Dynamics of pollutant dispersion and solid–fluid interfacial layer in Jeffrey nanofluid flow subjected to waste discharge concentration: Implementation of probabilists’ Hermite polynomial collocation method

J., Madhu; K., Karthik; R. S., Varun Kumar; R. J., Punith Gowda; R., Naveen Kumar; B.C., Prasannakumara

doi:10.1080/10407782.2024.2319349

Numerical Heat Transfer, Part A: Applications

2024

DOI: 10.1080/10407782.2024.2319349

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Dynamics of pollutant dispersion and solid–fluid interfacial layer in Jeffrey nanofluid flow subjected to waste discharge concentration: Implementation of probabilists’ Hermite polynomial collocation method

Madhu J.,

Karthik K.,

Varun Kumar R. S.

et al.

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2024

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Cited by 7 publications

References 49 publications

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Implementation of stacking regressor model on the flow induced by TiO₂‐H₂O and Ti₆Al₄V‐H₂O nanofluid with waste discharge concentration

Madhukesh,

Fareeduddin

et al. 2024

Z Angew Math Mech

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The present investigation examines the circulation of and based nanofluids while considering the concentration of waste discharge. An innovative stacking regressor model is used to increase prediction accuracy. Using Shooting and Runge Kutta Fehlberg's fourth and fifth‐order schemes, the governing equations are converted into ordinary differential equations using similarity transformation and then numerically solved. The findings are represented graphically, and the model's correctness is assessed using Gaussian Process Regression, Categorical Boost, Extreme Gradient Boosting, and Random Forest, with linear regression acting as a meta‐model. The closely related testing and training data show the model's consistency and stability. Magnetic field and inclination angle will decline the velocity, space, and temperature‐dependent internal heat generation factors will enhance the temperature. Raising the pollutant external source parameter raises concentration. In all the cases, shows better performance than based nanofluid. The work's application ranges from fluid dynamics to waste management. By offering precise forecasts of nanofluid concentration, the proposed prediction model may aid in designing and optimizing waste discharge systems.

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Implementation of stacking regressor model on the flow induced by TiO₂‐H₂O and Ti₆Al₄V‐H₂O nanofluid with waste discharge concentration

Madhukesh,

Fareeduddin

et al. 2024

Z Angew Math Mech

View full text Add to dashboard Cite

show abstract

A numerical study on the radiative heat transfer aspects of hybrid nanofluid flow past a deformable rotating cone

Kumar,

Remidi,

Nagapavani

et al. 2024

Multiscale and Multidiscip. Model. Exp. and Des.

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The nanoparticles aggregation aspects on the chemically reactive unsteady flow of alumina-water based nanofluid: A Keller box approach with applications of wavelet physics inspired neural networks

Shagolshem,

Akkur

et al. 2024

Partial Differential Equations in Applied Mathematics

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Dynamics of pollutant dispersion and solid–fluid interfacial layer in Jeffrey nanofluid flow subjected to waste discharge concentration: Implementation of probabilists’ Hermite polynomial collocation method

Cited by 7 publications

References 49 publications

Implementation of stacking regressor model on the flow induced by TiO₂‐H₂O and Ti₆Al₄V‐H₂O nanofluid with waste discharge concentration

Implementation of stacking regressor model on the flow induced by TiO₂‐H₂O and Ti₆Al₄V‐H₂O nanofluid with waste discharge concentration

A numerical study on the radiative heat transfer aspects of hybrid nanofluid flow past a deformable rotating cone

The nanoparticles aggregation aspects on the chemically reactive unsteady flow of alumina-water based nanofluid: A Keller box approach with applications of wavelet physics inspired neural networks

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Dynamics of pollutant dispersion and solid–fluid interfacial layer in Jeffrey nanofluid flow subjected to waste discharge concentration: Implementation of probabilists’ Hermite polynomial collocation method

Cited by 7 publications

References 49 publications

Implementation of stacking regressor model on the flow induced by TiO2‐H2O and Ti6Al4V‐H2O nanofluid with waste discharge concentration

Implementation of stacking regressor model on the flow induced by TiO2‐H2O and Ti6Al4V‐H2O nanofluid with waste discharge concentration

A numerical study on the radiative heat transfer aspects of hybrid nanofluid flow past a deformable rotating cone

The nanoparticles aggregation aspects on the chemically reactive unsteady flow of alumina-water based nanofluid: A Keller box approach with applications of wavelet physics inspired neural networks

Contact Info

Product

Resources

About

Implementation of stacking regressor model on the flow induced by TiO₂‐H₂O and Ti₆Al₄V‐H₂O nanofluid with waste discharge concentration

Implementation of stacking regressor model on the flow induced by TiO₂‐H₂O and Ti₆Al₄V‐H₂O nanofluid with waste discharge concentration