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Record W1635655340

System Identification of Heritage Court Tower Using Stochastic Subspace Method, #407

2000· article· en· W1635655340 on OpenAlexaboutno aff
Jyrki Kullaa

Bibliographic record

VenueProceedings of IMAC-XVIII: A Conference on Structural Dynamics · 2000
Typearticle
Languageen
FieldEngineering
TopicStructural Health Monitoring Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsSubspace topologyModalIdentification (biology)TowerModal analysisStructural engineeringSystem identificationOperational Modal AnalysisVibrationComputer scienceSet (abstract data type)MathematicsEngineeringAcousticsArtificial intelligenceData miningPhysicsFinite element method
DOInot available

Abstract

fetched live from OpenAlex

Modal parameters from a 15-story reinforced concrete shear core building were identified. The building, known as the Heritage Court Tower, is located in Vancouver, Canada. Ambient vibration measurements were performed by the University of British Columbia and the data was made freely available for comparative analysis of identification methods. In the present study a stochastic subspace system identification method was used to define the modal properties of the structure. This time-domain identification method is based on the state space model and does not use iterative search. Important parameters in the stochastic subspace method are model order and auxiliary order, which must be optimised to get the most reliable model. Different model orders were compared using the stabilisation diagram. Eleven modes below 12 Hz were found. The first seven modes below 7 Hz were found to be clearly stabilised. The first three are closely spaced between 1.23 and 1.46 Hz and correspond to the first two bending modes and the first torsional mode. Different modal parameters were extracted from each measurement set-up, but the discrepancy was not large.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.930
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.021
GPT teacher head0.300
Teacher spread0.279 · 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.

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

Citations1
Published2000
Admission routes1
Has abstractyes

Explore more

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