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#graph neural networks Open access

##拓扑优化算法的基于图神经网络的融合

Jincheng Zhang
Aug 2026 · Zenodo (CERN European Organization for Nuclear Research)
Topology Optimization in Engineering

Abstract

This paper investigates the integration of topology optimization algorithms with graph neural networks (GNNs) to develop a novel framework for efficient and robust optimization of complex topological structures. Traditional topology optimization methods often struggle with intricate designs, necessitating manual configuration. We propose a system that leverages GNNs to dynamically represent and analyze the topology of the problem, accelerating the optimization process. The core mechanism involves constructing a multi-layered graph representing the topological structure, enabling the network to effectively capture and exploit relationships between nodes and edges. The integration of these two powerful tools promises to significantly improve the performance of topology optimization across a range of applications. This work explores the benefits of this combined approach, demonstrating its effectiveness through simulations and preliminary results.

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