English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

We propose a least-squares method involving the recovery of the gradient andpossibly the Hessian for elliptic equation in nondivergence form. As ourapproach is based on the Lax--Milgram theorem with the curl-free constraintbuilt into the target (or cost) functional, the discrete spaces require noinf-sup stabilization. We show that standard conforming finite elements can beused yielding apriori and aposteriori convergnece results. We illustrate ourfindings with numerical experiments with uniform or adaptive mesh refinement.

A least-squares Galerkin approach to gradient and Hessian recovery for nondivergence-form elliptic equations