Utilization of Nonlinear Finite Elements for the Design and Assessment of Large Concrete Structures. II: Applications
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This second-part article presents applications of advanced nonlinear finite-element analysis for the design of large reinforced-concrete structures. Because shear and the size effect are fundamental aspects of these structures, the first section of this paper is devoted to the prediction of shear failure for very large members more than 3 m deep. It is shown that the tendency of shear strength is much less sensitive to size effects for very large members than the predictions of some design code equations. Applications to the draft tube complex structure are then presented in a second part. A comparison of cracking patterns with an existing powerhouse is performed at the service level. It is shown that thermal effects have an important effect on the final cracking pattern. The draft tube model is then analyzed up to failure. Following a new design methodology proposed by the authors in a previous paper, and using the model error properties computed in part 1, the global resistance factor is computed for the ultimate level. The effects of temperature, nominal shear reinforcement, and lateral confinement are discussed.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it