Constitutive and Predictive Modeling of cDLP Additively Manufactured Hyperelastic Polymers for Soft Robotics
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Recent developments in polymer chemistries along with timely advancements in the field of additive manufacturing (AM) have expanded the possibilities for soft material application. Specifically, novel UV-curable, ultra-stretchable (hyperelastic) liquid resins have been generated for compatibility with continuous digital light processing (cDLP) AM, a subset of vat photopolymerization (VP). However, the use of these materials in relevant applications is impeded by a lack of thorough mechanical testing and subsequent material modeling to clarify behavior. This project aims to address this issue through (1) building a framework of multimodal experimental test data, (2) fashioning descriptive constitutive (material) models, and (3) scripting representative finite element simulations, all towards the implementation of hyperelastic materials in soft robotics.
Robert L. Lowe
Primary Advisor's Department
Mechanical and Aerospace Engineering
Stander Symposium project, School of Engineering
United Nations Sustainable Development Goals
Industry, Innovation, and Infrastructure; Responsible Consumption and Production
"Constitutive and Predictive Modeling of cDLP Additively Manufactured Hyperelastic Polymers for Soft Robotics" (2020). Stander Symposium Projects. 1956.