MétaCan
Menu
Back to cohort
Record W3016867678 · doi:10.1002/tal.1743

Seismic design of outrigger systems using equivalent energy design procedure

2020· article· en· W3016867678 on OpenAlexafffundabout
T.Y. Yang, Jeremy Atkinson, Lisa Tobber, Dorian P. Tung, Bob Neville

Bibliographic record

VenueThe Structural Design of Tall and Special Buildings · 2020
Typearticle
Languageen
FieldEngineering
TopicSeismic and Structural Analysis of Tall Buildings
Canadian institutionsRead Jones Christoffersen (Canada)University of British Columbia
FundersNational Natural Science Foundation of ChinaCanadian Institute of Steel Construction
KeywordsOutriggerStructural engineeringShear wallEngineeringSeismic analysisJoint (building)Margin (machine learning)Civil engineeringComputer science

Abstract

fetched live from OpenAlex

Summary An outrigger system is an effective structural scheme that is commonly used in high‐rise construction to increase the stiffness of concrete core walls and to reduce the moment demand within the walls. Despite the on‐going use of outrigger systems around the world, a formal seismic design procedure is yet available. This paper presents an equivalent energy design procedure (EEDP) to design outrigger systems for seismic applications. Three prototype outrigger‐wall buildings of various heights are designed for Vancouver, Canada. Detailed finite element models are developed to assess the seismic performance of the prototype buildings and to assess the safety using the FEMA P695 methodology. The result shows that EEDP is an efficient method to design outrigger systems which results in structures that can achieve sufficient margin of safety against collapse and satisfy multiple performance objectives at different seismic hazard levels.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.033
GPT teacher head0.219
Teacher spread0.186 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations27
Published2020
Admission routes3
Has abstractyes

Explore more

Same venueThe Structural Design of Tall and Special BuildingsSame topicSeismic and Structural Analysis of Tall BuildingsFrench-language works237,207