Evidence map›Paper›PMID 37688230›Full record

ArticlePolymers2023

Tensile and Compression Strength Prediction and Validation in 3D-Printed Short-Fiber-Reinforced Polymers.

Timothy Russell, David A Jack

Abstract read
In one paragraph

Article in Polymers, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Timothy RussellDepartment of Mechanical Engineering, Baylor University, Waco, TX 76798, USA.ORCID 0000-0002-4108-6045
David A JackDepartment of Mechanical Engineering, Baylor University, Waco, TX 76798, USA.ORCID 0000-0001-7199-0556

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the current study, a methodology is validated for predicting the internal spatially varying strength properties in a single 3D-printed bead composed of 13%, by weight, carbon-fiber-filled acrylonitrile butadiene styrene. The presented method allows for the characterization of the spatially varying microstructural behavior yielding a local anisotropic stiffness and strength that can be integrated in a finite element framework for a bulk estimate of the effective stiffness and strength. The modeling framework is presented with a focus on composite structures made from large area additive manufacturing (LAAM). LAAM is an extrusion-based process yielding components on the order of meters, with a typical raster size of 10 mm. The presented modeling methods are applicable to other short-fiber-reinforced polymer processing methods as well. The results provided indicate the modeling framework yields results for the effective strength and stiffness that align with experimental characterization to within ∼1% and ∼10% for the longitudinal compressive and tensile strength, respectively, and to within ∼3% and ∼50% for the longitudinal compressive and tensile stiffness, respectively.

Indexed as

closurefiber orientationJeffery modellarge area additive manufacturingshort-fiber compositesstructural properties

Identifiers

PMID37688230
PMCPMC10489888

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.