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Record W4308864548 · doi:10.5267/j.esm.2022.9.001

The effect of stacking sequence and fiber orientation on tensile and flexural strength of fiber reinforced composite fabricated by VARTM process

2022· article· en· W4308864548 on OpenAlexvenueno aff
Himanshu V. Patel, Harshit K. Dave

Bibliographic record

VenueEngineering Solid Mechanics · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicErosion and Abrasive Machining
Canadian institutionsnot available
Fundersnot available
KeywordsMaterials scienceComposite materialFlexural strengthAramidUltimate tensile strengthComposite numberStackingFiberEpoxy

Abstract

fetched live from OpenAlex

In this study, Carbon, Glass, and Aramid fiber reinforced composite and their hybridized forms were fabricated using five different stacking sequences of the fabrics. Using the Vacuum Assisted Resin Transfer Molding (VARTM) procedure, epoxy resin was injected into these fabrics and allowed to cure at room temperature. From these five stacking sequences, a standard specimen with four different orientations viz. 0/90°, 15/75°, 30/60°, 45/-45° orientations were obtained using the Abrasive Water Jet Machining(AWJM) Process. The influence of stacking order and fiber orientation on tensile and flexural properties of composite was investigated. From the result of tensile testing, the highest and lowest tensile strength values were observed for neat carbon fiber reinforced composite at 0/90° orientation and at 45/-45° orientation respectively. The highest flexural strength was achieved in a hybrid combination of two layers of carbon, glass and aramid fabric for 0/90° whereas the lowest flexural strength was found in glass reinforced composite for the 45/-45° orientation.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.202
Threshold uncertainty score0.300

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 studies0.0000.000
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 head0.005
GPT teacher head0.230
Teacher spread0.225 · 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.

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

Citations5
Published2022
Admission routes1
Has abstractyes

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