Studies to Correlate Actual and Expected Behavior of Tall Buildings Under Wind Action
Bibliographic record
Abstract
The design of tall buildings is predominantly governed by the need to provide adequate strength and stiffness against lateral dynamic forces induced by wind, and to satisfy stability and serviceability conditions. While serviceability requirements are fulfilled by limiting lateral displacements (drifts) to maintain the integrity of architectural elements such as cladding and partitions; the minimization of perceptible accelerations assures occupant comfort. These conditions are directly affected by the dynamic and aerodynamic characteristics of the building and the severity of the local wind climate. The design process involves the selection of an appropriate structural system, and the evaluation of that system under design wind environments utilizing code, analytical methods, and wind tunnel testing. This may be an iterative process for exceptionally tall, slender, or unusual building forms. Interestingly enough, while tall building structures serve as one of our most vital constructed facilities, the design process is based almost solely on the information provided by analytical and scaled models. Understandably, while full scale models are not feasible, considering their sheer size and cost, monitoring the performance of actual structures is paramount and must be undertaken following construction as a means of verification and improvement of current design practices and analytical models.
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 | 0.005 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".