Intelligent Modeling of Erosion-Corrosion in Polymer Composites: Integrating Fuzzy Logic and Machine Learning.

Hazzaa F Alqurashi, Mohammed Y Abdellah, Mubark Alshareef, Mohamed K Hassan, Fadhel T Alabdullah, Ahmed F Moamed

Abstract read

In one paragraph

Article in Polymers, 2025. 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.

Developing machine learning regression model optimized using Tabu search harmony search algorithm for prediction of mass transfer in membranes.Scientific reports · 2026
Article
Data-Driven Design of Epoxy-Granite Machine Foundations: Bayesian Optimization for Enhanced Compressive Strength and Vibration Damping.Polymers · 2026
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.

Hazzaa F AlqurashiMechanical Engineering Department, College of Engineering and Architecture, Umm Al-Qura University, P.O. Box 5555, Makkah 21955, Saudi Arabia.ORCID 0009-0005-4030-5743

Mohammed Y AbdellahMechanical Engineering Department, Faculty of Engineering, Qena University, Qena 83523, Egypt.ORCID 0000-0003-2538-3207

Mubark AlshareefDepartment of Chemistry, Faculty of Science, Umm Al-Qura University, Makkah 24230, Saudi Arabia.ORCID 0000-0001-7720-937X

Mohamed K HassanIndustrial Engineering Department, College of Engineering and Computer Science, Mustaqbal University, Western Ring Road, Al Hamra Exit, Buraydah 52547, Saudi Arabia.ORCID 0000-0002-5353-3578

Fadhel T AlabdullahTechnical Section, Training Management Department, The Energy and Water Academy, P.O. Box 53, Rabigh 21911, Saudi Arabia.

Ahmed F MoamedMechanical Engineering Department, Faculty of Engineering, Sohag University, Sohag 82524, Egypt.ORCID 0000-0003-3559-9650

Funding

Umm al-Qura University 25UQU4320745GSSR01

6 · The paper itself

Abstract

This study presents a novel hybrid intelligent framework integrating fuzzy logic and artificial neural networks (ANN) to model the erosion-corrosion behavior of glass-fiber-reinforced pipes (GRP) under harsh operating conditions. Experimental data encompassing multiple operational parameters-including abrasive sand concentrations (250 g, 400 g, 500 g), flow rates (0.0067 m

Indexed as

artificial neural networkscorrosionerosionfuzzy logicGRP

Identifiers

PMID41516794

DOI10.3390/polym18010009

PMCPMC12787327

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LicenceCC BY

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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.