Evidence map›Paper›PMID 40077368›Full record

ArticleMaterials (Basel, Switzerland)2025

Analysis of the Motion Characteristics of Coarse Aggregate Simulated by Smart Aggregate During the Compaction Process.

Xiaofeng Wang, Feng Wang, Xiang Li, Shenghao Guo, Yi Zhou

Abstract read
In one paragraph

Article in Materials (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

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

5 authors.

Xiaofeng WangSchool of Materials Science and Engineering, Wuhan University of Technology, Wuhan 430070, China.
Feng WangSchool of Materials Science and Engineering, Chang'an University, Xi'an 710064, China.
Xiang LiSchool of Materials Science and Engineering, Wuhan University of Technology, Wuhan 430070, China.
Shenghao GuoSchool of Materials Science and Engineering, Chang'an University, Xi'an 710064, China.
Yi ZhouSchool of Materials Science and Engineering, Wuhan University of Technology, Wuhan 430070, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Asphalt pavement has become a vital component of modern highway construction due to its high wear resistance, short construction period, economic viability, and excellent skid resistance. However, increasing traffic volume has heightened the structural performance requirements of asphalt pavement, especially during compaction. The compaction degree of asphalt mixtures has emerged as a key indicator for assessing construction quality. This study explores the relationship between the internal structural evolution of asphalt mixtures and their compaction performance, focusing on the motion behavior of coarse aggregates. To achieve this, a wireless smart aggregate was developed using 3D printing technology to simulate coarse aggregate motion and enable real-time monitoring during compaction. Compaction experiments, including Superpave gyratory compaction and wheel rolling, were conducted on asphalt mixtures with different gradations (e.g., AC-13 and AC-20). The dynamic responses of smart aggregates were analyzed to identify motion patterns. The results show that the Superpave gyratory compaction method more accurately replicates aggregate motion observed in road construction. Additionally, asphalt mixture gradation significantly affects the motion behavior of coarse aggregates. This study provides insights into the microscale motion of coarse aggregates and its connection to compaction performance, contributing to improved asphalt pavement quality and efficiency.

Indexed as

3D printingasphalt pavementdegree of compactionintelligent aggregateskinematic characteristics of coarse aggregates

Identifiers

PMID40077368
PMCPMC11902104

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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.