In this study, improved prediction methods based on supervised machine-learning
algorithms is proposed to predict the effect of the application of air injection and transverse …

This work used artificial neural network (ANN) to predict the heat transfer rates of shell-and-
tube heat exchangers with segmental baffles or continuous helical baffles, based on limited …

The study of the fluid flow in heat exchangers and its related mass and heat transfer
processes is a very complicated research subject. Modeling of coupled fluid flow and heat …

Typically, success in the estimation of machine learning is expected to rise with increasing
input parameters, whereas the noise issue may rarely arise owing to redundant input factors …

Two intelligent optimization methods, artificial neural networks (ANNs) and adaptive neuro-
fuzzy inference system (ANFIS), with particle swarm optimization (PSO), were employed in …

This work applied Artificial Neural Network (ANN) for heat transfer analysis of shell-and-tube
heat exchangers with segmental baffles or continuous helical baffles. Three heat …

Heat exchangers are widely used in many field for the purpose of heat from one medium to
another. In heat exchanger one or more fluids are used, and which are various types based …

In this paper an Adaptive Neuro-Fuzzy Inference System (ANFIS) is used for modeling the
effect of important parameters on heat transfer and fluid flow characteristics of helicoidal …

This study presents the development and evaluation of a novel shell-and-tube heat
exchanger (STHX) design with segmental porous baffles. Computational fluid dynamics …

Nowadays, nanofluids are broadly utilized for various engineering and industrial systems
including heat exchangers, power plants, air-conditioning, etc. The helically coiled tube heat …