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Updated: Dec 6, 2025

Author Spotlight: Enhancing Fiber Composite Laminate Quality with the Wet Hand Lay-Up/Vacuum Bag Process
Published on: June 30, 2023
Optimal design and manufacture of variable stiffness laminated continuous fiber reinforced composites
Narasimha Boddeti1,2, Yunlong Tang3, Kurt Maute4
1Digital Manufacturing and Design Centre, Singapore University of Technology and Design, Singapore, Singapore. narasimha.boddeti@wsu.edu.
Abstract:
Advanced manufacturing methods like multi-material additive manufacturing are enabling realization of multiscale materials with intricate spatially varying microstructures and thus, material properties. This blurs the boundary between material and structure, paving the way to lighter, stiffer, and stronger structures. Taking advantage of these tunable multiscale materials warrants development of novel design methods that effectively marry the concepts of material and structure. We propose such a design to manufacture workflow and demonstrate it with laminated continuous fiber-reinforced composites that possess variable stiffness enabled by spatially varying microstructure. This contrasts with traditional fiber-reinforced composites which typically have a fixed, homogenous microstructure and thus constant stiffness. The proposed workflow includes three steps: (1) Design automation-efficient synthesis of an optimized multiscale design with microstructure homogenization enabling efficiency, (2) Material compilation-interpretation of the homogenized design lacking specificity in microstructural detail to a manufacturable structure, and (3) Digital manufacturing-automated manufacture of the compiled structure. We adapted multiscale topology optimization, a mesh parametrization-based algorithm and voxel-based multimaterial jetting for these three steps, respectively. We demonstrated that our workflow can be applied to arbitrary 2D or 3D surfaces. We validated the complete workflow with experiments on two simple planar structures; the results agree reasonably well with simulations.
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