Evidence map›Paper›PMID 42514740›Full record

ArticlePolymers2026

Nonlinear Hyper-Viscoelastic Constitutive Modeling and PRF Parameter Identification of Rubber Materials.

Mingkuan Wang, Jiaheng Yao, Long Zhang, Ang Gao, Enchao Zhang, Shimin Zhang, Xiaoxiao Zhu

Abstract read
In one paragraph

Article in Polymers, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

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.

Mingkuan WangCollege of Mechanical and Transportation Engineering, China University of Petroleum (Beijing), Beijing 102249, China.ORCID 0009-0004-1714-5668
Jiaheng YaoCollege of Mechanical and Transportation Engineering, China University of Petroleum (Beijing), Beijing 102249, China.
Long ZhangCollege of Mechanical and Transportation Engineering, China University of Petroleum (Beijing), Beijing 102249, China.
Ang GaoCollege of Mechanical and Transportation Engineering, China University of Petroleum (Beijing), Beijing 102249, China.
Enchao ZhangCollege of Mechanical and Transportation Engineering, China University of Petroleum (Beijing), Beijing 102249, China.
Shimin ZhangCollege of Mechanical and Transportation Engineering, China University of Petroleum (Beijing), Beijing 102249, China.
Xiaoxiao ZhuCollege of Safety and Ocean Engineering, China University of Petroleum (Beijing), Beijing 102249, China.ORCID 0000-0003-0902-5776

Funding

the National Key Research and Development Program of China 2023YFC3011300
6 · The paper itself

Abstract

To accurately characterize the nonlinear hyper-viscoelastic mechanical behavior of rubber materials under large deformation and stress relaxation conditions, this study investigates fluororubber (FKM) and hydrogenated nitrile rubber (HNBR) with different hardness levels through uniaxial mechanical tests and stress relaxation experiments. A constitutive parameter identification method based on hyperelastic models and the parallel rheological framework (PRF) model is established. First, several representative hyperelastic models, including the Neo-Hookean, Mooney-Rivlin, Yeoh, Ogden, Arruda-Boyce, and Van der Waals models, are comparatively evaluated. The results show that the Ogden model with (N = 3) provides the highest fitting accuracy for the large-deformation responses of FKM and HNBR with different hardness levels, with coefficients of determination (

Indexed as

hyper-viscoelastic constitutive modelparallel rheological frameworkProny seriesrubber materialsstress relaxation

Identifiers

PMID42514740
PMCPMC13415613

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.