Bibliographic record
Abstract
Outrigger systems are an effective structural scheme that is commonly used in high-rise construction to increase stiffness and distribute the moment demand within the core to the exterior columns. Despite the on-going use of outrigger structural systems around the world, a formal seismic design procedure for outrigger system is missing. This thesis presents an equivalent energy-based design procedure (EEDP) to design outrigger systems for seismic applications. Using the concept of an energy balance, elastic single-degree of freedom systems are equated to equivalent nonlinear systems, and plastic mechanisms are used to derive design forces for the outrigger systems. EEDP allows engineers to design the outrigger-wall buildings to achieve different performance objectives at different seismic hazard levels, which is desirable for creating earthquake-resilient buildings. Three prototype outrigger-wall buildings of various heights were designed using the proposed procedure for a hypothetical site in Vancouver, Canada. Detailed finite element models were developed using OpenSees to assess the seismic performance of the prototype buildings. The results of the nonlinear time history analyses show that the prototypes can meet the performance objectives specified during the design procedure. Lastly, incremental dynamic analyses were conducted using the FEMA P695 methodology to quantify the seismic safety of outrigger systems designed using EEDP. The results show that the proposed EEDP is an effective method to design outrigger systems, where the structure can achieve sufficient margin of safety against collapse and satisfy multiple performance objectives at different hazard levels without iteration.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".