Numerical analysis of structural components in power generation facilities
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
The analysis of large civil structures made of composite materials, like brick masonry and/or heavily reinforced concrete, should best be conducted at a macro-scale. In this case, the material can be described as a continuum whose average properties are identified at the level of constituents taking into account their geometric arrangement. For structural masonry, several different approximations have been developed for assessing the average properties. Those include the micropolar Cosserat continuum models (e.g. Sulem and Muhlhaus [1], Masiani and Trovalusci [2]) as well as the estimates based on the theory of homogenization for periodic media (e.g., Anthoine [3-4]). In addition, a significant work has also been undertaken with regards to the development of phenomenologicaly-based macroscopic failure criteria. Examples include the studies of Lourenco et al. [5], Raffard et al. [6] and Ushaksaraei and Pietruszczak [7]. For heavily reinforced concrete structures, such as hydraulic or nuclear ones, the presence of reinforcement cannot be modeled in a discrete way, as this would be beyond the capabilities of modern day computers. Thus, the material should also be considered as a composite medium comprising the concrete matrix and a set of families of reinforcement. NUMERICAL ANALYSIS OF STRUCTURAL COMPONENTS IN POWER GENERATION FACILITIES
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) | 0.001 | 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