Reliability study of generalized Rayleigh distribution based on inverse power law using artificial neural network with Bayesian regularization

AB Çolak, TN Sindhu, SA Lone, A Shafiq… - Tribology …, 2023 - Elsevier
Using the generalized Rayleigh distribution and the inverse power law, this paper proposes
a new reliability model and investigates the effect of the key parameters on reliability …

Predicting mechanical behaviors of rubber materials with artificial neural networks

Z Yuan, MQ Niu, H Ma, T Gao, J Zang, Y Zhang… - International Journal of …, 2023 - Elsevier
Rubber is considered as a new material for making landing gear shock absorbers for new
energy electric aircraft. This investigation tested nitrile butadiene rubber blocks with different …

A mechanistic-based data-driven approach for general friction modeling in complex mechanical system

H Peng, N Song, F Li, S Tang - Journal of Applied …, 2022 - asmedigitalcollection.asme.org
The effect of friction is widespread around us, and most important projects must consider the
friction effect. To better depict the dynamic characteristics of multibody systems with friction …

Predicting the effect of inertia, rotation, and magnetic field on the onset of convection in a bidispersive porous medium using machine learning techniques

M Singh, R Ragoju, G Shiva Kumar Reddy… - Physics of …, 2023 - pubs.aip.org
Effects of the magnetic field and inertia on the onset of thermal convection in a horizontal
bidispersive porous layer, rotating about a vertical axis, are analyzed. The Darcy equation …

Establishment of CNN and encoder–decoder models for the prediction of characteristics of flow and heat transfer around NACA sections

J Seo, HS Yoon, MI Kim - Energies, 2022 - mdpi.com
The present study established two different models based on the convolutional neural
network (CNN) and the encoder–decoder (ED) to predict the characteristics of the flow and …

Nonlinear magneto convection in an inclined porous layer with artificial neural network prediction

GSK Reddy, R Ragoju, P Dey… - Mathematical Methods in …, 2022 - Wiley Online Library
The onset of magnetoconvection in an inclined porous layer is investigated. The effects of
physical parameters, such as the Rayleigh number, the inclination angle, and the Hartmann …

[HTML][HTML] Enhanced Heat Transfer in Novel Star-Shaped Enclosure with Hybrid Nanofluids: A Neural Network-Assisted Study

QU Ain, IA Shah, SM Alzahrani - Case Studies in Thermal Engineering, 2024 - Elsevier
The current research is a numerical investigation of the thermo-fluidic transport trend within
a new star-shaped enclosure filled with (Multiwall Carbon Nanotubes) suspended hybrid …

Artificial Neural Network analysis on the effect of mixed convection in triangular-shaped geometry using water-based Al2O3 nanofluid

MN Hudha, MJ Hasan, T Bairagi, AK Azad… - PloS one, 2024 - journals.plos.org
The objective of the study is to investigate the fluid flow and heat transfer characteristics
applying Artificial Neural Networks (ANN) analysis in triangular-shaped cavities for the …

Double diffusive Buoyancy‐driven flow in a fluid‐saturated elliptical annulus with a neural network‐based prediction of heat and mass transfer

H Boulechfar, F Berrahil, A Boulmerka, A Filali… - Heat …, 2023 - Wiley Online Library
This paper presents a numerical study of buoyancy‐driven double‐diffusive convection
within an elliptical annulus enclosure filled with a saturated porous medium. An in‐house …

Evaluation of non-Newtonian model to accurately predict high Rayleigh number natural convection characteristics using PIV experiment and CFD simulation

S Pandey, MY Ha - International Journal of Heat and Mass Transfer, 2023 - Elsevier
Non-Newtonian fluids exhibit variable viscosity particularly at relatively high Rayleigh
numbers (Ra), resulting in the occurrence of a complex natural convection phenomenon. In …