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

Graphics Processing Unit (GPU) computing is becoming an alternate computingplatform for numerical simulations. However, it is not clear which numericalscheme will provide the highest computational efficiency for different types ofproblems. To this end, numerical accuracies and computational work of severalnumerical methods are compared using a GPU computing implementation. TheCorrection Procedure via Reconstruction (CPR), Discontinuous Galerkin (DG),Nodal Discontinuous Galerkin (NDG), Spectral Difference (SD), and Finite Volume(FV) methods are investigated using various reconstruction orders. Both smoothand discontinuous cases are considered for two-dimensional simulations. Fordiscontinuous problems, MUSCL schemes are employed with FV, while CPR, DG, NDG,and SD use slope limiting. The computation time to reach a set error criteriaand total time to complete solutions are compared across the methods. It isshown that while FV methods can produce solutions with low computational times,they produce larger errors than high-order methods for smooth problems at thesame order of accuracy. For discontinuous problems, the methods show goodagreement with one another in terms of solution profiles, and the totalcomputational times between FV, CPR, and SD are comparable.

A Comparative Study of 2D Numerical Methods with GPU Computing