In the past few years, a significant research effort has been imposed by the researchers on
the in-depth analysis of functionally graded carbon nanotubes reinforced composite (FG …

Predicting mechanical properties of graphene-reinforced metal matrix nanocomposites
(GRMMNCs) usually requires atomistic simulations that are computationally expensive …

The present research compares the influences of nanofiller materials on the free vibrational
performance of Nanocomposite Cylindrical Shells (NCSs). For this purpose, three well …

Industry 4.0 recommends a paradigm shift from traditional manufacturing to automated
industrial practices, especially in different parts of supply chain management. Besides, the …

An efficient approach for improving the predictive understanding of dynamic mechanical
system variability is developed in this work. The approach requires low model assessment …

Present manuscript undergoes with the investigation of the wave propagation features of
smart magnetostrictive sandwich nanoplates (MSNPs) with regard to the influences of small …

In this paper, a deep-learning model is proposed as a viable approach to optimize the
information on soil parameters and agricultural variables' effect in cotton cultivation, even in …

Predicting the mechanical properties of multiscale nanocomposites requires simulations that
are costly from a practical viewpoint and time consuming. The use of algorithms for property …

The time-dependent viscoelastic deflection characteristics of laminated composite structures
consisted of an auxetic core respectively surrounded by piezoelectric and gold layers in …

Carbon nanotube (CNT)-reinforced polymer nanocomposites have excellent stiffness,
strength and viscoelastic nature due to the time-dependent properties of the polymers …