Reliability-Based Design Aid for Evaluation and FRP Retrofit of Existing RC Bending Members by Considering Project-Specific Conditions
Bibliographic record
Abstract
This paper presents the formulation of a reliability-based design aid to assess the need for strengthening existing reinforced concrete (RC) flexural members and optimize the retrofit using externally bonded fiber-reinforced polymers (FRPs) if the member is deficient. The design aid consists of evaluation charts and a simplified formula calibrated using reliability theory to consider the effect of satisfactory past performance of the assessed structure in terms of load type and magnitude seen during the service life and the redundancy of the considered structural system. The design aid was calibrated based on the design procedure given in the American Concrete Institute ACI PRC-440.2-23, “Guide for the design and construction of externally bonded FRP systems for strengthening concrete structures,” and the Canadian Standards Association CSA S806-12, “Design and construction of building structures with fibre-reinforced polymers,” and presented in a user-friendly manner to be used by engineers experienced in the assessment and retrofit of structures. The input of the design aid consists of the member’s unstrengthened utilization ratio (demand-to-capacity) and the number of hinges to form a mechanism, while the output is the required flexural resistance to upgrade the member capacity. Numerical examples of using the design aid in structural evaluation projects are presented, highlighting the significant savings in the required amount of FRP to retrofit deficient members compared to the conventional structural evaluation method.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".