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UEC Int’l Mini-Conference No.54                                                               39







            turing. This represents the first systematic cou-  [5] K. Deb, A. Pratap, S. Agarwal, and T. Me-
            pling of dynamic frequency analysis with multi-      yarivan, “A Fast and Elitist Multiobjec-
            objective topology optimization on dense tetra-      tive Genetic Algorithm: NSGA-II,” IEEE
            hedral meshes. At the same time, the reliance        Transactions on Evolutionary Computation,
            on static, linear FEM and the need to calibrate      Vol. 6, No. 2, pp. 182–197, 2002.
            filtering radii highlight areas for improvement.
            Geometric distortions may arise if filter param-  [6] E. Zitzler and L. Thiele, “SPEA2: Improv-
                                                                 ing the Strength Pareto Evolutionary Al-
            eters are not carefully chosen, and real-world
            durability under variable or nonlinear loads re-     gorithm,” Evolutionary Methods for Design,
            mains to be assessed.                                Optimization and Control with Applications
              Practically,  this  framework   accelerates        to Industrial Problems, pp. 95–100, 2001.
            the design cycle by producing 3D-printable,
                                                              [7] Q. Zhang and H. Li, “MOEA/D: A Mul-
            lightweight structures with minimal manual           tiobjective Evolutionary Algorithm Based
            intervention, paving the way for rapid prototyp-     on Decomposition,” IEEE Transactions on
            ing in aerospace, automotive, and biomedical         Evolutionary Computation, Vol. 11, No. 6,
            applications. Future extensions will incorporate     pp. 712–731, 2007.
            nonlinear and fatigue analyses, embed manufac-
            turing constraints such as print orientation and  [8] M. Langelaar, “Topology Optimization for
            anisotropy directly into the optimization loop,      Additive Manufacturing: Status and Chal-
            and explore co-optimization with composite           lenges,” Additive Manufacturing, Vol. 30,
            materials to further enhance performance and         100894, 2019.
            robustness.
                                                              [9] M. Y. Wang, W. X. Zhong, and Y. Wang,
                                                                 “Connectivity-Based Topology Optimiza-
            8    Acknowledgments                                 tion for Additive Manufacturing,” Computer

                                                                 Methods in Applied Mechanics and Engi-
            Space to thank others for their contributions and    neering, Vol. 350, pp. 331–353, 2019.
            support to the research or project. Thank the
            funders (grant, shcolarship).                     [10] P. Zhu, J. Zheng, and Z. Pan, “A Morpho-
                                                                 logical Filter Approach for Minimum Fea-
                                                                 ture Size Control in Topology Optimiza-
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