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While performance demands in the natural world are varied, graded lattice structures reveal distinctive mechanical properties with tremendous engineering application potential. For biomechanical functions where mechanical qualities are required from supporting under external loading and permeability is crucial which affects bone tissue engineering, the geometric design in lattice structure for bone scaffolds in loading-bearing applications is necessary. However, when tweaking structural traits, these two factors frequently clash. For graded lattice structures, this study aims to develop a design-optimization strategy to attain improved attributes across different domains.

To handle diverse stress states, parametric modeling is used to produce strut-based lattice structures with spatially varied densities. The tailored initial gradients in lattice structure are subject to automatic property evaluation procedure that hinges on finite element method and computational fluid dynamics simulations. The geometric parameters of lattice structures with numerous objectives are then optimized using an iterative optimization process based on a non-dominated genetic algorithm.

The initial stress-based design of graded lattice structure with spatially variable densities is generated based on the stress conditions. The results from subsequent dual-objective optimization show a series of topologies with gradually improved trade-offs between mechanical properties and permeability.

In this study, a novel structural design-optimization methodology is proposed for mathematically optimizing strut-based graded lattice structures to achieve enhanced performance in multiple domains.

This study aims to investigate the mechanical properties of sustainable recycled polypropylene (rPP) composite materials integrated with spherical silicon carbide (SiC) particles.

A representative volume element (RVE) analysis is employed to predict the Young’s modulus of rPP filled with spherical-shaped SiC at varying volume percentages (i.e. 10, 20 and 30%).

The investigation reveals that the highest values of Young’s modulus, tensile strength, flexural strength and mode 1 frequency are observed for the 30% rPP/SiC samples, exhibiting increases of 115, 116, 62 and 15%, respectively, compared to pure rPP. Fractography analysis confirms the ductile nature of pure rPP and the brittle behavior of the 30% rPP/SiC composite. Moreover, the RVE method predicts Young’s modulus more accurate than micromechanical models, aligning closely with experimental results. Additionally, results from ANSYS simulation tests show tensile strength, flexural strength and frequency within a 10% error range when compared to experimental data.

This study contributes to the field by demonstrating the mechanical enhancements achievable through the incorporation of sustainable materials like rPP/SiC, thereby promoting environmentally friendly engineering solutions.