Generative design of physical objects using modular framework
نویسندگان
چکیده
In recent years generative design techniques have become firmly established in numerous applied fields, especially engineering. These methods are crucial for automating the initial stages of engineering various structures, which reduces amount routine work. However, existing approaches limited by specificity problem under consideration. addition, they do not provide desired flexibility choosing a method particular problem. To avoid these issues, we proposed general approach to an arbitrary and implemented novel open-source framework called GEFEST (Generative Evolution For Encoded STructure) on its basis. This is based three principles: sampling, estimation, optimization. ensures freedom adjustment solution therefore enables construction most suitable one. A series experimental studies was conducted confirm effectiveness framework. It involved synthetic real-world cases (coastal engineering, microfluidics, thermodynamics, oil field planning). The flexible structure makes it possible obtain results that surpass baseline state-of-the-art solutions: 12% improvement coastal problem; 9% microfluidics; 8% thermodynamics 7% planning.
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ژورنال
عنوان ژورنال: Engineering Applications of Artificial Intelligence
سال: 2023
ISSN: ['1873-6769', '0952-1976']
DOI: https://doi.org/10.1016/j.engappai.2022.105715