Evolutionary Algorithm-Based Design and Performance Evaluation of Wood-Plastic Composite Roof Panels for Low-Cost...

Area of Science:

• Materials Science and Engineering
• Computational Mechanics
• Sustainable Construction

Background:

• Wood-plastic composites (WPCs) offer sustainable and cost-effective solutions for construction, especially in low-cost housing.
• Designing WPC panels requires balancing structural integrity, serviceability, and manufacturing constraints.
• Optimizing the cross-sectional shape is crucial for efficient material usage and performance.

Purpose of the Study:

• To optimize the cross-sectional shape of WPC roof panels to minimize material usage.
• To ensure compliance with deflection and stress constraints under various loading conditions.
• To compare the effectiveness of genetic algorithms (GA) and particle swarm optimization (PSO) for WPC panel design.

Main Methods:

• Utilized evolutionary algorithms (GA and PSO) to optimize sinusoidal and trapezoidal WPC panel profiles.
• Integrated finite element analysis (FEA) to evaluate structural performance under uniform loads and self-weight.
• Determined the modulus of elasticity of WPC material via experimental three-point bending tests.

Main Results:

• The trapezoidal WPC panel profile demonstrated superior deflection performance compared to the sinusoidal profile.
• Particle swarm optimization (PSO) exhibited higher solution optimality and faster convergence than the genetic algorithm (GA).
• The optimized designs successfully minimized material usage while meeting structural and serviceability requirements.

Conclusions:

• Trapezoidal WPC roof panels are optimal for achieving superior deflection performance and material efficiency.
• PSO is a more effective optimization algorithm than GA for designing WPC structural elements.
• The study validates the potential of WPCs in sustainable low-cost housing and informs algorithm selection for engineering design.