Updating structural dynamic models with emphasis on the damping properties

Chouaki, A.; Proslier, L.

doi:10.2514/3.13938

Cited by 18 publications

(36 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…A complete parallel with Tarantola's theory [34] was identified recently in [38]. This option requires a choice of norm of the "statistical" type for the unreliable experimental information, a direction which, until now, has been followed only in [37]. A recent work [38] showed that this "statistical" choice is not absolutely required if the experimental data are uncertain.…”

Section: Validation Using the Modified-cre: General Philosophymentioning

confidence: 98%

“…Then, the method was extended to forced vibration problems in [20]. This approach is based on what is known as the Drucker error, and it has proved its effectiveness in updating the mass, stiffness and damping properties [21,22]. The method can also deal with nonlinearities due to the material's behavior or to contacts.…”

Section: Introductionmentioning

confidence: 99%

“…Regarding validation, one should mention what is known as "inverse methods", many of which definitely fall into the stochastic category [34,35]; in fact, in these methods, the approach is purely stochastic and mechanics is mostly absent; a first attempt to draw a parallel between the CRE and the general inverse problem theory can be found in [36], where it is proposed to use the local value of the CRE to evaluate the relative variances on the parameters of the model. In [37], a statistical interpretation of the norm to be applied to the measurements in direct relation to the covariance matrix was advocated as being the only possible choice if the data are scarce for a first true attempt to extend the constitutive relation error to the stochastic case. In [38], this statement was shown to be excessive and equally effective choices were presented.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Validation of structural dynamics models containing uncertainties

Ladevèze

Puel

Deraemaeker

et al. 2006

Computer Methods in Applied Mechanics and Engineering

View full text Add to dashboard Cite

This paper deals with model validation in structural dynamics for a family of quasiidentical structures in the context of uncertain measurements. The crucial point is for the engineer to be able to quantify the quality of the model, which is probabilistic with respect to a set of measurements from which a probability density function can be extracted. Our approach is based on the "mechanical concept" of Constitutive Relation Error Estimator (CRE), which was introduced initially in order to quantify the quality of finite element analyses, then developed in the deterministic context. Our extended CRE estimator enables us to quantify the quality of a given probabilistic model and, thus, to update and validate the model. Several examples are given, including an industrial case.

show abstract

Section: Validation Using the Modified-cre: General Philosophymentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Validation of structural dynamics models containing uncertainties

Ladevèze

Puel

Deraemaeker

et al. 2006

Computer Methods in Applied Mechanics and Engineering

View full text Add to dashboard Cite

show abstract

“…Its concept consists in using an a posteriori estimator and its efficiency has previously been shown [14][15][16][17]. The method is based on the Drucker error.…”

Section: The Constitutive Relation Error Methodsmentioning

confidence: 99%

“…Three categories of cost functions can be used : the input residuals [10,11], the output residuals [12,13] and the residual named the "Constitutive Relation Error (CRE)" which is used in this paper. It provides a measure of quality of the updated model which is essential for model validation [14][15][16][17].…”

Section: Introductionmentioning

confidence: 99%

Robust damage assessment of multiple cracks based on the frequency response function and the Constitutive Relation Error updating method

Faverjon

Sinou

2008

Journal of Sound and Vibration

View full text Add to dashboard Cite

To cite this version:Béatrice Faverjon, Jean-Jacques Sinou. Robust damage assessment of multiple cracks based on the frequency response function and the Constitutive Relation Error updating method. Journal of Sound and Vibration, Elsevier, 2008, 312, pp.821-837 AbstractThe aim of this paper is to present a damage assessment technique for the non destructive detection and sizing of multiple open cracks in beams. The Constitutive Relation Error updating method is used for the identification of the location and the size of multi-cracks in a simply supported beam. The present identification method is illustrated through numerical examples including double and triples cracks. Moreover, the efficiency and robustness of the proposed method is demonstrated through various numerical simulations in regard to the non-dimensional crack depth and the crack location. It is demonstrated that the Constitutive Relation Error updating method can detect the number of cracks on the beam and can estimate both the crack positions and sizes with satisfactory precision, even if 10% or 20% noise levels has been added to the simulations, and only few degrees of freedom are used for the identification procedure.

show abstract

NN‐mCRE: A modified constitutive relation error framework for unsupervised learning of nonlinear state laws with physics‐augmented neural networks

Benady,

Baranger,

Chamoin

2024

Numerical Meth Engineering

View full text Add to dashboard Cite

This article proposes a new approach to train physics‐augmented neural networks with observable data to represent mechanical constitutive laws. To train the neural network and learn thermodynamics potentials, the proposed method does not rely on strain‐stress or strain‐free energy pairs but needs only partial strain or displacement measurements inside the structure. The neural network is trained thanks to an unsupervised procedure in which the modified constitutive relation error (mCRE) is minimized. The mCRE functional provides a bias‐aware data assimilation framework with a rich physical sense as the constitutive relation error (CRE) part can be interpreted as a modeling error continuously defined over the structure, and can be used as a prediction quality in the inference phase. This article also extends previous works on the mCRE by introducing a new minimization procedure in the case of nonlinear state laws. As typical structural health monitoring applications may require that the neural networks should be trained online, an important focus is thus made on automatic and adaptive tuning of sensitive hyperparameters (learning rate, weighting between losses, number of epochs and initialization). It is shown that when the training database is rich enough with respect to the loading cases, the proposed method achieves remarkable performance regarding the quality of the learned model, noise robustness, and low sensitivity to user‐defined hyperparameters. The method is evaluated on two test cases: a non‐quadratic potential in the small strain regime with synthetic optic fiber measurements, and a Mooney–Rivlin model in the hyperelastic case with synthetic digital image correlation observations.

show abstract

Updating structural dynamic models with emphasis on the damping properties

Cited by 18 publications

References 0 publications

Validation of structural dynamics models containing uncertainties

Validation of structural dynamics models containing uncertainties

Robust damage assessment of multiple cracks based on the frequency response function and the Constitutive Relation Error updating method

NN‐mCRE: A modified constitutive relation error framework for unsupervised learning of nonlinear state laws with physics‐augmented neural networks

Contact Info

Product

Resources

About