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Record W7127987248 · doi:10.22260/crc-csce-2025/0200

Comprehensive Life Cycle Assessment of Building Materials: A Comparative LCA of Hybrid Steel/Timber Structure with Reduced Timber Design

2025· article· W7127987248 on OpenAlexfundaboutno aff
Abdulrahman Sati, Thomas Froese, Mohammed A. Alsati

Bibliographic record

Venuenot available
Typearticle
Language
FieldEnvironmental Science
TopicEnvironmental Impact and Sustainability
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsLife-cycle assessmentComponent (thermodynamics)Production (economics)Process (computing)

Abstract

fetched live from OpenAlex

In Canada, it has been found that the construction sector contributes significantly to greenhouse gas emissions.To mitigate this impact, timber-based constructions have become increasingly favored due to their lightweight characteristics, expedited assembly, and environmental advantages.This research seeks to objectively validate the environmental impacts of hybrid structures through a case study building in Victoria, Canada.The focus of this study would be mainly to compare two different proposed designs for the same building.Design 1 evaluates the environmental impact of a structure predominantly composed of timber, whereas Design 2 substitutes glulam components (for instance, columns and beams) with steel elements whilst preserving a uniform floor configuration.Employing Athena software, the research quantifies the ecological footprints and determines that Design 2 exhibits a 5% elevated Global Warming Potential in comparison to Design 1.The results showed that Design 1, which contains a greater mass of timber, performed better across the entire life cycle of the project.The most significant difference between the two designs is at the beyond-building life stage (D), where Design 1 is projected to recover 197,000 kg CO₂ eq more than Design 2. These results indicate the necessity for further investigation into optimized hybrid structures that balance carbon reduction, resource efficiency, and long-term sustainability within the construction sector.

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)0.001
metaresearch head score (Gemma)0.001
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: Empirical
Teacher disagreement score0.433
Threshold uncertainty score0.862

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.313
Teacher spread0.292 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

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