Intelligent design of high-performance fluids for thermal management: integrating response surface methodology, weighted Tchebycheff method, and strength Pareto evolutionary algorithm II.

Mohamed Bechir Ben Hamida, Ali Basem, Neeraj Varshney, Loghman Mostafa

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Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

4 authors.

Mohamed Bechir Ben HamidaDeanship of Scientific Research, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, Saudi Arabia.

Ali BasemFaculty of Engineering, Warith Al-Anbiyaa University, Karbala, 56001, Iraq.

Neeraj VarshneyDepartment of Computer Engineering and Applications, Institute of Engineering and Technology, GLA University, Mathura, Uttar Pradesh, 281406, India.

Loghman MostafaCollege of Technical Engineering, Islamic Azad University, Urmia Branch, Urmia, Iran. loghmanmostafa2@gmail.com.

Funding

Deanship of Scientific Research at Imam Mohammad Ibn Saud Islamic University IMSIU-DDRSP2503

6 · The paper itself

Abstract

Optimizing nanofluid thermophysical properties (TPPs) is essential for advancing heat transfer applications; however, most studies focus on two-objective optimization, limiting their real-world applicability. This study presents a novel multi-objective optimization framework integrating response surface methodology (RSM) with enhanced hill climbing (EHC) algorithm and strength Pareto evolutionary algorithm II (SPEA-II) to optimize multiple TPPs. The weighted Tchebycheff method (WTM) is employed for decision-making, ensuring a balanced and application-specific selection of nanofluids. The RSM models demonstrated high predictive accuracy, with R

Indexed as

Enhanced hill climbing algorithmHybrid nanofluidMulti-objective optimizationResponse surface methodologyStrength Pareto evolutionary algorithm IIWeighted Tchebycheff method

Identifiers

PMID40595061

DOI10.1038/s41598-025-07132-0

PMCPMC12218536

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LicenceCC BY-NC-ND

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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.