E
Eric Li
Researcher at Teesside University
Publications - 112
Citations - 2465
Eric Li is an academic researcher from Teesside University. The author has contributed to research in topics: Finite element method & Smoothed finite element method. The author has an hindex of 23, co-authored 95 publications receiving 1713 citations. Previous affiliations of Eric Li include Shanghai Jiao Tong University & University of Sydney.
Papers
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In-plane crashworthiness of re-entrant hierarchical honeycombs with negative Poisson’s ratio
TL;DR: In this article, two re-entrant hierarchical honeycombs constructed by replacing the cell walls of reentrant honeycomb with regular hexagon substructure (RHH) and equilateral triangle substructures (RHT) were used to investigate the crashworthiness by using the LS-DYNA.
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Hybrid smoothed finite element method for acoustic problems
TL;DR: In this article, the hybrid smoothed finite element method (HS-FEM) using triangular (2D) and tetrahedron (3D) elements that can be generated automatically for any complicated domain is formulated to solve acoustic problems.
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An ES-FEM for accurate analysis of 3D mid-frequency acoustics using tetrahedron mesh
TL;DR: In this article, an edge-based smoothed finite element method (ES-FEM) is proposed to solve 3D acoustic problems in the mid-frequency range, using the simplest linear tetrahedron meshes that can be generated automatically for complicated geometry.
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An edge-based smoothed tetrahedron finite element method (ES-T-FEM) for 3D static and dynamic problems
TL;DR: A novel domain-based selective scheme is proposed leading to a combined ES-T-/NS-FEM model that is immune from volumetric locking and hence works well for nearly incompressible materials.
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A Method of State-of-Charge Estimation for EV Power Lithium-Ion Battery Using a Novel Adaptive Extended Kalman Filter
TL;DR: A new method for online estimating SOC is proposed, which combines a novel adaptive extended Kalman filter (AEKF) and a parameter identification algorithm based on adaptive recursive least squares (RLS).