Predictive Modelling and Optimization of Entropy Generation in Power-Law Hybrid Nanofluid Flow Over Rotating Disk Using Adaptive Neuro-Fuzzy Inference System-Particle Swarm Optimization DOI

A. Divya,

Thandra Jithendra,

Esambattu Hemalatha

et al.

Journal of Nanofluids, Journal Year: 2024, Volume and Issue: 13(6), P. 1279 - 1294

Published: Dec. 1, 2024

Modelling hypothetical phenomena with a power-law hybrid fluid over spinning disk is the main objective of present effort. In this phase progress, optimization numerical approach that integrates Adaptive Neuro-Fuzzy Inference System (ANFIS) and Particle Swarm Optimization (PSO) to fabricate heat source/sink, non-linear thermal radiation entropy generation has been facilitated. To make sure appropriate self-similarity variables have used convert PDE set s into an ODE. The model’s study findings, few notable exceptions, generally align those from earlier studies included in dataset trained ANFIS-PSO model. visually appealing outcomes for various profiles reflect effects active elements. This illustrates how velocity temperature grow abruptly increasing magnetic field radiation, creating paradox decreasing electric inputs. Also, profile’s tilting source or sink indicates inclination. Additionally, training was examine approximations certain circumstances, effectiveness created assessed by comparing it testing dataset. nanoparticles here, their longer render, might be suitable use biological industrial applications, including exchanger simulation, glass polymer industries, metal plate cooling.

Language: Английский

Performance prediction of co-rotating disk cavity with finned vortex reducer based on machine learning DOI

Minhui Zhang,

Chunhua Wang, Jingzhou Zhang

et al.

International Journal of Thermal Sciences, Journal Year: 2024, Volume and Issue: 205, P. 109287 - 109287

Published: July 23, 2024

Language: Английский

Citations

0
Metal-to-semiconductor transitions and optical properties of ReNiO3 superlattices: An integration of first-principles calculations and machine learning analysis DOI
Yuanyuan Cui, Chengyu Zhang, Ling Niu

et al.

Surfaces and Interfaces, Journal Year: 2024, Volume and Issue: unknown, P. 105475 - 105475

Published: Nov. 1, 2024

Language: Английский

Citations

0
An imperative need for machine learning algorithms in heat transfer application: a review DOI

M. Ramanipriya,

S. Anitha

Journal of Thermal Analysis and Calorimetry, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 21, 2024

Language: Английский

Citations

0
Predictive Modelling and Optimization of Entropy Generation in Power-Law Hybrid Nanofluid Flow Over Rotating Disk Using Adaptive Neuro-Fuzzy Inference System-Particle Swarm Optimization DOI

A. Divya,

Thandra Jithendra,

Esambattu Hemalatha

et al.

Journal of Nanofluids, Journal Year: 2024, Volume and Issue: 13(6), P. 1279 - 1294

Published: Dec. 1, 2024

Modelling hypothetical phenomena with a power-law hybrid fluid over spinning disk is the main objective of present effort. In this phase progress, optimization numerical approach that integrates Adaptive Neuro-Fuzzy Inference System (ANFIS) and Particle Swarm Optimization (PSO) to fabricate heat source/sink, non-linear thermal radiation entropy generation has been facilitated. To make sure appropriate self-similarity variables have used convert PDE set s into an ODE. The model’s study findings, few notable exceptions, generally align those from earlier studies included in dataset trained ANFIS-PSO model. visually appealing outcomes for various profiles reflect effects active elements. This illustrates how velocity temperature grow abruptly increasing magnetic field radiation, creating paradox decreasing electric inputs. Also, profile’s tilting source or sink indicates inclination. Additionally, training was examine approximations certain circumstances, effectiveness created assessed by comparing it testing dataset. nanoparticles here, their longer render, might be suitable use biological industrial applications, including exchanger simulation, glass polymer industries, metal plate cooling.

Language: Английский

Citations

0