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Record W2940064139 · doi:10.29173/mocs21

Polymer-based Modular Residential Building Design and Construction äóñ A new Paradigm?

2016· article· en· W2940064139 on OpenAlexaffvenue
Andy H. Wong, Pierre Mertiny

Bibliographic record

VenueModular and Offsite Construction (MOC) Summit Proceedings · 2016
Typearticle
Languageen
FieldMaterials Science
TopicNatural Fiber Reinforced Composites
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsModular designSandwich-structured compositeSandwich panelRigidity (electromagnetism)Embodied energyArchitectural engineeringComposite numberEngineeringMaterials scienceComputer scienceComposite material

Abstract

fetched live from OpenAlex

The onsite wood frame method of constructing new buildings has been the norm for residential and basic commercial structures for more than a century. In this review study, we consider investment into plastic composite structures to supplement or replace wood frame home construction. Previous developments in this field often centralize on using a classic composite sandwich panel design: a polymer-based core material adjoined to layers of synthetic fiber-reinforced polymer (e.g. fiberglass). The core of the composite panels is designed to meet demands toward low cost, light weight, and structural rigidity. Different varieties of plastics, including thermosets and thermoplastics, are discussed. Factors that need to be considered in the fabrication of composite modular residential buildings include, but are not limited to, energy consumption (both in building heating and cooling, and fabrication energy usage), fire resistance, resource use, environmental impact, human impact, and cost. Basic fabrication principles and techniques for composite modular panels are reviewed, wherein mechanical and electrical work can be incorporated into the building during panel manufacturing. Methods in which panels can be fabricated in high volumes that enable economies of scale are described. Thusly, recent progress in the application of plastics forming and machining that is applicable to the construction industry, and the feasibility of this type of residential construction are elucidated and discussed holistically.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
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 studies0.0000.001
Scholarly communication0.0010.001
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 head0.216
Teacher spread0.205 · 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 designBench or experimental
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

Citations1
Published2016
Admission routes2
Has abstractyes

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