This article reports on development of an adaptive framework for predicting the erosion
performance of polymer composites using certain statistical and machine learning (ML) …

This work reports on the application of different machine learning (ML) techniques and
statistical methods to analyze and predict the erosion wear performance of ramie fiber …

This study presents a comprehensive analysis of the morphology, mechanical properties,
erosion resistance, and machine learning modeling of Si 3 N 4+ TiC+ VC and CrNi based …

This study evaluates the sliding wear behavior of hybrid composites made of epoxy
reinforced with alternating layers of flax fiber mats and steel wire mesh. The aim is to …

This article reports on the implementation of artificial neural network (ANN) and statistical
methods to analyze and predict the erosion performance of titania (TiO2) filled ramie‐epoxy …

Slurry erosion due to particle entrainment poses a significant threat to slurry handling
components, leading to reduced performance and shorter service life. The ferritic-austenitic …

This research work aims to investigate the effect of fabrication techniques on the physico‐
mechanical properties of pistachio shell (PS) filled glass‐epoxy composites and to compare …

This study investigates the sliding wear behavior of hybrid epoxy composites reinforced with
alternating layers of glass fiber mats and steel wire mesh. The objective is to enhance the …

Drilling is one of the primary and most preferred machining operations for producing holes in
composite materials. Unlike conventional materials, drilling of fiber reinforced polymer (FRP) …

This paper reports on a data driven machine learning (ML) approach to analyze and predict
the erosion behavior of titanium oxide (titania) filled ramie-epoxy composites. ML models are …