MétaCan
Menu
Back to cohort
Record W2553366519 · doi:10.5539/jmsr.v6n1p15

Novel Process Approach for in-situ Insertion of Functional Elements in RTM-Applications

2016· article· en· W2553366519 on OpenAlexvenueno aff
Mathias Bobbert, Florian Augethaler, Zheng Wang, Thomas Tröster, Gerson Meschut

Bibliographic record

VenueJournal of Materials Science Research · 2016
Typearticle
Languageen
FieldEngineering
TopicManufacturing Process and Optimization
Canadian institutionsnot available
FundersDeutsche Forschungsgemeinschaft
KeywordsMaterials scienceTransfer moldingInterlockConsolidation (business)Fibre-reinforced plasticComposite materialEpoxyTorsion (gastropod)Structural engineeringEngineering

Abstract

fetched live from OpenAlex

Lightweight design in vehicles leads to an increasing use of fibre-reinforced-plastics (FRP). To ensure the possibility of detachable joints in those constructions specific joining technologies have to be developed. Available technologies are not suitable for mass production or are leading to damage in the FRP. The aim of this paper is to show the possibilities and the general feasibility of a new process approach for the application of functional elements in FRP or hybrid materials during resin transfer moulding (RTM) processes. Therefore the movement of the RTM-tool-punch is utilised to produce an interlock between the splay stud and the fibres of the non-consolidated preform. This enables the application of the elements during the RTM-process. The resin infusion leads to the consolidation of the CFRP and a further fixation of the splay stud. Pull-out-tests as well as torsion tests are showing the mechanical performance of the joints.

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: none
Teacher disagreement score0.002
Threshold uncertainty score0.008

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.077
GPT teacher head0.350
Teacher spread0.273 · 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

Citations2
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Materials Science ResearchSame topicManufacturing Process and OptimizationFrench-language works237,207