Stability analysis of a clutch system with uncertain parameters using sparse polynomial chaos expansions

To remedy this problem, one considers sparse Polynomial Chaos (sparse PC) expansion. This method is filled out by an iterative procedure allowing to build iteratively a sparse

To further analyze the accuracies of the di ff erent method, the relative errors of the mean value of the QoI and its variance with respect to the reference solution (i.e. N

Gaillard, Two parameters wronskian representation of solutions of nonlinear Schr¨odinger equation, eight Peregrine breather and multi-rogue waves, J.. Gaillard, Hierarchy of

We obtained new patterns in the (x; t) plane, by different choices of these parameters; we recognized rings configurations as already observed in the case of deformations depending

Sparse polynomial chaos expansions (PCE) are a popular surrogate modelling method that takes advantage of the properties of PCE, the sparsity-of-effects principle, and powerful

One of the sources for this error is the interpolation. One can reduce it by reducing the frequency step. In addition, close to the resonance frequency, the amplitude is driven

For the meta-models developed with EDs of size N = 500, Figure 26 depicts the evolution of err c C G with increasing response threshold; the left graph of the figure shows this

Figure 1 shows the relative error in the second moment over the spatial domain of a stochastic Galerkin approximation to the solution of (4.7) using standard Hermite