Background to the <i>fib</i> Model Code 2010 shear provisions – part I: beams and slabs
Bibliographic record
Abstract
Abstract This paper examines the evidence for the one‐way shear model developed for the fib Model Code for Concrete Structures 2010 and provides examples of its application. For the design and analysis for shear, for members with and without shear reinforcement, the fib Model Code 2010 procedures have been developed from physical‐mechanical models that are based on observed behaviour at the meso‐scale level; they represent a significant advance over previous standardized empirical methods. In addition, an approach referred to as “level of approximation” (LoA) is incorporated where advanced models are simplified in a consistent and conservative way such that the designer can select the effort needed to justify their design. To illustrate the practical use of the models and the LoA approach, two examples are presented. The first is a deck slab of a cut‐and‐cover tunnel where design and possible refinements are discussed for a given configuration. The second is a prestressed concrete bridge girder, which is considered for the cases of design and for the analysis of an existing structure.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.021 | 0.010 |
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".