Inverse design of three-dimensional fiber reinforced composites with spatially-varying fiber size and orientation using multiscale topology optimization

Jung, Taehoon; Lee, Jae‐Wook; Nomura, Tsuyoshi; Dede, Ercan M.

doi:10.1016/j.compstruct.2021.114768

Cited by 25 publications

(5 citation statements)

References 24 publications

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“…Various benchmark and multi-load structure problems have been studied, and it was concluded that locally varying FRC materials augment the global stiffness of the structure more than a fixed fiber volume fraction or isotropic multi-material structure. In continuation of the Kim methodology, Jung [132] proposed a 3D TO approach for designing FRC structures with spatially varying fiber fractions and orientations. Finally, a work by Boddeti et al [133] introduced a complete design to the manufacturing workflow for laminated continuous fiber-reinforced composites with variable stiffness enabled by spatially varying micro-structures.…”

Section: Materials Parameterizationmentioning

confidence: 99%

A Review on Topology Optimization Strategies for Additively Manufactured Continuous Fiber-Reinforced Composite Structures

Gandhi

Minak

2022

Applied Sciences

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Topology Optimization (TO) recently gained importance due to the development of Additive Manufacturing (AM) processes that produce components with good mechanical properties. Among all additive manufacturing technologies, continuous fiber fused filament fabrication (CF4) can fabricate high-performance composites compared to those manufactured with conventional technologies. In addition, AM provides the excellent advantage of a high degree of reconfigurability, which is in high demand to support the immediate short-term manufacturing chain in medical, transportation, and other industrial applications. CF4 enables the fabrication of continuous fiber-reinforced composite (FRC) materials structures. Moreover, it allows us to integrate topology optimization strategies to design realizable CFRC structures for a given performance. Various TO strategies for attaining lightweight and high-performance designs have been proposed in the literature, exploiting AM’s design freedom. Therefore, this paper attempts to address works related to strategies employed to obtain optimal FRC structures. This paper intends to review and compare existing methods, analyze their similarities and dissimilarities, and discuss challenges and future trends in this field.

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Section: Materials Parameterizationmentioning

confidence: 99%

A Review on Topology Optimization Strategies for Additively Manufactured Continuous Fiber-Reinforced Composite Structures

Gandhi

Minak

2022

Applied Sciences

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“…See Hu [2021] for a survey (called "free material optimization"). The most common approach for orientation optimization is to set density and orientation as design variables and optimize an objective such as compliance [Chu et al 2021;da Silva et al 2020;Jung et al 2022] or the Tsai-Wu failure criterion [Ma et al 2022] with a gradient-based optimizer. To address the checkerboard pattern issue (periodicity of the orientation variables), researchers usually use filtering [Andreassen et al 2011] to smooth the design variable field (e.g., through a weighted average of neighboring elements).…”

Section: Related Work 21 Fiber Orientation Optimization In 3d Printingmentioning

confidence: 99%

More Stiffness with Less Fiber: End-to-End Fiber Path Optimization for 3D-Printed Composites

Sun¹,

Roeder²,

Xue³

et al. 2022

Preprint

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In 3D printing, stiff fibers (e.g., carbon fiber) can reinforce thermoplastic polymers with limited stiffness. However, existing commercial digital manufacturing software only provides a few simple fiber layout algorithms, which solely use the geometry of the shape. In this work, we build an automated fiber path planning algorithm that maximizes the stiffness of a 3D print given specified external loads. We formalize this as an optimization problem: an objective function is designed to measure the stiffness of the object while regularizing certain properties of fiber paths (e.g., smoothness). To initialize each fiber path, we use finite element analysis to calculate the stress field on the object and greedily "walk" in the direction of the stress field. We then apply a gradient-based optimization algorithm that uses the adjoint method to calculate the gradient of stiffness with respect to fiber layout. We compare our approach, in both simulation and real-world experiments, to three baselines: (1) concentric fiber rings generated by Eiger, a leading digital manufacturing software package developed by Markforged, ( 2) greedy extraction on the simulated stress field (i.e., our method without optimization), and (3) the greedy algorithm on a fiber orientation field calculated by smoothing the simulated stress fields. The results show that objects with fiber paths generated by our algorithm achieve greater stiffness while using less fiber than the baselines-our algorithm improves the Pareto frontier of object stiffness as a function of fiber usage. Ablation studies show that the smoothing regularizer is needed for feasible fiber paths and stability of optimization, and multi-resolution optimization help reduce the running time compared to single-resolution optimization.CCS Concepts: • Applied computing → Computer-aided manufacturing.

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“…The fiber orientation tensor-based approach provides improved convexity because the rotation tensor is unused and it can be used for various applications. [19][20][21] However, the growth of the anisotropy is uncontrolled during optimization, despite the fact that it affects the optimized results.…”

Section: Introductionmentioning

confidence: 99%

Penalized anisotropy: Controlling anisotropy growth in concurrent optimization of topology and fiber orientation for orthotropic composite materials

Ichihara,

Ueda,

Yokozeki

2024

Journal of Composite Materials

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The topology and fiber orientation of fiber-reinforced composite structures must be designed computationally to fully demonstrate their anisotropic mechanical properties. Optimization of the topology and fiber orientation is performed either sequentially or concurrently. In the sequential method, topology optimization is performed first, followed by fiber orientation optimization. This separated optimization process does not consider material anisotropy during the topology optimization process. The concurrent method has the potential to realize better results by considering the anisotropic properties during topology optimization. However, the concurrent method often obtains locally optimal solutions because of material anisotropy in the initial optimization process. A continuation approach for anisotropy, which starts with weak anisotropy and then improves the anisotropy gradually, resolves this issue. This paper proposes a new concurrent optimization that can control the growth of anisotropy. The growth of anisotropy affects the topology, which is used to determine a better structure. Optimization results were obtained serially by varying the growth of anisotropy, which allowed a highly optimal topology and fiber orientation to be explored by considering their anisotropic nature.

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Inverse design of three-dimensional fiber reinforced composites with spatially-varying fiber size and orientation using multiscale topology optimization

Cited by 25 publications

References 24 publications

A Review on Topology Optimization Strategies for Additively Manufactured Continuous Fiber-Reinforced Composite Structures

A Review on Topology Optimization Strategies for Additively Manufactured Continuous Fiber-Reinforced Composite Structures

More Stiffness with Less Fiber: End-to-End Fiber Path Optimization for 3D-Printed Composites

Penalized anisotropy: Controlling anisotropy growth in concurrent optimization of topology and fiber orientation for orthotropic composite materials

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