Evidence map›Paper›PMID 33672935›Full record

ArticleMolecules (Basel, Switzerland)2021

A Rheological Model for Evaluating the Behavior of Shear Thickening of Highly Flowable Mortar.

Mengyuan Li, Jianguo Han, Yuqi Zhou, Peiyu Yan

Abstract read
In one paragraph

Article in Molecules (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

4 authors.

Mengyuan LiDepartment of Civil Engineering, Tsinghua University, Beijing 100084, China.ORCID 0000-0001-5686-2791
Jianguo HanDepartment of Civil Engineering, Tsinghua University, Beijing 100084, China.
Yuqi ZhouDepartment of Civil Engineering, Tsinghua University, Beijing 100084, China.
Peiyu YanDepartment of Civil Engineering, Tsinghua University, Beijing 100084, China.

Funding

China Postdoctoral Science Foundation 2019TQ0162National Natural Science Foundation of China 51678343Science and Technology R&D Program of China Construction Co. Ltd. CSCEC-2018-Z-11
6 · The paper itself

Abstract

Neither the modified Bingham model nor the Herschel-Bulkley model can be used to characterize and calculate the performance of shear thickening of highly flowable mortar because of their incalculability of the rheological parameters. A new exponential rheological model was established to solve the characterization and calculation of shear thickening of the lubrication layer (highly flowable mortar) during the pumping of concrete in this paper. This new exponential rheological model has three rheological parameters, namely, yield stress, consistency coefficient, and consistency exponent. They can quantitatively describe the yield stress, differential viscosity, and shear thickening degree of highly flowable mortar. The calculating results of the rheological parameters of the newly established model for the mortars with different compositions showed that the consistency exponent of mortar decreased with the increase of its sand-binder ratio or the dosage of fly ash in the binder. This indicates that the shear thickening degree of mortar decreases. The consistency exponent of mortar initially decreases and subsequently increases with the increase in silica fume content or the dosage of the superplasticizer. It illustrates that the degree of the shear thickening of mortar initially decreased and subsequently increased. These varying patterns were confirmed by the rheological experiment of mortars.

Indexed as

Models, TheoreticalRheologyShear StrengthConstruction MaterialsNonlinear DynamicsPlasticizersRotationTorqueViscosityPlasticizersconsistency exponentdifferential viscosityexponential rheological modelhighly flowable mortarshear thickeningyield stress

Identifiers

PMID33672935
PMCPMC7917666

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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.