A Computational Framework for Electric Scooter Neck Design Using Non-Uniform Rational B-Spline-Based Geometric Reconstruction of Topology-Optimized Structures

Abstract

This study presents a hybrid Non-Uniform Rational B-Spline (NURBS) methodology for the geometric reconstruction of topology-optimized structural components. NURBS are employed exclusively as a post-processing tool; all structural analyses are performed using standard finite elements (SOLID187 elements, ANSYS Mechanical R19.2), and isogeometric analysis (IGA) is not used. The methodology is validated on an Al 6061-T6 electric scooter neck under a 600 N static load. Two SIMP optimization iterations followed by a hybrid NURBS reconstruction reduce the component mass from 1.247 kg to 0.531 kg, achieving a 57.4% mass reduction. Finite element re-validation of the reconstructed geometry yields a maximum von Mises stress of 126.45 MPa (safety factor, SF = 2.18, exceeding the 2.0 requirement), a maximum deflection of 2.31 mm, and a first natural frequency of 127 Hz. Mesh convergence between the 2.5 mm and 1.25 mm refinements is Δ = 0.90%. Relative to the direct SIMP output (201 MPa), NURBS reconstruction reduces the peak stress by 37%, demonstrating that geometric post-processing is not a neutral step but a critical determinant of structural performance. Both fully automated STL reconstruction and edge-based NURBS reconstruction failed for this geometry class due to non-manifold topology and patch discontinuities, respectively. The proposed hybrid region-decomposition approach is the only method that has produced a watertight, FEA-compatible CAD model.