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Record W4387309213 · doi:10.56330/kltb8950

Quay Quarter Tower, Sydney – conservation, life extension and upgrade using live digital twinning

2023· article· en· W4387309213 on OpenAlexaboutno aff
Nimal Perera, Murray Middleton, Reza Hassani, Marco Ficca

Bibliographic record

VenueThe Structural Engineer · 2023
Typearticle
Languageen
FieldEngineering
TopicBIM and Construction Integration
Canadian institutionsnot available
Fundersnot available
KeywordsTowerUpgradeQuarter (Canadian coin)ReuseIntervention (counseling)Architectural engineeringStiffnessEngineeringCivil engineeringComputer scienceStructural engineeringGeographyWaste management

Abstract

fetched live from OpenAlex

This article describes the feasibility studies, investigations, analysis, structural health monitoring, digital twinning, and structural adequacy verification of the repurposed 50-storey Quay Quarter Tower in Sydney, Australia. The design life of the retained building was extended by 50 years with minimum structural intervention. The adaptive reuse increased the net lettable area from 45 000m2 to 90 000m2. The 45-year-old retained components provided structural integrity for the accelerated construction programme and 80% of the lateral strength and stiffness with minimum intervention for the upgraded building. The digital twinning technology facilitated safe and speedy construction and conserved 12 079t of embodied carbon, with a carbon footprint for the gross internal area of 247kgCO2e/m2. The innovative engineering processes enabled the client, AMP, to achieve its aspirations for a unique world-class commercial building using a comprehensive approach to reducing embodied and operational carbon.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.323
Threshold uncertainty score0.456

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 head0.014
GPT teacher head0.217
Teacher spread0.203 · 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 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

Citations0
Published2023
Admission routes1
Has abstractyes

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