Application of Intensifying Wind Analysis in Time History Analysis of Tall Buildings
Bibliographic record
Abstract
Abstract The wind phenomenon has always caused significant damage to structures. Suffering from extensive damage and loss over the years has led researchers to establish the novel science of wind engineering. Wind engineering references introduce wind as an intricate dynamic and random phenomenon and encourage engineers to familiarize themselves with its exact effects on structures by utilizing the latest methods of structural analysis, such as time history analysis. In this research, the idea of a new method for time history analysis of tall buildings against the wind is proposed. In this method, the purpose is to determine the responses of the structure against any wind of any intensity and return period by performing a single analysis. The purpose is achieved by generating and utilizing some special functions called intensifying wind records. The aforementioned process paves the way for a comprehensive and accurate assessment of the structure, and for performing the efficient performance-based design which is developing at a galloping pace in recent years. In order to perform the wind time history analysis, it is indispensable to generate and assign wind speed records to the structure. After performing a time-consuming process of artificially generating and assigning unique wind records to each node of the tall structure in the software and performing a time history analysis under the simultaneous effect of all of them, the response of the structure subjected to a specific wind with a specified mean speed and return period will be obtained. It goes without saying that in the performance-based wind design for instance, determining the responses and behavior of the structure under the influence of various winds with different return periods is required. In this case, there is no other way but to repeat the whole illustrated process. In order to solve this problem, the present study assesses wind records through a creative viewpoint and by combining several complicated methods of wind record production obtains intensifying wind records, simplifies the difficult problem of record generation.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| 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 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".