Material characterization and precise finite element analysis of fiber reinforced thermoplastic composites for 4D printing

Yu, Yuxuan; Liu, Haolin; Qian, Kuanren; Yang, Humphrey; McGehee, Matthew; Gu, Jianzhe; Luo, Danli; Yao, Lining; Zhang, Yongjie

doi:10.1016/j.cad.2020.102817

Cited by 54 publications

(29 citation statements)

References 30 publications

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“…Still, this approach requires taking small time steps to avoid divergence, leading to long simulation rollout (i.e., a trial of simulation) time and cannot afford real-time CAD interactions and iterations. Similarly, although elastic rods [31] have been used to assist the design of deformable objects, their limitations (i.e., tradeoff between noncircular cross-section shapes or viscoelastic materials [5]) make them inapplicable to certain morphing materials design spaces (e.g., the viscoelastic transformation of [40,41,47]). Compared to these methods, SimuLearn can provide more accurate predictions and support larger design spaces while requiring similar or less computation time.…”

Section: Simulation In Morphing Materialsmentioning

confidence: 99%

“…For instance, FEA has been applied to design adaptive actuators [6], multi-stage transformations [6,7], and self-folding structures of complex topologies [50]. A recent work [47] also demonstrated using FEA as a backend engine to design robust artifacts made of composite materials. Yet, FEA involves establishing and solving large linear systems, making them time-consuming to perform even on supercomputing servers.…”

Section: Simulation In Morphing Materialsmentioning

confidence: 99%

“…We use the analysis software Abaqus and follow [47] to establish a physically-based FEA model for our material system. This FEA model adopts a two-stage strategy to simulate 4D printed PLA: the first stage corresponds to the residual stress-induced transformation, and the second stage depicts PLA's creeping under gravity.…”

Section: Fea Modelingmentioning

confidence: 99%

“…The accuracy of this FEA model is reported to be above 95%. We refer readers to [47] for more technical details. The FEA solvers are configured to output a smooth animation of transformation processes -the first stage solver outputs ten equally spaced frames by procedurally releasing 10% of the total residual stress.…”

Section: Fea Modelingmentioning

confidence: 99%

“…Advanced methods such as elastic rods [5,31] are also restricted to certain material properties and shapes, thus having a limited morphing materials design space. In contrast, while FEA is physically-based, their sheer computational cost renders them unviable in interactive design tools [47]. More, morphing materials are often soft during transformation and have virtually infinite degrees of freedom, requiring high-resolution discrete models to avoid divergence, which further slows down the computation.…”

Section: Introductionmentioning

confidence: 99%

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SimuLearn

Yang

Qian

Liu

et al. 2020

Proceedings of the 33rd Annual ACM Symposium on User Interface Software and Technology

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Morphing materials allow us to create new modalities of interaction and fabrication by leveraging the materials' dynamic behaviors. Yet, despite the ongoing rapid growth of computational tools within this realm, current developments are bottlenecked by the lack of an effective simulation method. As a result, existing design tools must trade-off between speed and accuracy to support a real-time interactive design scenario. In response, we introduce SimuLearn, a data-driven method that combines finite element analysis and machine learning to create real-time (0.61 seconds) and truthful (97% accuracy) morphing material simulators. We use mesh-like 4D printed structures to contextualize this method and prototype design tools to exemplify the design workflows and spaces enabled by a fast and accurate simulation method. Situating this work among existing literature, we believe SimuLearn is a timely addition to the HCI CAD toolbox that can enable the proliferation of morphing materials.

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Section: Simulation In Morphing Materialsmentioning

confidence: 99%

Section: Simulation In Morphing Materialsmentioning

confidence: 99%

Section: Fea Modelingmentioning

confidence: 99%

Section: Fea Modelingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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SimuLearn

Yang

Qian

Liu

et al. 2020

Proceedings of the 33rd Annual ACM Symposium on User Interface Software and Technology

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Human–Material Interaction Enabled by Fused Filament Fabrication 4D Printing

Lalegani Dezaki,

Zolfagharian,

Demoly

et al. 2024

Adv Eng Mater

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This review delves into four‐dimensional printing (4DP) through fused filament fabrication (FFF) and its implications for human‐material interaction (HMI). FFF 4DP’s emergence in HMI represents a nascent and evolving concept worthy of deeper exploration. The article introduces FFF 4DP’s fundamental principles, methodologies, materials, and associated benefits and challenges. Its primary focus is the intersection between FFF 4DP and HMI, investigating the potential of employing FFF 4D printed objects as interactive interfaces. Various HMI scenarios are examined, including applications in soft actuators, smart toys, household devices, smart consumer products, 4D textiles, and customizable wood‐based items. Moreover, the article discusses the current state‐of‐art and development in the field, highlighting notable projects that integrate FFF 4DP into HMI to advance environmental sustainability. It also identifies key challenges/limitations requiring attention for the widespread adoption of 4DP in HMI applications. This work offers an in‐depth analysis of FFF 4DP within the HMI context, underscoring its potential to transform human interactions with machines and smart devices. It introduces innovative features for dynamic and adaptable interfaces, promising to revolutionize user experiences. The article serves as a valuable resource for researchers, practitioners, and designers interested in exploring the exciting possibilities of FFF 4DP in the realm of HMI.This article is protected by copyright. All rights reserved.

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The Design of 4D‐Printed Hygromorphs: State‐of‐the‐Art and Future Challenges

Kergariou

Demoly

Perriman

et al. 2022

Adv Funct Materials

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In recent years, 4D printing has allowed the rapid development of new concepts of multifunctional/adaptive structures. The 4D printing technology makes it possible to generate new shapes and/or property-changing capabilities by combining smart materials, multiphysics stimuli, and additive manufacturing. Hygromorphs constitute a specific class of new smart materials where their properties and morphing capabilities are dependent on the surrounding humidity, which drives actuation. Although multiple efforts have been made to fabricate hygromorph demonstrators, a comprehensive design process to produce hygromorphs by multiple 4D printing techniques is not yet available. The broad aim of this review and concept paper is to i) highlight existing scientific and technology gaps in the field of 4D-printed hygromorphs, ii) identify tools existing in other research fields for filling those gaps, and iii) discuss a series of guidelines for tackling future challenges and opportunities to develop 4D-printed composite hygromorph materials and related manufacturing processes. Accordingly, this review describes the materials and additive manufacturing techniques used for hygromorph composite fabrication. Moreover, the relevant parameters that control actuation, the models selection and performance, the design methods and the actuation measurements for customized 4D-printed hygromorph materials, are discussed.

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Material characterization and precise finite element analysis of fiber reinforced thermoplastic composites for 4D printing

Cited by 54 publications

References 30 publications

SimuLearn

SimuLearn

Human–Material Interaction Enabled by Fused Filament Fabrication 4D Printing

The Design of 4D‐Printed Hygromorphs: State‐of‐the‐Art and Future Challenges

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