Dielectric elastomers are employed on a wide variety of adaptive structures. Many of these soft elastomers exhibit significant rate-dependencies in their response. Accurately quantifying this viscoelastic behavior is non-trivial and in many instances a nonlinear modeling framework is required. Fractional-order operators have been applied to modeling viscoelastic behavior for many years, and recent research has shown fractional-order methods to be effective for nonlinear frameworks. This implementation can become computationally expensive to achieve an accurate approximation of the fractional-order derivative. In this paper, we demonstrate the effectiveness of using quadrature techniques in approximating the Riemann-Liouville definition for fractional derivatives in the context of developing a nonlinear viscoelastic model.
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ASME 2018 Conference on Smart Materials, Adaptive Structures and Intelligent Systems
September 10–12, 2018
San Antonio, Texas, USA
Conference Sponsors:
- Aerospace Division
ISBN:
978-0-7918-5194-4
PROCEEDINGS PAPER
Numerical Techniques to Model Fractional-Order Nonlinear Viscoelasticity in Soft Elastomers
Paul Miles,
Paul Miles
North Carolina State University, Raleigh, NC
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Graham Pash,
Graham Pash
North Carolina State University, Raleigh, NC
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William Oates,
William Oates
Florida State University, Tallahassee, FL
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Ralph C. Smith
Ralph C. Smith
North Carolina State University, Raleigh, NC
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Paul Miles
North Carolina State University, Raleigh, NC
Graham Pash
North Carolina State University, Raleigh, NC
William Oates
Florida State University, Tallahassee, FL
Ralph C. Smith
North Carolina State University, Raleigh, NC
Paper No:
SMASIS2018-8102, V001T03A021; 7 pages
Published Online:
November 14, 2018
Citation
Miles, P, Pash, G, Oates, W, & Smith, RC. "Numerical Techniques to Model Fractional-Order Nonlinear Viscoelasticity in Soft Elastomers." Proceedings of the ASME 2018 Conference on Smart Materials, Adaptive Structures and Intelligent Systems. Volume 1: Development and Characterization of Multifunctional Materials; Modeling, Simulation, and Control of Adaptive Systems; Integrated System Design and Implementation. San Antonio, Texas, USA. September 10–12, 2018. V001T03A021. ASME. https://doi.org/10.1115/SMASIS2018-8102
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