MétaCan
Menu
Back to cohort
Record W2551257298

DESIGN OF SYDNEY OLYMPIC STADIUM FOR MITIGATION OF CROWD-INDUCED VIBRATION

2007· article· en· W2551257298 on OpenAlexaboutno aff
Graham Brown, Peter Erdmanis, Ross Emslie, David G. Hanson

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicStructural Engineering and Vibration Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsStadiumVibrationEngineeringStructural engineeringFinite element methodArchitectural engineeringComputer scienceAcousticsPhysics
DOInot available

Abstract

fetched live from OpenAlex

Increasingly, crowd-induced vibration is seen as an important issue in the design of assembly occupancies, especially large stadia, which are used for pop concerts, involving rhythmic activity, as well as sporting events. This paper presents an overview of an investigation undertaken by Sinclair Knight Merz into the response of the Sydney Olympic Stadium due to crowd-induced vibration. The first part of the investigation involved the construction of a finite element model of the stadium which was subjected to dynamic loading to simulate the likely response of the structure to concert loads. The vibration responses were evaluated in terms of design specifications based on the Canadian Building Code. The results of these simulations, and a review of crowd-induced vibration in the literature, were used to develop the original stadium design to reduce predicted vibration responses. The design approach, together with the final design and its implementation are described in the paper. The second part of the investigation involved the subsequent testing of the structure during a concert performance. Accelerations were recorded at ten locations on the structure over the duration of the concert and the structure was shown to meet the performance requirements for crowd-induced vibration.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.848
Threshold uncertainty score0.280

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.017
GPT teacher head0.237
Teacher spread0.220 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations0
Published2007
Admission routes1
Has abstractyes

Explore more

Same topicStructural Engineering and Vibration AnalysisFrench-language works237,207