Evidence map›Paper›PMID 30347713›Full record

ArticleMaterials (Basel, Switzerland)2018

Dust Loading Performance of a Novel Submicro-Fiber Composite Filter Medium for Engine.

Jin Long, Min Tang, Zhaoxia Sun, Yun Liang, Jian Hu

Abstract read
In one paragraph

Article in Materials (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

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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.

Jin LongState Key Laboratory of Pulp and Paper Engineering, South China University of Technology, Guangzhou 510641, China. lj_king@139.com.
Min TangState Key Laboratory of Pulp and Paper Engineering, South China University of Technology, Guangzhou 510641, China. tangminde@163.com.ORCID 0000-0002-7490-7735
Zhaoxia SunState Key Laboratory of Pulp and Paper Engineering, South China University of Technology, Guangzhou 510641, China. careysun988@163.com.
Yun LiangState Key Laboratory of Pulp and Paper Engineering, South China University of Technology, Guangzhou 510641, China. liangyun@scut.edu.cn.
Jian HuState Key Laboratory of Pulp and Paper Engineering, South China University of Technology, Guangzhou 510641, China. ppjhu@scut.edu.cn.

Funding

National Key R and D Program of China 2017YFB0308000Science and Technology Planning Project of Guangdong Province 2005B090925003
6 · The paper itself

Abstract

Airborne dust can cause engine wear and contribute to engine gas emission. This study developed a novel submicro-fiber filter medium to provide protection to engines against dust. The wet-laid submicro-fiber medium was prepared by a dual-layer paper machine, and its dust loading performance was compared with other filter media during laboratory and field tests. During the laboratory tests, the dust holding capacity of the wet-laid submicro-fiber medium was 48% and 10% higher than that of the standard heavy-duty medium and electrospun submicro-fiber medium, respectively. During the field tests, the pressure drop of the wet-laid submicro-fiber filter was 45% lower than that of the standard heavy-duty filter after 10,000 km of operation. It was found that there were two crucial ways to design a better filter medium for protection against dust. Firstly, the surface loading rather than the depth loading was preferred for dust filtration. The submicro-fiber layer kept large amounts of dust particles from penetrating into the depth of filter medium. Secondly, particles were captured preferably by fibers rather than pores. The unique fibrous structure of the wet-laid submicro-fiber medium made more particle deposition take place on fibers via interception and inertial impaction.

Indexed as

airborne dustengine filtrationloading performancesubmicro-fiber

Identifiers

PMID30347713
PMCPMC6213046

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.