Algorithmic evolution of structures from monoliths to bionic design via topology optimization

Abstract

The article presents the results of advanced digital design methods, focusing on topology optimization and generative design within the construction industry. Currently, the sector faces a critical challenge – achieving a significant reduction in metal consumption without compromising the stability or durability of structures. In an era of resource scarcity and stringent environmental regulations, shifting toward the rational distribution of materials has become a primary objective for the engineering community. For the comparative analysis, three distinct structural configurations were selected: a standard solid steel beam, a conventional truss, and an innovative bionic structure that mimics natural load-bearing principles. The entire numerical modeling cycle was conducted using the Autodesk Fusion 360 environment. The core focus of the study is directed at algorithmic design – a process where the final geometry emerges not from an engineer’s subjective vision, but as a direct result of the mathematical calculation of stress fields. The performed calculations demonstrated that the bionic model, shaped by stripping away non-loaded zones, ensures the most logical transfer of internal forces. Experimental data confirmed that generative design allows for a structural weight reduction of up to 80% compared to the monolithic prototype. Crucially, the required safety factor remains fully intact. Furthermore, the study highlights that such weight optimization directly correlates with a reduced carbon footprint, as less raw material extraction and energy-intensive smelting are required. These results clearly illustrate that moving away from massive forms in favor of complex algorithmic structures represents a logical evolution of engineering toward resource efficiency. The integration of these geometries with additive manufacturing (3D printing) further expands the horizons of architectural freedom. The study’s findings hold direct practical value for the design of next-generation lightweight metal structures. Implementing such high-level automated systems into educational programs and industrial workflows will not only save on materials and logistics but also lay the foundation for sustainable construction where every component operates at its physical limit. Ultimately, this approach transforms the structural engineer from a traditional draughtsman into a curator of algorithmic processes