Evidence map›Paper›PMID 40281068›Full record

ArticleScientific reports2025

Development and application of tail brush elastic test device.

Jingkai Li, Jingbo Guo, Shaopu Yang, Mengze Han, Jie Li, Ziyue Zhang, Zifeng Ren, Jun Ge, Jinbo Liu

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. 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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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

9 authors.

Jingkai LiDepartment of Mechanical Traffic and Transportation, Shijiazhuang Tiedao University, Shijiazhuang, 050043, Hebei, China. 2202206012@student.stdu.edu.cn.
Jingbo GuoDepartment of Mechanical Engineering, Shijiazhuang Tiedao University, Shijiazhuang, 050043, Hebei, China. guojingbo66@163.com.
Shaopu YangDepartment of Mechanical Engineering, Shijiazhuang Tiedao University, Shijiazhuang, 050043, Hebei, China.
Mengze HanDepartment of Mechanical Engineering, Shijiazhuang Tiedao University, Shijiazhuang, 050043, Hebei, China.
Jie LiDepartment of Mechanical Engineering, Shijiazhuang Tiedao University, Shijiazhuang, 050043, Hebei, China.
Ziyue ZhangDepartment of Mechanical Engineering, Shijiazhuang Tiedao University, Shijiazhuang, 050043, Hebei, China.
Zifeng RenDepartment of Mechanical Engineering, Shijiazhuang Tiedao University, Shijiazhuang, 050043, Hebei, China.
Jun GeDepartment of Mechanical Engineering, Shijiazhuang Tiedao University, Shijiazhuang, 050043, Hebei, China.
Jinbo LiuDepartment of Mechanical Engineering, Shijiazhuang Tiedao University, Shijiazhuang, 050043, Hebei, China.

Funding

Hebei Education Department CXZZBS2024145Ministry of Science and Technology of the People´s Republic of China 2020YFB1709504S&T Program of Hebei 23567602H
6 · The paper itself

Abstract

The shield tail brush loss elasticity is the key reason for the failure of shield tail seal. However, due to the limitation of test equipment, there is little research on the elastic properties of tail brush. In this research, a tail brush elastic test device was developed. Through this device, the tail brush is tested for elasticity. In this test, the grease filling layer number, tail brush mass, tail clearance, pressing number and pressing time were taken as the influencing factors, and the elastic coefficient and resilience force were taken as the response values. Single-factor test was carried out for each factor, then based on the Plackett-Burmanf theory and Box-Behnken response surface design theory, the ANOVA method was used to find out the significant degree of each factor's influence on the quantitative index. The prediction model of elastic coefficient and resilience force was fitted based on RSM theory, and the verification group was added to verify the reliability of the prediction model. The results showed that the significance of influencing factors on the elasticity coefficient was ranked as follows: tail clearance > pressing number > pressing time > grease filling layer number. The significance of influencing factors on brush resilience F was ranked as follows: tailclearance > grease filling layer number > pressing time > pressing number. The accuracy of elastic coefficient regression model is 94.1%. The accuracy of the resilience force regression model is 99.56%, and the accuracy of the prediction model is high, which can be used to predict the elasticity coefficient and resilience force. Finally, the elastoplastic development mechanism of tail brush is discussed, and the safety standard of tail brush is proposed, which provides a basis for the selection of tail brush in practical construction.

Indexed as

Box-Behnken testElastic coefficientPlackett-Burman testResilience forceShield tail sealing systemTail brush

Identifiers

PMID40281068
PMCPMC12032339

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