Enhancing HFSS Design Efficiency through Python-Based Automation: A Case Study of Sierpinski Triangle Fractal

The Sierpinski Triangle is a well-established mathematical structure with a clearly defined geometric formulation. However, its significance extends beyond pure mathematics, particularly in RF engineering. Fractal geometries like the Sierpinski Triangle have proven highly beneficial for designing high-fre-quency components such as antennas, waveguides and filters. However, manu-ally creating these intricate structures with software simulators can be time-con-suming and error prone. This paper presents a novel approach to optimizing the design process of the Sierpinski Triangle fractal pattern using the High Frequency Structure Simulator (HFSS) and Python scripting. A test scenario was conducted to assess the adaptability of the automated process across different fractal itera-tion levels. A comparative analysis between automated and manual design meth-ods was performed, focusing on key metrics such as time efficiency, design ac-curacy, and flexibility. The findings demonstrate significant time savings, re-duced human intervention, and improved precision, underscoring the advantages of automation in high-frequency component design.