Evidence map›Paper›PMID 38743667›Full record

ArticlePloS one2024

Interface stress transfer model and modulus parameter equivalence method for composite materials embedded with tensile pre-strain shape memory alloy fibers.

Yizhe Huang, Xueliang Duan, Jun Wang, Zhifu Zhang, Yuanyuan Shi, Bin Huang, Enyong Xu

Abstract read
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Yizhe HuangSchool of Mechanical Engineering, Hubei University of Technology, Wuhan, China.ORCID 0000-0001-7117-6255
Xueliang DuanSchool of Mechanical Engineering, Hubei University of Technology, Wuhan, China.
Jun WangSchool of Mechanical Engineering, Hubei University of Technology, Wuhan, China.
Zhifu ZhangSchool of Mechanical and Electrical Engineering, Hainan University, Haikou, China.ORCID 0000-0002-9709-7851
Yuanyuan ShiState Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, China.
Bin HuangSchool of Mechanical Engineering, Hubei University of Technology, Wuhan, China.
Enyong XuState Key Laboratory of Digital Manufacturing Equipment and Technology, Huazhong University of Science and Technology, Wuhan, China.ORCID 0000-0001-8159-2420

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The constitutive model and modulus parameter equivalence of shape memory alloy composites (SMAC) serve as the foundation for the structural dynamic modeling of composite materials, which has a direct impact on the dynamic characteristics and modeling accuracy of SMAC. This article proposes a homogenization method for SMA composites considering interfacial phases, models the interface stress transfer of three-phase cylinders physically, and derives the axial and shear stresses of SMA fiber phase, interfacial phase, and matrix phase mathematically. The homogenization method and stress expression were then used to determine the macroscopic effective modulus of SMAC as well as the stress characteristics of the fiber phase and interface phase of SMA. The findings demonstrate the significance of volume fraction and tensile pre-strain in stress transfer between the fiber phase and interface phase at high temperatures. The maximum axial stress in the fiber phase is 705.05 MPa when the SMA is fully austenitic and the pre-strain increases to 5%. At 10% volume fraction of SMA, the fiber phase's maximum axial stress can reach 1000 MPa. Ultimately, an experimental verification of the theoretical calculation method's accuracy for the effective modulus of SMAC lays the groundwork for the dynamic modeling of SMAC structures.

Indexed as

AlloysStress, MechanicalTensile StrengthElastic ModulusMaterials TestingModels, TheoreticalSmart MaterialsAlloysSmart Materials

Identifiers

PMID38743667
PMCPMC11093366

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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.