arXiv subjects

Marcone Corrêa Pereira

Publications and source records attributed to Marcone Corrêa Pereira.

3 recordsLinked to original sources

arXiv2020

The p-Laplacian operator in oscillating thin domains

In this paper we study the asymptotic behavior of the solutions of a class of nonlinear elliptic problems posed in a 2-dimensional domain that degenerates into a line segment (a thin domain) when a positive parameter $\varepsilon$ goes to zero. We also allow high oscillating behavior on the upper boundary of the thin domain as $\varepsilon \to 0$. Combining methods from classic homogenization theory for reticulated structures and monotone operators we obtain the homogenized equation proving convergence of the solutions and establishing a corrector function which guarantees strong convergence in $W^{1,p}$ for $1<p<+\infty$.

math.AP↗

arXiv2019

The p-Laplacian equation in thin domains: The unfolding approach

In this work we apply the unfolding operator method to analyze the asymptotic behavior of the solutions of the $p$-Laplacian equation with Neumann boundary condition set in a bounded thin domain of the type $R^\varepsilon=\left\lbrace(x,y)\in\mathbb{R}^2:x\in(0,1)\mbox{ and }0 1$ representing respectively weak, resonant and high osillations at the top boundary. In the three cases we deduce the homogenized limit and obtain correctors.

math.AP↗

arXiv2011

Error estimates for a Neumann problem in highly oscillating thin domains

In this work we analyze convergence of solutions for the Laplace operator with Neumann boundary conditions in a two-dimensional highly oscillating domain which degenerates into a segment (thin domains) of the real line. We consider the case where the height of the thin domain, amplitude and period of the oscillations are all of the same order, given by a small parameter $ε$. We investigate strong convergence properties of the solutions using an appropriate corrector approach. We also give error estimates when we replace the original solutions for the second-order expansion through the Multiple-Scale Method.

math.AP↗