Multi-resolution space-time topology optimization

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Abstract

In the realm of traditional additive manufacturing, design and fabrication sequence planning have historically followed separate tracks. However, recent strides in the field, particularly in the utilization of robotic arms with multiple degrees of freedom, have brought forth a revolutionary approach known as Space-Time Topology Optimization (STTO). This groundbreaking algorithm breaks down the barriers between design and fabrication by simultaneously optimizing the structure and fabrication sequence. It achieves this feat by employing density and time fields as design variables, allowing for a holistic and integrated approach to the manufacturing process.
However, within the framework of STTO, multiple iterations of finite element computations become necessary. This results in a substantial computational burden throughout the overall process.
My contribution within STTO lies in its adoption of a multi-resolution strategy. This strategy enables the use of different resolutions for the design fields, enhancing computational efficiency. Coarsening, a critical component of this strategy, is implemented through a sophisticated weighted average scheme. This coarsening process facilitates the construction of stiffness matrices with significantly reduced finite element calculations, resulting in substantial time savings during the optimization process.
The impact of coarsening in STTO has been rigorously studied across various levels, yielding remarkable results and advantages. In 2D scenarios, this approach has achieved an impressive 5-fold reduction in computation time, while in the more complex 3D domain, it has led to an astounding 30-fold decrease. Moreover, it's worth noting that compliance, a crucial performance metric, maintains its integrity even with coarsening, with compliance drop remaining below 5% for levels deemed acceptable. This study illuminates the profound implications of coarsening within the STTO framework, emphasizing the significant strides made in computational efficiency while ensuring structural integrity and performance.