.png){kind=icon}
.png){kind=icon}
Return
Morphological feedback for precise structural complexity control in topology optimization
.png){kind=icon}
PRE
AI
DOI：10.1016/j.compstruc.2026.108299.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
This paper presents a morphological feedback approach for precise structural complexity control in topology optimization, ensuring that the optimized design strictly satisfies the prescribed target number of holes. To address the critical limitations of existing explicit structural complexity control methods, particularly their dependence on restricted initial layouts and the spatial ambiguity of global topological invariants, the proposed framework establishes a closed-loop control system driven by morphological sensing. Leveraging the spontaneous topology-changing capability of a reaction–diffusion equation driven level set method, the framework enables autonomous hole nucleation, allowing flexible initialization from either a solid domain or an arbitrarily perforated configuration without predefined hole patterns. This generative capability is integrated with a morphological sensing module utilizing connected component analysis, which provides hole-resolved measurements to distinctly guide the evolution toward the exact target. To enforce this guidance, a gradient-based soft regulation strategy injects signed feedback signals into the physical sensitivity field to facilitate online bidirectional adjustment. This mechanism enables the system to autonomously switch between nucleation and annihilation modes, thereby avoiding the monotonic reduction constraint common to most existing explicit structural complexity control schemes. Numerical studies on representative benchmarks demonstrate that the proposed approach robustly attains the prescribed structural complexity target with stable convergence, providing an effective and flexible tool for structural design.
Keywords:
Topology optimization
Level set method
Reaction–diffusion
Structural complexity control
Morphological feedback
Journal
C
IF:
4.8
Papers:
198
Citations:
0