Evidence map›Paper›PMID 37504164›Full record

ArticleBiomimetics (Basel, Switzerland)2023

Cushioning Performance of the Biomimetic Cobweb Cushioning Silicone Pad.

Changyu Liao, Ye Tian, Wei Xu, Jiahang Zhang, Zhihui Sun, Zhuang Liu

Abstract read
In one paragraph

Article in Biomimetics (Basel, Switzerland), 2023. 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

6 authors.

Changyu LiaoSchool of Light Industry, Harbin University of Commerce, Harbin 150000, China.
Ye TianSchool of Light Industry, Harbin University of Commerce, Harbin 150000, China.ORCID 0000-0003-3469-4103
Wei XuSchool of Light Industry, Harbin University of Commerce, Harbin 150000, China.
Jiahang ZhangSchool of Light Industry, Harbin University of Commerce, Harbin 150000, China.
Zhihui SunSchool of Light Industry, Harbin University of Commerce, Harbin 150000, China.
Zhuang LiuSchool of Light Industry, Harbin University of Commerce, Harbin 150000, China.

Funding

National Natural Science Foundation of China 41772387Natural Science Foundation of Heilongjiang Province LH2020E027Youth Academic Backbone Program of Harbin University of Commerce 2019CX04
6 · The paper itself

Abstract

At present, the packing method of "plastic bag-buffer packing-packing paper box" is adopted for bearing packaging. However, the common packing method has a poor packing effect and poor versatility. In this study, a new biomimetic cobweb cushion is proposed to solve the problem of insufficient cushioning capacity of high-precision bearing cushion packaging pads. First, according to the nature of cobweb form, the cobweb cushion structure configuration is determined. Next, based on the structure of the cushion and the relationship between the parameters of radial thread and spiral thread, a mechanical and target optimization model is established. The stress nephogram of bearing and the cobweb cushion are analyzed under three drop heights of 381, 610, and 700 mm, in the finite element simulation software to ensure that the maximum bearings stress is not beyond the material yield strength. Via the 3D printing technology, a cobweb cushion shell cast is made. Drop tests of the bearing were performed, and the results were verified with the finite element simulation analysis. This research can provide technical support for the protection of high-precision bearings from accidental drops during transportation.

Indexed as

3D printingbiomimetic structurecushion padsilicone

Identifiers

PMID37504164
PMCPMC10377657

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.