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Record W6969363208 · doi:10.5445/ir/1000151130

Fatigue behavior of continuous-discontinuous sheet molding compounds

2022· article· en· W6969363208 on OpenAlexaboutno aff

Bibliographic record

VenueRepository KITopen (Karlsruhe Institute of Technology) · 2022
Typearticle
Languageen
FieldEngineering
TopicComposite Material Mechanics
Canadian institutionsnot available
Fundersnot available
KeywordsSheet moulding compoundMolding (decorative)BendingFiberUltimate tensile strengthGlass fiberCore (optical fiber)Composite number

Abstract

fetched live from OpenAlex

Sheet molding compound (SMC) composites have been well-established as nonstructural and semi-structural components in vehicles due to their high lightweight potential. Over the past decade, increasing need for further vehicle weight reduction has fueled endeavors to further improve mechanical properties of SMC and thereby to expand their suitability as structural components. One promising approach to achieve this goal is the combination of discontinuous glass fiber SMC with local continuous carbon fiber reinforcement, which is currently being investigated by the German-Canadian research training group GRK 2078. Such hybrid continuous-discontinuous composites enable the production of components with excellent mechanical properties while maintaining the advantages of the SMC process including geometric flexibility, short cycle times and cost efficiency. However, several factors prevent the exploitation of the composite’s full potential. Major obstacles for a safe and efficient application of continuous-discontinuous SMC are the lack of knowledge regarding their fatigue behavior and about uncharted effects of hybridization on damage behavior under cyclic loading conditions. This thesis describes a systematical analysis of the fatigue behavior of continuous-discontinuous SMC both under cyclic tensile and bending loads at different temperatures and frequencies. The hybrid composite, which consists of a discontinuous glass fiber SMC core and unidirectional carbon fiber SMC face plies, shows significantly higher fatigue resistance compared to discontinuous SMC without continuous reinforcement. The effect of hybridization is more pronounced under cyclic loading than under monotonic loading, which is a result of distinct damage mechanisms acting at distinct applied stresses. The mechanical behavior of continuous-discontinuous SMC is dominated by the continuous plies at high stresses and by the discontinuous ply at low stresses. The effect of hybridization is particularly distinctive under cyclic bending load on account of the composite’s sandwich-like structure. In addition, relative stiffness degradation of continuous-discontinuous SMC is less pronounced over a larger loading period compared to discontinuous SMC. While damage evolution within the discontinuous SMC ply remains largely unaffected by hybridization, the continuous SMC plies are enabled to withstand significantly higher cyclic loads than continuous SMC specimens that are not a part of a hybrid composite. When using a cross-ply instead of a unidirectional continuous reinforcement, early initiation of cracks in the 90° ply at comparatively low stresses leads to rapidly growing delaminations and large cracks in the discontinuous SMC ply. Consequently, the effect of hybridization under cyclic loading is less pronounced. While continuous-discontinuous SMC is largely insensitive to a change in frequency, enhanced temperature leads to early failure of the unidirectional ply on the compression loaded side, which results in a significant decrease of fatigue life.

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 head0.012
GPT teacher head0.222
Teacher spread0.211 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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