Evidence map›Paper›PMID 40870120›Full record

ArticleMaterials (Basel, Switzerland)2025

Analysis and Correction of the Shrinkage Prediction Model for Manufactured Sand Concrete.

Wei Fan, Yang Wei, Jiyang Yi, Kang Zhao, Binrong Zhu, Guofen Li

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. 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.

Wei FanCollege of Civil Engineering, Nanjing Forestry University, Nanjing 210037, China.
Yang WeiCollege of Civil Engineering, Nanjing Forestry University, Nanjing 210037, China.ORCID 0000-0003-2915-3898
Jiyang YiCollege of Civil Engineering, Nanjing Forestry University, Nanjing 210037, China.ORCID 0009-0006-2838-7739
Kang ZhaoCollege of Civil Engineering, Nanjing Forestry University, Nanjing 210037, China.ORCID 0000-0002-3538-6121
Binrong ZhuCollege of Civil Engineering, Nanjing Forestry University, Nanjing 210037, China.
Guofen LiCollege of Civil Engineering, Nanjing Forestry University, Nanjing 210037, China.

Funding

Yang Wei No. BK20231293Yang Wei Nos.51778300
6 · The paper itself

Abstract

With the continuous depletion of natural river sand resources and the escalating ecological degradation caused by excessive sand mining, manufactured sand has emerged as a sustainable and environmentally favorable alternative aggregate, playing an increasingly important role in the advancement of green construction materials. Nevertheless, the shrinkage behavior of manufactured sand concrete (MSC) exhibits significant deviations from that of conventional natural sand concrete due to differences in the material characteristics. Existing shrinkage prediction models-such as ACI 209, CEB-FIP 2010, B3, and GL 2000-fail to adequately incorporate the specific properties and substitution effects of manufactured sand, thereby limiting their predictive accuracy and applicability. To bridge this gap, the present study conducted a systematic evaluation of the four aforementioned classical shrinkage prediction models based on experimental data from MSC specimens incorporating varying replacement rates of manufactured sand. The findings revealed that models such as B3 and CEB-FIP 2010 neglected the influence of critical characteristics of manufactured sand-namely, particle morphology, gradation, and stone powder content-on the cementitious matrix and interfacial transition zone, which led to substantial prediction discrepancies. Accordingly, a nonlinear regression-based correction function was developed, introducing the manufactured sand content as a key influencing variable to recalibrate and enhance the ACI 209 and GL 2000 models for a more accurate application to MSC. The modified models exhibited markedly improved fitting performance and predictive robustness across the full range of manufactured sand replacement ratios (0-100%), thereby offering a more reliable framework for modeling the shrinkage development of MSC.

Indexed as

admixture mitigationmanufactured sand concrete (MSC)model calibration and analysisshrinkage

Identifiers

PMID40870120
PMCPMC12387264

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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.