Picture of mobile phone running fintech app

Fintech: Open Access research exploring new frontiers in financial technology

Strathprints makes available Open Access scholarly outputs by the Department of Accounting & Finance at Strathclyde. Particular research specialisms include financial risk management and investment strategies.

The Department also hosts the Centre for Financial Regulation and Innovation (CeFRI), demonstrating research expertise in fintech and capital markets. It also aims to provide a strategic link between academia, policy-makers, regulators and other financial industry participants.

Explore all Strathclyde Open Access research...

Non-uniform order mixed FEM approximation : implementation, post-processing, computable error bound and adaptivity

Ainsworth, Mark and Ma, Xinhui (2012) Non-uniform order mixed FEM approximation : implementation, post-processing, computable error bound and adaptivity. Journal of Computational Physics, 231 (2). pp. 436-453. ISSN 0021-9991

Full text not available in this repository. Request a copy from the Strathclyde author

Abstract

The present work provides a straightforward and focused set of tools and corresponding theoretical support for the implementation of an adaptive high order finite element code with guaranteed error control for the approximation of elliptic problems in mixed form. The work contains: details of the discretisation using non-uniform order mixed finite elements of arbitrarily high order; a new local post-processing scheme for the primary variable; the use of the post-processing scheme in the derivation of new, fully computable bounds for the error in the flux variable; and, an hp-adaptive refinement strategy based on the a posteriori error estimator. Numerical examples are presented illustrating the results obtained when the procedure is applied to a challenging problem involving a ten-pole electric motor with singularities arising from both geometric features and discontinuities in material properties. The procedure is shown to be capable of producing high accuracy numerical approximations with relatively modest numbers of unknowns.