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Record W4281682729 · doi:10.24904/footbridge2022.199

Sustainability and Visual Considerations for Footbridges Designed with Stainless Steel

2022· article· en· W4281682729 on OpenAlexaboutno aff
Juan A. Sobrino

Bibliographic record

VenueFootbridge 2022, Madrid: Creating Experience · 2022
Typearticle
Languageen
FieldEngineering
TopicStructural Engineering and Vibration Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsCorrosionSustainabilityDurabilityEngineeringDeconstruction (building)Capital costMaterials scienceCivil engineeringMetallurgyComposite materialWaste management

Abstract

fetched live from OpenAlex

<p>Despite the impact that stainless steel has had in the architecture, industrial applications and multitude of consumer products for more than 50 years, its presence in civil engineering structures is recent. Some interesting structures, mainly pedestrian bridges, have been built in the last two decades. Stainless steel creates a light, strong, corrosion-resistant, and elegant structure with premium aesthetics. The extended structure life-cycle typically offsets the higher capital cost of stainless steel due to the increased corrosion resistance and reduced maintenance, which in turn reduces the overall cost of ownership. This represents a net advantage for the asset owner and improves safety and long-term durability. Stainless steel is recognized as a sustainable material with a lower environmental impact, lightweight construction, and low maintenance and deconstruction cost over the bridge lifespan. Stainless steel is one of the highest recycling rates of any material.</p><p>This paper provides an overview of the sustainability and visual considerations for footbridges designed with stainless steel through a recently built example: the Garrison Crossing in Toronto.</p>

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.171
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.011
GPT teacher head0.250
Teacher spread0.240 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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