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Record W2597374800 · doi:10.1108/rpj-10-2015-0151

Tensile strength of partially filled FFF printed parts: meta modelling

2017· article· en· W2597374800 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

VenueRapid Prototyping Journal · 2017
Typearticle
Languageen
FieldEngineering
TopicAdditive Manufacturing and 3D Printing Technologies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsUltimate tensile strengthMaterials scienceParametric statisticsFused filament fabricationCross section (physics)Composite materialRoofStructural engineering3D printingMathematicsEngineering

Abstract

fetched live from OpenAlex

Purpose This paper aims to investigate the tensile strength of partially filled fused filament fabrication (FFF) printed parts with respect of cross-sectional geometry of partially filled test pieces. It was reported in the authors’ earlier work that the ultimate tensile strength (UTS) is inversely proportional to the cross-sectional area of a specimen, whereas the number of shells and infill density are directly proportional to the UTS with all other parameters being held constant. Here, the authors present an in-depth evaluation of the phenomenon and a parametric model that can provide useful estimates of the UTS of the printed part by accounting for the dimensions of the solid floor/roof layers, shells and infills. Design/methodology/approach It was found that partially filled FFF printed parts consist of hollow sections. Because of these voids, the conventional method of determining the UTS via the gross cross-sectional area given by A = b × h , where b and h are the width and thickness of the printed part, respectively, cannot be used. A mathematical model of a more accurate representation of the cross-sectional area of a partially filled part was formulated. Additionally, the model was extended to predict the dimensions as well as the lateral distortion of the respective features within a printed part using input values from the experimental data. Findings The result from this investigation shows that to calculate the UTS of a partially filled FFF part, the calculation based on the conventional approach is not sufficient. A new meta-model is proposed which takes into account the geometry of the internal features to give an estimate of the strength of a partially filled printed part that is closer to the value of the strength of the material that is used for fabricating the part. Originality/value This paper investigates the tensile strength of a partially filled FFF printed part. The results have shown that the tensile strength of a partially filled part can be similar to that of a solid part, at a lower cost: shorter printing time and lower material usage. By taking into account the geometries within a printed part, the cross-sectional area can be accurately represented. The mathematical model which was developed would aid end-users to predict the tensile strength for a given set of input values of the process parameters.

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)0.001
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.655
Threshold uncertainty score0.771

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
Research integrity0.0000.001
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 head0.051
GPT teacher head0.257
Teacher spread0.206 · 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