MULTISCALE COMPUTATIONAL DESIGN AND STRUCTURAL-FUNCTIONAL OPTIMIZATION OF FLY ASH-REINFORCED ALUMINUM MATRIX COMPOSITES

Abstract

For sustainable development and utilizing industrial waste, this study comprehensively researches multiscale computational design and optimization of fly ash -aluminum composites (AMC). With elevated level modeling of these materials the methodology integrates atomistic to macroscale modeling. Molecular dynamics (MD) enables understanding of interfacial interaction and finite element method (FEM) is utilized in the macroscale property analysis. Accelerated design is enabled largely by ML (auxiliary models that mimic input-output relationships by computer). At the atomic level, we have discovered that chemical reactions (4Al + 3SiO2 = 2Al2O3 + 3Si), wettability and surface roughness are all crucial for strong interfacial bondings and force transfer. By microscale- and macroscale FEM analyses governing rules are derived to achieve high-level mechanical properties improvement s, including tetra strength about (19.56%), hardness roughly (34.67 months),anti -fatigue power improved approximately (26.87%) and wear resistance raised by about (31.45%) fly ashes further bring about a convergence of improved material functional properties: contraction coefficient and specific gravity (valuable for ultra-high vacuum systems etc), not least it is an ideal electromagnetic shielding/damping medium thereby improving utility. Using of ML models allows to achieve very good predictive performance (e.g. R2 of 0.990 for melting point) while maintaining computational advantages. Experimental check with SEM EDX, XRD and FTIR and several mechanical experiments on the other hand aid large system computation. Design of Experiments like Topsis and Fuzzy logic have been developed to optimize the production parameters and developed counterstrategy of high-speed machining. This integrated computational-experimental study validates the potential of fly ash as a green AMC reinforcement material, consistent with circular economy principles.