Evidence map›Paper›PMID 37687751›Full record

ArticleMaterials (Basel, Switzerland)2023

Gray Model Study of Strength and Pore Structure of Recycled Concrete Powder (RCP) Concrete Based on Low-Field NMR Technology.

Yongli Hou, Zhengxing Yu, Jianhua Zhang, Hongrui Yang, Weiqing Song

Abstract read
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 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  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.

Yongli HouCollege of Civil Engineering, Inner Mongolia University of Technology, Hohhot 010051, China.
Zhengxing YuCollege of Civil Engineering, Inner Mongolia University of Technology, Hohhot 010051, China.
Jianhua ZhangCollege of Aerospace and Civil Engineering, Harbin Engineering University, Harbin 150001, China.ORCID 0000-0003-2528-6132
Hongrui YangCollege of Civil Engineering, Inner Mongolia University of Technology, Hohhot 010051, China.
Weiqing SongCollege of Civil Engineering, Inner Mongolia University of Technology, Hohhot 010051, China.

Funding

Jianhua Zhang No.: 423 2021YFB2600800
6 · The paper itself

Abstract

In order to improve the resource utilization of recycled concrete powder (RCP), this study aimed to investigate the effect of RCP admixture, curing age, and alkali excitation on the strength of RCP concrete. In addition, the pore structure characteristics of RCP concrete were analyzed in combination with low-field NMR. Furthermore, a gray predictive GM (1, 4) model was established to predict the mechanical properties of the concrete based on the pore structure parameters, especially the compressive and flexural tensile strengths. The results of the study indicate that the mechanical properties, namely compressive strength and flexural strength, of RCP concrete exhibit an initial increase followed by a subsequent decrease with increasing RCP content at 3 d, 7 d, and 28 d curing ages. In particular, the concrete exhibits the highest mechanical properties when the RCP content reaches 10%. As the curing age increases, the RCP gradually achieves full hydration, resulting in further refinement of the concrete pores and a denser structure, which subsequently improves the mechanical properties. In addition, the strength growth rate of alkali-excited recycled concrete (ARC) showed a continuous increase, indicating that alkali excitation increasingly improved the mechanical properties of the concrete. Furthermore, the study accurately predicted the mechanical properties of RCP concrete by using GM (1, 4) prediction models for its compressive strength and flexural tensile strength using pore characteristic parameters.

Indexed as

GM (1, 4)gray entropy correlation grademechanical propertypore structureRCP

Identifiers

PMID37687751
PMCPMC10488844

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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.