Evidence map›Paper›PMID 40399338›Full record

ArticleScientific reports2025

Multiscale computational modeling of 3D printed continuous Fiber reinforced polymer composites.

Xin Li

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Review
  3. 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

1 author.

Xin LiKey Laboratory of Traffic Safety on Track of Ministry of Education, School of Traffic & Transportation Engineering, Central South University, Changsha, 410075, China. lixin204212100@outlook.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Printing parameters significantly affect elastic properties of 3DP-CFRPCs. Testing these experimentally would require time and would cost much. Computational material modeling is an adequate technique for studying how 3DP-CFRPCs would behave in varying printing conditions. Material modeling was employed in this work to analyze how elastic properties in 3DP-CFRPCs vary with printing conditions. Pores in the matrix were homogenized by Mori-Tanaka method to calculate bead flexibility. Elastic modulus was found by finite element modeling of Representative Volume Elements (RVEs) with microstructure and printing conditions taken into account. Elastic properties differed in differently microstructured models with more disparity in more intricate structures than in more basic ones. Computational modeling provided insight to elastic properties of 3DP-CFRPCs in varied printing conditions. The results also show that thickness of the layers and interfacial properties determine the elastic properties to a great extent, such that higher thickness of the layers and stronger interfacial bonding lead to higher stiffness. The model also correctly simulated behavior of 3DP-CFRPCs when different printing parameters were used, with low error compared to experimental results. The impact of layer thickness on the mechanical characteristics of 3DP-CFRPCs was determined to be more substantial compared to the effect of printing temperature. The application of offset layup printing techniques enhanced the elastic properties of 3DP-CFRPCs, with the degree of improvement varying based on the orientation. As the level of porosity increased, the influence of pores situated between beads on the overall stiffness of 3DP-CFRPCs gradually diminished, while the impact of matrix pores on the overall stiffness of 3DP-CFRPCs gradually intensified.

Indexed as

3D printingCompositesComputational modelingContinuous fiber

Identifiers

PMID40399338
PMCPMC12095671

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.