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Record W4407051340 · doi:10.1016/j.jobe.2025.111968

Assessing the environmental impact of building houses in remote areas: 3D printing vs. traditional construction techniques

2025· article· en· W4407051340 on OpenAlexaffabout
Mohammad Abu Hasan Khondoker, Golam Kabir

Bibliographic record

VenueJournal of Building Engineering · 2025
Typearticle
Languageen
FieldEngineering
TopicInnovations in Concrete and Construction Materials
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsArchitectural engineeringEnvironmental impact assessmentCivil engineeringBuilding constructionEnvironmental scienceConstruction engineeringEngineeringForensic engineeringStructural engineering

Abstract

fetched live from OpenAlex

The building sector holds a pivotal position in influencing our artificial landscape, emphasizing the pressing need to embrace green and inventive approaches, equipment, and instruments to mitigate its ecological impacts. In this study, a comprehensive evaluation of environmental burdens associated with construction methods in the remote area of Attawapiskat, a First Nation community located in northern Ontario, Canada, is carried out. The study includes a detailed comparison of the sustainability between 3D printing technology and conventional construction approaches. Six distinct scenarios for comparing 3D printing technology and conventional construction in Attawapiskat were identified. Subsequently, a cradle-to-gate life cycle analysis (LCA) was conducted for each scenario, facilitated by SimaPro software. The environmental impact across various categories was then compared. Ultimately, sensitivity analyses were employed to interpret the results, assessing the influence of variations on our findings. Our study highlights a substantial environmental improvement when using Geo-polymer concrete in 3D printing in construction compared to conventional methods. To boost 3D printing's eco-friendliness further, we advocate local material sourcing to cut transportation emissions and reduce the carbon footprint, ultimately advancing sustainability in construction. • Comprehensive evaluation of environmental burdens associated with construction methods in remote area of Attawapiskat. • Comparison of the sustainability between 3D printing technology and conventional construction approaches. • Analyze six distinct scenarios for comparing 3D printing technology and conventional construction in Attawapiskat. • Explore the benefit of using Geo-polymer concrete in 3D printing in construction compared to conventional methods. • Provide suggestions to reduce transportation emissions and carbon footprint to boost 3D printing's eco-friendliness.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.216
Threshold uncertainty score0.429

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0020.000
Open science0.0000.001
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 head0.011
GPT teacher head0.263
Teacher spread0.252 · 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 designObservational
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

Citations11
Published2025
Admission routes2
Has abstractyes

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