Evidence map›Paper›PMID 33441681›Full record

ArticleScientific reports2021

Velocity prediction of nanofluid in a heated porous pipe: DEFIS learning of CFD results.

Meisam Babanezhad, Iman Behroyan, Azam Marjani, Saeed Shirazian

Abstract read
In one paragraph

Article in Scientific reports, 2021. 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. Review
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.

Meisam BabanezhadInstitute of Research and Development, Duy Tan University, Da Nang, 550000, Vietnam.
Iman BehroyanFaculty of Mechanical and Energy Engineering, Shahid Beheshti University, Tehran, Iran.
Azam MarjaniDepartment for Management of Science and Technology Development, Ton Duc Thang University, Ho Chi Minh City, Vietnam. azam.marjani@tdtu.edu.vn.
Saeed ShirazianLaboratory of Computational Modeling of Drugs, South Ural State University, 76 Lenin prospekt, 454080, Chelyabinsk, Russia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Utilizing artificial intelligence algorithm of adaptive network-based fuzzy inference system (ANFIS) in combination with the computational lfuid dynamics (CFD) has recently revealed great potential as an auxiliary method for simulating challenging fluid mechnics problems. This research area is at the beginning, and needs sophisticated algorithms to be developed. No studies are available to consider the efficiency of the other trainers like differential evolution (DE) integrating with the FIS for capturing the pattern of the simulation results generated by CFD technique. Besides, the adjustment of the tuning parameters of the artificial intelligence (AI) algorithm for finding the highest level of intelligence is unavailable. The performance of AI algorithms in the meshing process has not been considered yet. Therfore, herein the Al

Identifiers

PMID33441681
PMCPMC7806800

What OpenQuestion holds

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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.