Evidence map›Paper›PMID 39640723›Full record

ArticleHeliyon2024

Study on the influence of material hardness on the performance of V-shaped non-pneumatic tyres.

Sichen Gao, Yuan Yu, Mingjiao Sun, Weimin Yang, Zhenchuan Song, Yangjun Zheng, Jiangming Yuan, Zhibin Shuai, Zhiwei Jiao

Abstract read
In one paragraph

Article in Heliyon, 2024. 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. Review
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

9 authors.

Sichen GaoBeijing University of Chemical Technology, 100029 Beijing, China.
Yuan YuBeijing University of Chemical Technology, 100029 Beijing, China.
Mingjiao SunChina North Vehicle Research Institute, 100072 Beijing, China.
Weimin YangBeijing University of Chemical Technology, 100029 Beijing, China.
Zhenchuan SongChina North Vehicle Research Institute, 100072 Beijing, China.
Yangjun ZhengChina North Vehicle Research Institute, 100072 Beijing, China.
Jiangming YuanBeijing University of Chemical Technology, 100029 Beijing, China.
Zhibin ShuaiChina North Vehicle Research Institute, 100072 Beijing, China.
Zhiwei JiaoBeijing University of Chemical Technology, 100029 Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Material selection is a crucial factor in the design of non-pneumatic tyres (NPT). Most NPTs are integrally manufactured using polyurethane materials for the supports, the inner ring, and the outer ring. It is evident that designing different components with varying material hardness will have distinct impacts on NPT performance. To study the influence of material hardness on the performance of V-shaped non-pneumatic tyres (VS-NPT), we developed finite element models of VS-NPTs with different TPU materials. To validate the finite element models, we manufactured tyres with three different hardness levels and conducted performance tests. Based on this model, a design concept is proposed where different components use materials with varying hardness levels. To elucidate how material hardness affects VS-NPT performance, the Taguchi method was used for analysis. The results reveal that increased material hardness leads to higher triaxial forces and triaxial stiffness in integrally designed VS-NPTs. Regardless of variations in the structural parameters of existing VS-NPTs, the spoke material has a significant impact on triaxial stiffness and contact area. When the spoke thickness exceeds 7.3 mm, the tread material predominantly affects the contact area.

Indexed as

Finite element methodMaterial design methodologyNon-pneumatic tyreTaguchiV-shaped spokes

Identifiers

PMID39640723
PMCPMC11620062

What OpenQuestion holds

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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.