Model reduction technique for mechanical behaviour modelling: efficiency criteria and validity domain assessment
| dc.rights.license | open | en_US |
| hal.structure.identifier | ESTIA INSTITUTE OF TECHNOLOGY | |
| dc.contributor.author | ORDAZ HERNANDEZ, Keny | |
| hal.structure.identifier | ESTIA INSTITUTE OF TECHNOLOGY | |
| dc.contributor.author | FISCHER, Xavier | |
| dc.contributor.author | BENNIS, Fouad | |
| dc.date.accessioned | 2023-09-11T09:31:48Z | |
| dc.date.available | 2023-09-11T09:31:48Z | |
| dc.date.issued | 2008 | |
| dc.identifier.issn | 0954-4062 | en_US |
| dc.identifier.uri | https://oskar-bordeaux.fr/handle/20.500.12278/183644 | |
| dc.description.abstractEn | This paper presents the study of a neural network-based technique used to create fast, reduced, non-linear behavioural models. The studied approach is the use of artificial neural networks (ANNs) as a model reduction technique to create more efficient models, mostly in terms of computational speed. The test case is the deformation of a cantilever beam under large deflections (geometrical non-linearity). A reduced model is created by means of a multi-layer feed-forward neural network (MLFN), a type of ANN reported as "universal approximator" in the literature. Then it is compared with two finite element models: linear (inaccurate for large deflections but fast) and non-linear (accurate but slow). Under large displacements, the reduced model approximates well the non-linear model while having similar speed to the linear model. Unfortunately, the resulting model presents a shortening of its validity domain, as being incapable of approximating the deformed configuration of the cantilever beam under small displacements. In other words, the ANN-based model provides a very good compromise between accuracy and speed within its validity domain, despite the low fidelity presented: accurate for large displacements but inaccurate for small displacements. | |
| dc.language.iso | EN | en_US |
| dc.subject.en | artificial neural network | |
| dc.subject.en | validity domain | |
| dc.subject.en | cantilever beam | |
| dc.subject.en | non-linear behaviour | |
| dc.subject.en | model reduction | |
| dc.title.en | Model reduction technique for mechanical behaviour modelling: efficiency criteria and validity domain assessment | |
| dc.type | Article de revue | en_US |
| dc.subject.hal | Sciences de l'ingénieur [physics]/Mécanique [physics.med-ph]/Mécanique des structures [physics.class-ph] | en_US |
| dc.subject.hal | Informatique [cs]/Intelligence artificielle [cs.AI] | en_US |
| bordeaux.journal | Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science | en_US |
| bordeaux.page | JMES683R1 | en_US |
| bordeaux.hal.laboratories | ESTIA - Recherche | en_US |
| bordeaux.institution | Université de Bordeaux | en_US |
| bordeaux.institution | Bordeaux INP | en_US |
| bordeaux.institution | Bordeaux Sciences Agro | en_US |
| bordeaux.peerReviewed | oui | en_US |
| bordeaux.inpress | non | en_US |
| bordeaux.import.source | hal | |
| hal.identifier | hal-00187317 | |
| hal.version | 1 | |
| hal.popular | non | en_US |
| hal.audience | Internationale | en_US |
| hal.export | false | |
| workflow.import.source | hal | |
| dc.rights.cc | Pas de Licence CC | en_US |
| bordeaux.COinS | ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Proceedings%20of%20the%20Institution%20of%20Mechanical%20Engineers,%20Part%20C:%20Journal%20of%20Mechanical%20Engineering%20Science&rft.date=2008&rft.spage=JMES683R1&rft.epage=JMES683R1&rft.eissn=0954-4062&rft.issn=0954-4062&rft.au=ORDAZ%20HERNANDEZ,%20Keny&FISCHER,%20Xavier&BENNIS,%20Fouad&rft.genre=article |
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