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 Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

We present the Local Empirical Cubature Method (Local-ECM), a novel algorithmtailored for creating efficient integration rules, particularly addressingclusters of intrinsically distinct functions, as observed in localreduced-order models. Local-ECM seeks to enhance existing empirical cubaturemethodologies by harnessing the locality of the functions to yield the sparsestoutcome, while incurring virtually no implementation overheads. Our approachstraightforwardly poses a local cubature optimization problem for the firsttime, out of which we also propose alternative Linear Programming (LP)strategies for its resolution. Through examination across three academicexamples, we demonstrate the capability of our method to identify the sparsestcubature rules for a given tolerance, outperforming alternate methods outlined,including the LP and other global strategies. We have made our code freelyavailable through the GitHub repository athttps://github.com/Rbravo555/localECM

Local-ECM: An empirical cubature hyper-reduction method adapted to local reduced order models