The Payne effect in finite viscoelasticity: constitutive modelling based on fractional derivatives and intrinsic time scales

By A. Lion, C. Kardelky. 2004

150 citations recorded by the source corpus.

Subfields: Atomic and Molecular Physics, and Optics, Biomedical Engineering, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/e77968b46666f3fd18bc18e7d808183cfa8d4c32

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Atomic and Molecular Physics, and Optics

1. Martin Kröger
2. Wing Kam Liu
3. Ying Li
4. Brendan C. Abberton

In Biomedical Engineering

1. Ying Li
2. Brendan C. Abberton
3. Wing Kam Liu
4. Martin Kröger
5. Guido Raos
6. Giuseppe Allegra
7. M. Vacatello
8. Billy D. Todd

In Statistics and Probability

1. Wing Kam Liu
2. Ying Li
3. Brendan C. Abberton
4. Martin Kröger
5. Iman Hajirasouliha

Citations in the corpus

• Theories and simulations of polymer-based nanocomposites: From chain statistics to reinforcement (2008, background): “[155–159] for some entry points to this literature.”
• Challenges in Multiscale Modeling of Polymer Dynamics (2013, background): “Lion and Kardelky [333] applied a similar fractional diffusion equation to study the Payne effect in the finite viscoelasticity of carbon-black-filled elastomers.”
• Composites with recycled rubber aggregates: Properties and opportunities in construction (2018, methodology): “characteristics, reduce cost and increase elongation capacity [Gil-Negrete N. 2013]. Teh (2004) reported”