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Record W4387469122 · doi:10.1061/ppscfx.sceng-1278

Recent Development of 3D-Printing Technology in Construction Engineering

2023· article· en· W4387469122 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePractice Periodical on Structural Design and Construction · 2023
Typearticle
Languageen
FieldEngineering
TopicInnovations in Concrete and Construction Materials
Canadian institutionsWestern University
Fundersnot available
KeywordsConstruction engineering3D printingEngineeringCivil engineeringMechanical engineering

Abstract

fetched live from OpenAlex

The current construction industry for civil and structural engineering is considered to be one of the growing industries in the world. With the push toward a more digitized industry, emerging trends such as additive manufacturing and the use of three-dimensional (3D) printing technology, along with consumer demand, are resulting in automated development with multiple benefits. Successful applications for small-scale construction projects that have implemented 3D printing have shown improvements in cost, production time, and design freedom and complexity. However, for large-scale applications, there are various limitations and factors hindering the adoption of additive manufacturing technologies. In this paper, a systematic literature survey of recent 3D printing technologies was conducted specific to the area of construction engineering, and the various techniques, materials, software, and technical and nontechnical aspects were analyzed. The key applications and their benefits are outlined, and their potential for large-scale applications is articulated. Future research areas for these components are suggested to strengthen the technical readiness and feasibility of adopting 3D printing technology in construction engineering and industries.

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.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.901
Threshold uncertainty score0.862

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.019
GPT teacher head0.258
Teacher spread0.239 · 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