Design-Informed Generative Modelling using Structural Optimization

TL;DR

The paper tackles the challenge of converting mathematically optimal structural designs into ready-to-manufacture parametric CAD models by proposing a unified design-informed workflow. It integrates topology optimization (SIMP), skeletonization, frame extraction, sequential size and layout optimization, and CAD generation via Constructive Solid Geometry within a Rhino-Grasshopper environment, followed by Eurocode 3-based structural validation. Key contributions include a fully automated pipeline from continuum topology to a discrete frame with validated performance, and a comparative study of optimization strategies (SQP vs MMA) with node merging considerations. The approach enables manufacturable, code-compliant designs suitable for additive manufacturing and traditional fabrication, accelerating the transition from optimality to producible structures.

Abstract

Although various structural optimization techniques have a sound mathematical basis, the practical constructability of optimal designs poses a great challenge in the manufacturing stage. Currently, there is only a limited number of unified frameworks which output ready-to-manufacture parametric Computer-Aided Designs (CAD) of the optimal designs. From a generative design perspective, it is essential to have a single platform that outputs a structurally optimized CAD model because CAD models are an integral part of most industrial product development and manufacturing stages. This study focuses on developing a novel unified workflow handling topology, layout and size optimization in a single parametric platform, which subsequently outputs a ready-to-manufacture CAD model. All such outputs are checked and validated for structural requirements; strength, stiffness and stability in accordance with standard codes of practice. In the proposed method, first, topology-optimal model is generated and converted to a one-pixel-wide chain model using skeletonization. Secondly, a spatial frame is extracted from the skeleton for its member size and layout optimization. Finally, the CAD model is generated using constructive solid geometry trees and the structural integrity of each member is assessed to ensure structural robustness prior to manufacturing. Various examples presented in the paper showcase the validity of the proposed method across various engineering disciplines.

Figures (28)

• Figure 1: Structurally robust CAD model generation workflow from topology, size and layout optimal structure for a cantilevered beam example
• Figure 2: Topology optimization of a cantilever plate. Design, material, and optimization parameters are $\overline{E}$ = $2.1\ \times {10}^5\ {N/mm}^2$, ${E}_{min}$ = ${1\ \times 10}^{-9}\ {N/mm}^2$, $\nu$ = $0.3$, $p$ = $3$, $R$ = $1.2$, Maximum iterations = $200$.
• Figure 3: Illustration of skeletonization and pixels categorization
• Figure 4: Skeletonization of a cantilever plate example ($V_f$ = $0.5$)
• Figure 5: Compact graph model generation using important pixels