ArticleDiscover nano2026
Radiative heat transfer and entropy generation in MHD Williamson hybrid nanofluid flow over a Darcy-Forchheimer medium with heat source.
Article in Discover nano, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Entropy generation (EG) analysis is a fundamental tool for evaluating irreversibility and thermodynamic efficiency in hybrid nanofluid (HNF) flows, as it quantifies energy losses arising from heat transfer and fluid friction. It enables the identification of dominant sources of irreversibility and the determination of optimal operating conditions. Consequently, EG analysis plays a crucial role in enhancing heat transfer performance while minimizing thermodynamic losses in advanced thermal systems. In this study, we have analyzed EG in magnetohydrodynamic Williamson HNF flow with characteristics of transfer of heat over a permeable stretched sheet along with Darcy Forchheimer effects. The impacts of radiation, dissipation, and heat source are accounted in the expression of thermal energy. The relation for concentration is reported by taking the influence of chemical reaction. The HNF is constructed by suspending copper [Formula: see text] and aluminum oxide [Formula: see text] nanoparticle into water-based Williamson liquid. For modeling of EG thermodynamics, second law is utilized. Formulation resulted system of partial differential equations (PDEs). To obtain ordinary differential equations (ODEs) from PDEs, similarity transformations are utilized. ODEs are solved via NDSolve code in Mathematica. The various variables effect on flow velocity, Bejan number, concentration, temperature, and EG are graphically studied. Engineering quantities are scrutinized numerically. The results indicate that as the magnetic variable increases, the temperature also rises. In contrast, an increase in the Prandtl number leads to a decrease in temperature. When both the magnetic parameter and porosity increase, the velocity field of the hybrid nanofluid decreases. The concentration field declines with an enhancement in both the chemical reaction and the Schmidt number. Improvements in EG are observed with higher values of diffusion, the temperature difference ratio, and Brinkman variables. The Bejan number increases with rising diffusion and temperature difference ratio, but it decreases with higher Brinkman variable values.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.