Staged‐construction analysis of high‐rise buildings: A literature review and future perspectives
Bibliographic record
Abstract
Summary Staged‐construction analysis (SCA) has recently become a noticeable trend for estimating the design forces and deformations for high‐rise buildings (HRBs). SCA is a nonlinear step‐by‐step analysis that simulates the construction activities and conditions. It is a numerical simulation that considers loading history during construction, time‐dependent material behavior, environmental conditions, and any special measures taken by contractors to limit differential axial shortening during the construction process. However, building codes and guidelines do not provide adequate provisions that clearly identify how to approach this type of analysis. This paper presents a comprehensive state‐of‐the‐art review on how SCA was previously adopted in theoretical research and how it was applied in real buildings. It begins by critically reviewing different research work on SCA. Afterward, the paper puts forward the recent fundamentals of conducting SCA. Then, a series of studies about verifying SCA as practical analysis procedure using field measurements are then presented. In addition, the current paper reviews how SCA can specifically affect post‐tension slabs. Based on this review, several recommendations are provided to help in shaping the future code provisions, add to the development of recent practices, and inspire future research. The conducted review concludes that more investigations should be performed to better understand the effect of considering SCA on the deformations and design forces during HRB analysis.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".