On shear in members without stirrups and the application of energy‐based methods in light of 30 years of test observations
Bibliographic record
Abstract
Abstract In a recent paper in Structural Concrete, the authors Dönmez and Bažant explain that the theoretical background of the Model Code 2010 equations for one way and punching shear are not sufficiently grounded in theory and should instead use an energy‐based size effect law in their formulation to match behavior. To support this claim, finite element simulations were presented. In this paper the basic assumption that an energy‐based method must govern the shear failure of beams without stirrups is questioned. These questions are shown to be based on the hardening behavior of aggregate interlock tests and the inability for slip strains to localize during shear failure. In addition to these theoretical arguments finite element analyses were conducted with a constitutive model that is energy‐based but that also does an appropriate job at modeling aggregate interlock, an aspect that appears to be lacking in the analyses of Dönmez and Bažant. These new results are shown to better model the test results and confirm that aggregate interlock is important in explaining shear strength and therefore the size effect in shear for slender members. As such any concerns about the safety of the Model Code shear equations appear unwarranted.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".