Glass Fiber-Epoxy Composites with Carbon Nanotube Fillers for Enhancing Properties in Structure Modeling and Analysis Using Artificial Intelligence Technique.

Hybrid composite materials are a form of material that incorporates more than one type of reinforcement into a matrix to attain enhanced qualities. This usually includes the use of nanoparticle fillers in classic advanced composites with fiber reinforcements such as carbon or glass. In the current investigation, the impact of carbon nanopowder filler on the wear and thermal performance of the chopped strand mat E-glass fiber-reinforced epoxy composite (GFREC) were analyzed. Multiwall carbon nanotube (MWCNT) fillers were used; they react with the resin system to contribute a significant improvement of properties in the polymer cross-linking web. The experiments were carried out employing the central composite method of design of experiment (DOE). A polynomial mathematical model was created using response surface methodology (RSM). To forecast the wear rate of composites, four machine learning (ML) regression models were built. The study's findings indicate that the addition of carbon nanopowder has a substantial impact on the wear behavior of composites. This is mostly owing to the homogeneity created by the carbon nanofillers in uniformly dispersing the reinforcements in the matrix phase. Results revealed that a load of 1.005 kg, a sliding velocity of 1.499 m/s, a sliding distance of 150 m, and 15 wt % of filler were found to be the optimal parameters for the efficient reduction of specific wear rate. Composites with 10 and 20% carbon contents exhibit lower thermal expansion coefficients than plain composites. These composites' coefficients of thermal expansion fell by 45 and 9%, respectively. If the carbon proportion increases beyond 20%, so will the thermal coefficient of expansion.