Evidence map›Paper›PMID 34068521›Full record

ArticleMicromachines2021

Numerical Analysis of Thermal Radiative Maxwell Nanofluid Flow Over-Stretching Porous Rotating Disk.

Shuang-Shuang Zhou, Muhammad Bilal, Muhammad Altaf Khan, Taseer Muhammad

Abstract read
In one paragraph

Article in Micromachines, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

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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

4 authors.

Shuang-Shuang ZhouSchool of Science, Hunan City University, Yiyang 413000, China.
Muhammad BilalDepartment of Mathematics, City University of Science and Information Technology, Peshawar 25000, Pakistan.ORCID 0000-0001-7773-4844
Muhammad Altaf KhanInstitute for Groundwater Studies, Faculty of Natural and Agricultural Sciences, University of Free State, Bloemfontein 9300, South Africa.ORCID 0000-0002-4483-7879
Taseer MuhammadDepartment of Mathematics, College of Sciences, King Khalid University, Abha 61413, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The fluid flow over a rotating disk is critically important due to its application in a broad spectrum of industries and engineering and scientific fields. In this article, the traditional swirling flow of Von Karman is optimized for Maxwell fluid over a porous spinning disc with a consistent suction/injection effect. Buongiorno's model, which incorporates the effect of both thermophoresis and Brownian motion, describes the Maxwell nanofluid nature. The dimensionless system of ordinary differential equations (ODEs) has been diminished from the system of modeled equations through a proper transformation framework. Which is numerically computed with the bvp4c method and for validity purposes, the results are compared with the RK4 technique. The effect of mathematical abstractions on velocity, energy, concentration, and magnetic power is sketched and debated. It is perceived that the mass transmission significantly rises with the thermophoresis parameter, while the velocities in angular and radial directions are reducing with enlarging of the viscosity parameter. Further, the influences of thermal radiation Rd and Brownian motion parameters are particularly more valuable to enhance fluid temperature. The fluid velocity is reduced by the action of suction effects. The suction effect grips the fluid particles towards the pores of the disk, which causes the momentum boundary layer reduction.

Indexed as

brownian motionbvp4cmaxwell nanofluidporous rotating diskRK4 techniquethermally radiative fluidvon karman transformation

Identifiers

PMID34068521
PMCPMC8150900

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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.