We describe the space–time finite element techniques we developed for computation of fluid–structure interaction (FSI) problems. Among these techniques are the deforming-spatial-domain/stabilized space–time (DSD/SST) formulation and its special version, and the mesh update methods, including the solid-extension mesh moving technique (SEMMT). Also among these techniques are the block-iterative, quasi-direct and direct coupling methods for the solution of the fully discretized, coupled fluid and structural mechanics equations. We present some test computations for the mesh moving techniques described. We also present numerical examples where the fluid is governed by the Navier– Stokes equations of incompressible flows and the structure is governed by the membrane and cable equations. Overall, we demonstrate that the techniques we have developed have increased the scope and accuracy of the methods used in computation of FSI problems. � 2005 Elsevier B.V. All rights reserved.

Space-time finite element techniques for computation of fluid-structure interactions

Probabilistic LCF life assessment for turbine discs with DC strategy-based wavelet neural network regression

A novel metamodeling approach for probabilistic LCF estimation of turbine disk

This is the peer reviewed version of the following article: [ Tello, A, Codina, R, Baiges, J. Fluid structure interaction by means of variational multiscale reduced order models. Int J Numer Methods Eng. 2020; 121: 2601– 2625. https://doi.org/10.1002/nme.6321 ], which has been published in final form at [https://onlinelibrary.wiley.com/doi/abs/10.1002/nme.6321]. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving

/pdf/fluid-structure-interaction-by-means-of-variational-1u6snps7sw.pdf

Fluid structure interaction by means of variational multiscale reduced order models

A state-of-the-art review of crack branching

A novel surrogate model based on the Local Maximum-Entropy (LME) approximation is proposed in this paper. By varying the degrees of locality, the LME-based surrogate model is constructed according to the local behavior of the response function at the prediction points. The proposed method combines the advantages of both local and global approximation schemes. The robustness and effectiveness of the model are systematically investigated by comparing with the conventional surrogate models (such as Polynomial regression, Radial basis function, and Kriging model) in three types of test problems. In addition, the performance of the LME-based surrogate model is evaluated by an industry case of turbine disk reliability analysis (TDRA) involving random geometric parameters. In TDRA, two LME-based surrogate models are built including a 1
 s
 t
 surrogate model employed in the sensitivity analysis to determine the key random variables and a 2
 n
 d
 surrogate model utilized in Monte-Carlo Simulations (MCS) to predict the Low Cycle Fatigue (LCF) life of turbine disks. Finally, a model-based Uncertainty Quantification (UQ) analysis is performed to rigorously quantify the uncertainties of the physical system and fidelity of surrogate model predictions simultaneously. Results show that the LME-based surrogate model can achieve a desirable level of accuracy and robustness with reduced number of sample points, which indicates the proposed method possess the potential for approximating highly nonlinear limit state functions and applicable for structural reliability analysis.

Huming Liao

Papers

Local maximum-entropy based surrogate model and its application to structural reliability analysis

A monolithic Lagrangian meshfree scheme for Fluid–Structure Interaction problems within the OTM framework

A Lagrangian meshfree mesoscale simulation of powder bed fusion additive manufacturing of metals

The Hot Optimal Transportation Meshfree (HOTM) method for materials under extreme dynamic thermomechanical conditions

A dynamic adaptive eigenfracture method for failure in brittle materials