ASJC Scopus subject areas
- Chemical Engineering (miscellaneous)
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