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Record W4405978301 · doi:10.1016/j.rineng.2024.103841

Non Linear Thermal Radiation Analysis of Electromagnetic Chemically Reacting Ternary Nanofluid Flow over a Bilinear Stretching Surface

2025· article· en· W4405978301 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueResults in Engineering · 2025
Typearticle
Languageen
FieldEngineering
TopicNanofluid Flow and Heat Transfer
Canadian institutionsHorizon College and Seminary
Fundersnot available
KeywordsNanofluidTernary operationMaterials scienceThermal radiationFlow (mathematics)Bilinear interpolationThermalThermal analysisThermodynamicsChemical engineeringMechanicsMathematicsPhysicsComputer scienceEngineering

Abstract

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• The research explores the effects of magnetic fields, rotation, and thermal radiation on three-dimensional boundary layer flow in ternary nanofluids. • Increasing nanoparticle volume fraction leads to a 0.50% enhancement in heat transfer in Model-1. • Model-1 and Model-2 demonstrate impressive heat transfer rate increases of 29.01% and 29.12%, respectively. • Model-2 achieves a reliability score of 99.15%, validating the methodologies used in the study. Background The study investigates three-dimensional boundary layer flow in a reactive, rotating nanomaterial liquid, emphasizing non-linear thermal diffusion and radiation effects over a stretchable surface influenced by a Lorentz force. Water serves as the base fluid, with nanoparticles of silver (Ag), molybdenum disulfide (MoS₂), and copper (Cu) incorporated to enhance thermal conductivity. Rotational effects are introduced by a system rotating around a vertical axis at a constant angular velocity (⍵*). Such configurations are of significant interest in thermal management systems, heat exchangers, and other industrial applications. Motivation The increasing demand for advanced heat transfer mechanisms has driven interest in hybrid and ternary nanofluids due to their superior thermal properties compared to conventional fluids. This study aims to contribute to this growing field by analyzing the combined effects of magnetic fields, rotation, and thermal radiation on the flow and heat transfer behavior in nano materials. These insights are critical for optimizing heat transfer systems in energy, manufacturing, and engineering sectors. Aim and Objective The research seeks to analyze heat,velocity and concentration transfer rates in a three-dimensional flow system with two thermo physical models.The study focuses on the effects of magnetic field strength (M), stretching ratio (λ), Radiation parameter (R) and rotational parameter (γ) on heat transfer and fluid flow. Methodology The governing nonlinear partial differential equations (PDEs) are transformed into ordinary differential equations (ODEs) using similarity transformations. The numerical solutions are obtained using the BVP4C method and the shooting technique. MATLAB is employed to compute and graphically represent the results, including profiles for velocity, temperature, and concentration, along with Nusselt (Nu) and Sherwood (Sh) numbers. Results and Conclusions The analysis reveals that key parameters, such as magnetic field strength, stretching ratio, and rotational effects, significantly influence heat transfer and flow characteristics. In Model-1 , the percentage increase in heat transfer due to an increase in nanoparticle volume fraction (ϕ₂) is approximately 0.50%, while in Model-2 , it is around 0.35%. For the stretching ratio, Model -1 shows a transfer rate increase of about 29.01%, while Model -2 shows an increase of approximately 29.12%.Radiation effects expand the momentum layer and enhance the primary velocity in both cases. Model 2 demonstrates higher accuracy and efficiency for practical applications. Residual analysis confirms model reliability, with Model-1 at 98.73 % and Model-2 at 99.15%. These findings inform parameter optimization in heat transfer applications, particularly in thermal management systems and heat exchangers.

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Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.255
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.003
GPT teacher head0.208
Teacher spread0.204 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it