Evidence map›Paper›PMID 36616506›Full record

ArticlePolymers2022

Storage Life Prediction of Rubber Products Based on Step Stress Accelerated Aging and Intelligent Algorithm.

Xiaohui Guo, Xiaojing Yuan, Guangyong Liu, Genliang Hou, Ze Zhang

Open access · goldAbstract read
In one paragraph

Article in Polymers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.5field-weighted citation impact, top 42% of its field
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

3 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
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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

5 authors at 2 institutions in 1 country.

Xiaohui GuoCombat Support College, Rocket Force University of Engineering, Xi'an 710025, China.ORCID 0000-0002-9768-452X
Xiaojing YuanCombat Support College, Rocket Force University of Engineering, Xi'an 710025, China.
Guangyong LiuKey Laboratory of Rubber and Plastic Materials and Engineering, Ministry of Education, Qingdao University of Science and Technology, Qingdao 266042, China.
Genliang HouCombat Support College, Rocket Force University of Engineering, Xi'an 710025, China.
Ze ZhangCombat Support College, Rocket Force University of Engineering, Xi'an 710025, China.
PLA Rocket Force University of Engineering · CNQingdao University of Science and Technology · CN

Funding

Chinese People's Liberation Army WG20200017
6 · The paper itself

Abstract

Compared with the constant stress accelerated aging test, the step stress accelerated aging test reduces the accelerated aging test time by increasing the aging temperature step by step to obtain the aging failure life of rubber in a shorter time, but its data processing method is not mature enough. In this paper, a simplified step is proposed to process the step stress accelerated aging data. The identification of the acceleration factor is transformed into an optimization problem to avoid the error accumulation problem caused by fitting the data at each temperature. Considering the non-Arrhenius phenomenon in the rubber aging process, a modified Arrhenius equation was used to extrapolate the acceleration factor at low temperatures to calculate the prediction curves for the degradation of polyurethane rubber properties at low temperatures. The life prediction results of the constant stress accelerated aging test and step stress accelerated aging test were compared, and the dispersion coefficient between the two results was between 0.9 and 1. The results obtained by the two methods were in good agreement, which proved the correctness and feasibility of the method used in this paper.

Indexed as

acceleration factorimproved Arrhenius equationintelligent algorithmrubber storage lifestep stress accelerated aging test

Identifiers

PMID36616506
PMCPMC9823469
OpenAlexW4313361204

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.