Evidence map›Paper›PMID 37512369›Full record

ArticleMaterials (Basel, Switzerland)2023

Evaluation of the Adhesion between Aggregate and Asphalt Binder Based on Image Processing Techniques Considering Aggregate Characteristics.

Min Li, Jian Wang, Zibao Guo, Jingchun Chen, Zedong Zhao, Jiaolong Ren

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Materials (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. Article
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.

Min LiSchool of Civil Engineering and Geomatics, Shandong University of Technology, Zibo 255000, China.
Jian WangSchool of Civil Engineering and Geomatics, Shandong University of Technology, Zibo 255000, China.
Zibao GuoCCCC First Highway Northwest Engineering Co., Ltd., Xi'an 710110, China.
Jingchun ChenSchool of Civil Engineering and Geomatics, Shandong University of Technology, Zibo 255000, China.
Zedong ZhaoSchool of Transportation and Vehicle Engineering, Shandong University of Technology, Zibo 255000, China.
Jiaolong RenSchool of Civil Engineering and Geomatics, Shandong University of Technology, Zibo 255000, China.ORCID 0000-0002-3500-7320

Funding

National Natural Science Foundation of China 51808326
6 · The paper itself

Abstract

Aggregate-asphalt adhesion plays an important role in the water stability of asphalt concrete. In various test standards of different countries, it is evaluated via the subjective judgment of testers using the boiling water test. The subjective judgment in the test method is detrimental to the accuracy of the adhesion evaluation. However, there is no quantitative evaluation method for the aggregate-asphalt adhesion in existing studies. Moreover, the effects of aggregate shape on adhesion are also not discussed and stipulated. Hence, an innovative method based on the Chinese boiling water test and image processing technique is put forward to quantificationally evaluate the aggregate-asphalt adhesion. Moreover, the effects of aggregate shapes on adhesion are also investigated via the proposed method from a view of aspect ratio and homogeneity. Results show that the peeling of the asphalt membrane on the aggregate surface is more serious as the complexity of the aggregate shape increases after the boiling water tests, while the effect degree gradually decreases. The effect of aspect ratio on the peeling status of asphalt membrane is lower than that of aggregate homogeneity.

Indexed as

aggregate–asphalt adhesionaggregate characteristicsevaluation methodimage processing techniqueswater boiling test

Identifiers

PMID37512369
PMCPMC10383691

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.