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In most analytical models, back diffusion is neglected.
Most analytical models make the fundamental assumption that shear deformation in the viscoelastic core yields the largest damping and compressional deformation is negligible.
Most analytical models for the design of piled embankments or load transfer platforms with geosynthetic reinforcement (GR) include two calculation steps.
This method deals away with the constant stress/strain assumption present in most analytical models allowing for a more accurate prediction of the elastic properties, with computational cost only a fraction in comparison with finite element analysis.
However, due to the limited applicability of most analytical models and the limitations of 3D printers, it remains difficult to quantitatively predict and design the properties of nacre-inspired synthetic structures.
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Although the importance of learning is recognized in most analytical diffusion models, few studies have actually empirically examined the role of learning in the diffusion process.
Most existing analytical models assume instantaneous propagation of information flow through multi-hop communications.
The model is, unlike most reported analytical models, non-axisymmetric and it presents a good correlation with measured data.
The review covers the most known analytical models developed in the last 30 years to evaluate the elastic properties of textile composites.
The experimentally obtained lateral stiffness and strength have been compared with the results of some of the most common analytical models based on single diagonal equivalent strut, underlining the formulations that better fit the test outcomes.
Recent experimental results of the FRP concrete bonded joint using flexible adhesive showed that the most popular analytical models available in the literature underestimate the bond strength and the effective bond length of these experiments.
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