Abstract
Nonlinear dynamic analysis of complex engineering structures modelled using commercial finite element (FE) software is computationally expensive. Indirect reduced-order modelling strategies alleviate this cost byconstructinglow-dimensionalmodelsusingastatic solution dataset from the FE model. The applicability of such methods is typically limited to structures in which (a) the main source of nonlinearity is the quasi-static coupling between transverse and inplane modes (i.e. membrane stretching); and (b) the amount of in-plane displacement is limited. We show that the second requirement arises from the fact that, in existing methods, in-plane kinetic energy is assumed to be negligible. For structures such as thin plates and slender beams with fixed/pinned boundary conditions, this is often reasonable, but in structures with free boundary conditions (e.g. cantilever beams), this assumption is violated. Here, weexploittheconceptofnonlinearmanifoldstoshow how the in-plane kinetic energy can be accounted for in the reduced dynamics, without requiring any additional information from the FE model. This new insight enables indirect reduction methods to be applied to a far wider range of structures whilst maintainingaccuracytohigherdeflectionamplitudes. The accuracy of the proposed method is validated using an FE model of a cantilever beam.
Original language | English |
---|---|
Article number | 20200589 |
Number of pages | 20 |
Journal | Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences |
Volume | 476 |
Issue number | 2243 |
Early online date | 18 Nov 2020 |
DOIs | |
Publication status | Published - 25 Nov 2020 |
Keywords
- reduced-order modelling
- geometric nonlinearity
- nonlinear normal modes
- nonlinear manifold
- finite-element analysis
- structural dynamics
Fingerprint
Dive into the research topics of 'Indirect reduced-order modelling: Using nonlinear manifolds to conserve kinetic energy'. Together they form a unique fingerprint.Student theses
-
Reduced-order modelling of nonlinear dynamic structures
Nicolaidou, E. (Author), Hill, T. (Supervisor) & Neild, S. (Supervisor), 6 Dec 2022Student thesis: Doctoral Thesis › Doctor of Philosophy (PhD)
File