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Record W2031920963 · doi:10.5539/jmsr.v2n1p1

Prefabricated Thin-walled Structural Elements Made from High Performance Concrete Prestressed with CFRP Wires

2012· article· en· W2031920963 on OpenAlexvenueno aff
Giovanni P. Terrasi

Bibliographic record

VenueJournal of Materials Science Research · 2012
Typearticle
Languageen
FieldEngineering
TopicCivil and Structural Engineering Research
Canadian institutionsnot available
FundersUniversity of Cambridge
KeywordsMaterials scienceLoad bearingPrestressed concreteStructural engineeringStructural materialReinforced concreteBearing (navigation)Composite materialComputer scienceEngineering

Abstract

fetched live from OpenAlex

The innovative combination of prestressed carbon fibre reinforced plastic (CFRP) wires and high performance concrete (HPC) opens up promising possibilities in the design of structural elements and load-bearing structures. This enables manufacturing of thin-walled, lightweight, filigree, fatigue resistant and very durable concrete elements with very low raw-material consumption for use in several market niches of the construction industry. Two or more of these advantages should simultaneously apply to the intended application for justifying the higher material costs of prestressing and passive CFRP reinforcements in comparison to prestressing and reinforcing steel. Significant economic benefits are to be found in the areas of maintenance of the load-bearing elements as well as their transport and installation. Recently, a first commercial breakthrough of this novel technique was achieved in the structural and architectural field with the realisation of two large building façades in Zurich, Switzerland using a total of 3000 m prestressed self compacting concrete profiles. In this paper design and experimental validation details as well as several field projects are described.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.028
GPT teacher head0.297
Teacher spread0.268 · 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 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

Citations27
Published2012
Admission routes1
Has abstractyes

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