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A new generalized displacement control for nonlinear spectral stochastic finite element problems

Panther, Lukas 1; Wagner, Werner 1; Freitag, Steffen 1
1 Institut für Baustatik (IBS), Karlsruher Institut für Technologie (KIT)

Abstract:

The influence of uncertain material parameters on the mechanical behavior of structures is investigated using stochastic structural analysis. A widely used method for estimating the stochastic characteristics of the structural response is the Monte Carlo simulation (MCS). However, this approach exhibits a slow convergence rate. In this paper, we investigate geometrically nonlinear finite element problems using the spectral stochastic finite element method (SSFEM). This application of the SSFEM remains comparatively unexplored to date, see [1, 2, 14]. The SSFEM combines the polynomial chaos expansion (PCE) with the finite element method (FEM). The basis of the SSFEM is an extended variational formulation, which is discretized in the stochastic domain using the PCE and in the spatial domain using the FEM. This paper focuses on the development and implementation of solution algorithms for tracing nonlinear equilibrium paths within the framework of the SSFEM. In addition to existing standard solution methods, a generalized displacement control is developed for the application within the SSFEM. This algorithm allows the investigation of mechanical problems that cannot be solved using standard solution methods. ... mehr


Verlagsausgabe §
DOI: 10.5445/IR/1000193642
Veröffentlicht am 28.05.2026
Originalveröffentlichung
DOI: 10.1007/s00466-026-02772-z
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Baustatik (IBS)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2026
Sprache Englisch
Identifikator ISSN: 0178-7675, 1432-0924
KITopen-ID: 1000193642
Erschienen in Computational Mechanics
Verlag Springer
Vorab online veröffentlicht am 21.05.2026
Schlagwörter Solution algorithms, Generalized displacement control, Nonlinear spectral stochastic FEM, Polynomial chaos expansion, Uncertainty quantification
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