On the presence of a critical detachment angle in gecko spatula peeling - a numerical investigation using an adhesive friction model

Abstract

A continuum-based computational contact model is employed to study coupled adhesion and friction in gecko spatulae. Nonlinear finite element analysis is carried out to simulate spatula peeling from a rigid substrate. It is shown that the "frictional adhesion" behavior, until now only observed from seta to toe levels, is also present at the spatula level. It is shown that for sufficiently small spatula pad thickness, the spatula detaches at a constant angle known as the critical detachment angle irrespective of the peeling and shaft angles. The spatula reaches the same energy states at the jump-off contact point, which directly relates to the invariance of the critical detachment angle. This study also reveals that there is an optimum pad thickness associated with the invariance of the critical detachment angle. It is further observed that the sliding of the spatula pad is essential for the invariance of the critical detachment angle.

A Bayesian regularization-backpropagation neural network model for peeling computations

“…This section presents the BR based backpropagation neural network predictions of the maximum normal pull-off force F max n , the maximum tangential pull-off force F max t , and the resultant force angle at detachment α det along with the corresponding displacements ūmax and ūdet . Predictions of the networks are then compared with the FE results of Gouravaraju et al [30,70] that have not been yet used for training. To define the optimal structure of each network model, the mean square error (MSE) of Eq.…”

“…Bayesian regularization is used to improve the robustness of the backpropagation neural network and to eliminate cross-validation. The input data is obtained from the finite element analysis of Gouravaraju et al [30,70]. Three networks corresponding to the maximum normal pull-off force, maximum tangential pull-off force, and the resultant force angle at detachment and their corresponding displacements are formed.…”

“…In this section, the adhesive friction model of Mergel et al [72] and its application to gecko spatula peeling by Gouravaraju et al [30,70] are briefly described.…”

“…In this paper, Bayesian regularization based backpropagation neural networks are employed to predict the influence of the peeling angle on the peeling force of a gecko spatula. The input data is obtained from the finite element simulations of Gouravaraju et al [30,70], who have used a quasicontinuum finite element model that captures friction due to adhesion at the nanoscale [71,72].…”

Gecko-Like Dry Adhesive Surfaces and Their Applications: A Review

“…To capture the frictional behavior during the normal adhesive process, the research team also proposed two continuous contact models that coupled the adhesion and the friction based on whether the sliding friction is dependent on the normal distance of the adhesive interfaces [58]. Based on the two models, the peeling behaviors of the strip that simulates the peeling of the spatula were explored again, and some conclusions that are similar to the gecko adhesion could be obtained: the sliding of the spatula near the peeling front can pre-stretch the spatula, thereby increasing the peeling force; the peeling of the spatula exists the critical detachment angle; the spatula can be easily detached from the substrate by changing the shaft angle and adopting a vertical peeling method [59,60]. Although the two models have been extended to three dimensions by researchers [61], the assumption that the static friction threshold based on the macroscopic measurement is consistent with the resistance for kinetic friction still needs to be verified on the local contact area.…”