Challenges associated with drilling operations are numerous and their adverse effect could
lead to severe damage or even shutting down of the drilling operations. Wellbore instability …

Comprehensive experimental investigation and accurate predictive models are required to
understand the dynamics in Ionic liquid (IL) properties. Examples of these predictive models …

Concrete is the most commonly used construction material. The physical properties of
concrete vary with the type of concrete, such as high and ultra-high-strength concrete, fibre …

Ternary-blend concrete is a complex composite material, and the nonlinearity in its
compressive strength behavior is unquestionable. Entirely many models have been …

Waterflooding is a secondary oil recovery technique in which water is injected into an
underground oil reservoir to maintain the reservoir pressure and boost oil recovery. The …

The primary cause behind the degradation of reinforced concrete (RC) structures is the
propagation of corrosion in the steel-RC structures. Nowadays, numerous retrofitting …

Abstract Ionic Liquids (ILs) have received increased attention across a number of disciplines
in recent years. This noticeable importance of ILs is attributed to their attractive proprieties …

Vaporization properties are important for equipment modeling and process control involving
liquid-vapor equilibrium. The aim of this work was to obtain an Artificial Neural Network …

This work aims to develop a robust machine learning model for the prediction of the relative
viscosity of nanoparticles (NPs) including Al2O3, TiO2, SiO2, CuO, SiC, and Ag based on …

This study leverages machine learning techniques to predict pozzolanic concrete's
compressive strength accurately. Using artificial neural networks (ANN), random forest (RF) …