arXiv subjects

Saipraneeth Gouravaraju

Publications and source records attributed to Saipraneeth Gouravaraju.

3 recordsLinked to original sources

arXiv2022

A Bayesian regularization-backpropagation neural network model for peeling computations

Bayesian regularization-backpropagation neural network (BR-BPNN) model is employed to predict some aspects of the gecko spatula peeling viz. the variation of the maximum normal and tangential pull-off forces and the resultant force angle at detachment with the peeling angle. K-fold cross validation is used to improve the effectiveness of the model. The input data is taken from finite element (FE) peeling results. The neural network is trained with 75% of the FE dataset. The remaining 25% are utilized to predict the peeling behavior. The training performance is evaluated for every change in the number of hidden layer neurons to determine the optimal network structure. The relative error is calculated to draw a clear comparison between predicted and FE results. It is shown that the BR-BPNN model in conjunction with k-fold technique has significant potential to estimate the peeling behavior.

cs.CE↗

arXiv2020

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

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.

cond-mat.soft↗

arXiv2019

Investigating the normal and tangential peeling behaviour of gecko spatulae using a coupled adhesion-friction model

The present work investigates the normal and tangential peeling behaviour of a gecko spatula using a coupled adhesion-friction model. The objective is to explain the strong attachment and easy detachment behaviour of the spatulae as well as to understand the principles behind their optimum design. Using nonlinear finite element computations, it is shown that during tangentially-constrained peeling the partial sliding of the spatula pad near the peeling front stretches the spatula, thus increasing the strain energy and leading to high pull-off forces. The model is used to investigate the influence of various parameters on the pull-off forces -- such as the peeling angle, spatula shaft angle, strip thickness, and material stiffness. The model shows that increasing the spatula pad thickness beyond a certain level does not lead to a significant increase in the attachment forces. Further, the easy detachment behaviour of geckos is studied under tangentially-free peeling conditions. It is found that the spatulae readily detach from the substrate by changing their shaft angle and eventually peel vertically like a tape. Since the present computational model is not limited by the geometrical, kinematical, and material restrictions of theoretical models, it can be employed to analyse similar biological adhesive systems.

cond-mat.soft↗