Evidence map›Paper›PMID 38950007›Full record

ArticlePloS one2024

Forecasting the rheological state properties of self-compacting concrete mixes using the response surface methodology technique for sustainable structural concreting.

Edwin Zumba, Nancy Velasco, Edison Marcelo Melendres Medina, Jorge Bunay, Nestor Augusto Estrada Brito, Kennedy C Onyelowe, Nakkeeran Ganasen, Shadi Hanandeh

RetractedErratum issuedAbstract readRetracted Publication
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Edwin ZumbaUniversidad Nacional de Chimborazo (UNACH), Riobamba, Ecuador.
Nancy VelascoFaculta de Informatica y Electronica, Escuela Superior Politechnica de Chimborazo (ESCPOCH), Riobamba, Ecuador.
Edison Marcelo Melendres MedinaFacultad de Administracion de Empresas, Escuela Superior Politechnica de Chimborazo (ESCPOCH), Riobamba, Ecuador.
Jorge BunayFacultad de Mecanica, Escuela Superior Politechnica de Chimborazo (ESCPOCH), Riobamba, Ecuador.ORCID 0000-0001-6963-0383
Nestor Augusto Estrada BritoFaculta de Informatica y Electronica, Escuela Superior Politechnica de Chimborazo (ESCPOCH), Riobamba, Ecuador.
Kennedy C OnyeloweDepartment of Civil Engineering, Michael Okpara University of Agriculture, Umudike, Nigeria.ORCID 0000-0001-5218-820X
Nakkeeran GanasenDepartment of Civil Engineering, SRM Institute of Science and Technology, Tamil Nadu, India.
Shadi HanandehDepartment of Civil Engineering, Al-Balqa Applied University, As-Salt, Jordan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

It is structurally pertinent to understudy the important roles the self-compacting concrete (SCC) yield stress and plastic viscosity play in maintaining the rheological state of the concrete to flow. It is also important to understand that different concrete mixes with varying proportions of fine to coarse aggregate ratio and their nominal sizes produce different and corresponding flow- and fill-abilities, which are functions of the yield stress/plastic viscosity state conditions of the studied concrete. These factors have necessitated the development of regression models, which propose optimal rheological state behavior of SCC to ensure a more sustainable concreting. In this research paper on forecasting the rheological state properties of self-compacting concrete (SCC) mixes by using the response surface methodology (RSM) technique, the influence of nominal sizes of the coarse aggregate has been studied in the concrete mixes, which produced experimental mix entries. A total of eighty-four (84) concrete mixes were collected, sorted and split into training and validation sets to model the plastic viscosity and the yield stress of the SCC. In the field applications, the influence of the sampling sizes on the rheological properties of the concrete cannot be overstretched due to the importance of flow consistency in SCC in order to achieve effective workability. The RSM is a symbolic regression analysis which has proven to exercise the capacity to propose highly performable engineering relationships. At the end of the model exercise, it was found that the RSM proposed a closed-form parametric relationship between the outputs (plastic viscosity and yield stress) and the studied independent variables (the concrete components). This expression can be applied in the design and production of SCC with performance accuracies of above 95% and 90%, respectively. Also, the RSM produced graphical prediction of the plastic viscosity and yield stress at the optimized state conditions with respect to the measured variables, which could be useful in monitoring the performance of the concrete in practice and its overtime assessment. Generally, the production of SCC for field applications are justified by the components in this study and experimental entries beyond which the parametric relations and their accuracies are to be reverified.

Indexed as

Construction MaterialsRheologyForecastingMaterials TestingViscosity

Identifiers

PMID38950007
PMCPMC11216621

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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.