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A Functionally Connected Element Method for Solving Boundary Value Problems

Jielin Yang, Suchuan Dong

Abstract

We present the general forms of piece-wise functions on partitioned domains satisfying an intrinsic $C^0$ or $C^1$ continuity across the sub-domain boundaries. These general forms are constructed based on a strategy stemming from the theory of functional connections, and we refer to partitioned domains endowed with these general forms as functionally connected elements (FCE). We further present a method, incorporating functionally connected elements and a least squares collocation approach, for solving boundary and initial value problems. This method exhibits a spectral-like accuracy, with the free functions involved in the FCE form represented by polynomial bases or by non-polynomial bases of quasi-random sinusoidal functions. The FCE method offers a unique advantage over traditional element-based methods for boundary value problems involving relative boundary conditions. A number of linear and nonlinear numerical examples in one and two dimensions are presented to demonstrate the performance of the FCE method developed herein.

A Functionally Connected Element Method for Solving Boundary Value Problems

Abstract

We present the general forms of piece-wise functions on partitioned domains satisfying an intrinsic or continuity across the sub-domain boundaries. These general forms are constructed based on a strategy stemming from the theory of functional connections, and we refer to partitioned domains endowed with these general forms as functionally connected elements (FCE). We further present a method, incorporating functionally connected elements and a least squares collocation approach, for solving boundary and initial value problems. This method exhibits a spectral-like accuracy, with the free functions involved in the FCE form represented by polynomial bases or by non-polynomial bases of quasi-random sinusoidal functions. The FCE method offers a unique advantage over traditional element-based methods for boundary value problems involving relative boundary conditions. A number of linear and nonlinear numerical examples in one and two dimensions are presented to demonstrate the performance of the FCE method developed herein.
Paper Structure (37 sections, 162 equations, 10 figures, 8 tables)

This paper contains 37 sections, 162 equations, 10 figures, 8 tables.

Figures (10)

  • Figure 1: 1D Helmholtz equation: $l^{2}$ errors of $C^1$ FCEs as a function of (a) the element size, and (b) the polynomial order. In (a), the polynomial order ($p$) is fixed while the element size is varied (h-refinement), showing a convergence rate of ($p+1$). In (b), the number of elements ($N$) is fixed while the polynomial order $p$ is varied (p-refinement), showing an exponential convergence rate. $(p+2)$ collocation points per element (Gauss-Lobatto-Legendre points).
  • Figure 2: IVP: $l^{\infty}$ errors of FCE-$C^0$ as a function of (a) the element size, and (b) the polynomial order. $q=p+2$ Gauss-Lobatto-Legendre collocation points per element.
  • Figure 3: 1D nonlinear Helmholtz equation: $l^{\infty}$ errors of FCE-$C^1$ as a function of (a) the element size, and (b) the polynomial order. $N$ uniform elements, and $q=p+2$ uniform collocation points per element.
  • Figure 4: 2D Helmholtz equation: $l^{\infty}$ errors of FCE-$C^0$ versus (a) the element size in each direction, and (b) the polynomial order. $N$ uniform elements per direction.
  • Figure 5: Advection equation: $l^{\infty}$ errors of FCE-$C^0$ versus (a) the element size in each direction, and (b) the polynomial order. $q=p+2$ Gauss-Lobatto-Legendre collocation points; $N$ denotes the number of elements per direction.
  • ...and 5 more figures

Theorems & Definitions (13)

  • proof
  • Remark 1
  • Remark 2
  • proof
  • Remark 3
  • proof
  • proof
  • proof
  • Remark 4
  • Remark 5
  • ...and 3 more