Quadratic Weighted Histopolation on Tetrahedral Meshes with Probabilistic Degrees of Freedom

TL;DR

This paper introduces three new weighted quadratic enrichment strategies for local histopolation on tetrahedral meshes, significantly improving accuracy through probabilistic and integral-based methods.

Contribution

It presents three novel three-dimensional weighted quadratic enrichment strategies utilizing probabilistic moments and integral functionals for enhanced histopolation accuracy.

Findings

Strategies outperform classical linear histopolation

Adaptive algorithm optimally selects parameters

Numerical experiments confirm accuracy improvements

Abstract

In this paper we introduce three complementary three-dimensional weighted quadratic enrichment strategies to improve the accuracy of local histopolation on tetrahedral meshes. The first combines face and interior weighted moments (face-volume strategy), the second uses only volumetric quadratic moments (purely volumetric strategy), and the third enriches the quadratic space through edge-supported probabilistic moments (edge-face strategy). All constructions are based on integral functionals defined by suitable probability densities and orthogonal polynomials within quadratic trial spaces. We provide a comprehensive analysis that establishes unisolvence and derives necessary and sufficient conditions on the densities to guarantee well-posedness. Representative density families, including two-parameter symmetric Dirichlet laws and convexly blended volumetric families, are examined in detail, and a general procedure for constructing the associated quadratic basis functions is outlined. For all admissible densities, an adaptive algorithm automatically selects optimal parameters. Extensive numerical experiments confirm that the proposed strategies yield substantial accuracy improvements over the classical linear histopolation scheme.