Membrane desalination (MD) is an efficient process for desalinating saltwater, combining
the uniqueness of both thermal and separation distillation configurations. In this context, the …

In this article, the ability of GMDH artificial neural networks (ANNs) to predict the rheological
behavior (RB) of nanofluids (NFs) containing CuO NPs is studied. ANNs are a powerful …

Building integrated photovoltaic thermal (BIPV/T) systems offer a highly effective means of
generating clean energy for both electricity and heating purposes in residential buildings …

This study predicts the parameters such as viscosity and thermal conductivity in silica-
alumina-MWCN/water nanofluid using the artificial intelligence method and using design …

As the transport sector is responsible for the consumption of a vast proportion of the oil
produced, it is mandatory to research feasible solutions to tackle this issue. The application …

One of the important categories in office spaces is the control of daylight and energy
consumption. By controlling natural light, it is possible to provide uniform light in the entire …

The research used an artificial neural network (ANN) model to examine the rheological
properties of hybrid non-Newtonian ferrofluids (HNFFs) composed of Fe-CuO, water, and …

Background Nanofluids are the most widely used materials in various engineering fields.
They have different properties under different conditions, and predicting their properties …

The uncontrollable rise in energy consumption become a most significant issue in recent
decades. One of the largest consumers of energy resources across all industries is the …

The use of fossil fuels for energy supply causes air pollution and environmental degradation
factors, which itself causes climate change in the world. Therefore, researches are looking …