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Record W4409456928 · doi:10.1080/15376494.2025.2490817

A multi-scale model for interlayer fracture behavior of FDM-printed short fiber reinforced polymers

2025· article· en· W4409456928 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueMechanics of Advanced Materials and Structures · 2025
Typearticle
Languageen
FieldEngineering
TopicAdditive Manufacturing and 3D Printing Technologies
Canadian institutionsMinistry of Education and Child Care
FundersFundamental Research Funds for Central Universities of the Central South UniversityNational Natural Science Foundation of China
KeywordsMaterials scienceComposite material3d printedFracture (geology)PolymerFiberScale modelScale (ratio)EngineeringBiomedical engineering

Abstract

fetched live from OpenAlex

It is well-known that the interlayer fracture property plays a significant role in the structural integrity of composite parts, especially fused deposition modeling (FDM) printed ones. However, there is still uncertainty in evaluating fracture mechanics due to the lack of commonly accepted standards suitable for the highly anisotropic and inhomogeneous material properties. In this context, a multiscale prediction model for the fracture toughness and crack propagation of FDM-printed short fiber reinforced polymers (FDM-SFRPs) is presented. Firstly, effective elastic properties of FDM-SFRPs are estimated based on the microstructure characterization and a two-step homogenization scheme. Secondly, a three-dimensional (3D) numerical model with anisotropic material properties is developed, by which the fracture toughness can be calculated using J-integral. Lastly, by incorporating the predicted fracture toughness into the cohesive zone model, the interlayer crack propagation is predicted. Experiments following available standards have been carried out. It was found that the proposed model efficiently calibrated the experimental results and yielded more accurate estimations than the two-dimensional (2D) model. Additionally, based on the proposed model, the effects of fibers’ content, morphology on the fracture behaviors have been discussed, providing valuable insights that can guide the future material design.

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.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.177
Threshold uncertainty score0.683

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 head0.011
GPT teacher head0.253
Teacher spread0.242 · 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