Optimizing Lightweight Building Construction with Artificial Intelligence: A Focus on Efficiency, Sustainability, and Practical Design Solutions

The integration of artificial intelligence (AI) into lightweight building construction has unlocked significant opportunities to optimize design, enhance material efficiency, and promote sustainability. This study explores AI’s transformative impact, combining machine learning, generative design, and lifecycle assessment (LCA) methodologies to address the challenges of balancing weight reduction with structural integrity. AI-driven algorithms predicted material properties with over ۹۵% accuracy, enabling precise selection of advanced lightweight materials such as carbon fiber composites and bio-based polymers. Structural optimization using generative design tools reduced building weight by an average of ۲۵%, while maintaining safety factors exceeding ۲.۵. Fabrication waste was minimized to less than ۴%, representing a ۶۰% reduction compared to traditional methods. Furthermore, lifecycle assessment revealed a ۲۲% decrease in embodied carbon emissions and a ۱۷% reduction in construction energy consumption. These improvements were validated through finite element analysis (FEA) and the testing of physical prototypes, which withstood loads ۱.۵ times their design limits and demonstrated resilience to environmental stressors. This research highlights the potential of AI to transform lightweight construction, achieving cost savings, environmental benefits, and increased design adaptability. The findings underscore the need for continued research into scalable AI solutions, integration with robotics, and the development of industry standards to facilitate widespread adoption. By bridging the gap between technological innovation and sustainable practices, AI sets a new benchmark for the future of construction.

کلیدواژه ها:

Lightweight construction ، artificial intelligence ، material optimization ، generative design ، sustainability ، lifecycle assessment