The aim of this paper is to demonstrate that stochastic analyses can be performed on large and complex models within affordable costs. Stochastic analyses offer a much more realistic approach for analysis and design of components and systems although generally computationally demanding. Hence, resorting to efficient approaches and high performance computing is required in order to reduce the execution time.A general purpose software that provides an integration between deterministic solvers (i.e. finite element solvers), efficient algorithms for uncertainty management and high performance computing is presented. The software is intended for a wide range of applications, which includes optimization analysis, life-cycle management, reliability and risk analysis, fatigue and fractures simulation, robust design.The applicability of the proposed tools for practical applications is demonstrated by means of a number of case studies of industrial interest involving detailed models.

This paper addresses the most recent developments concerning the application of the P-C expansion method within the Stochastic Finite Element (SFE) analysis, in particular considering computational solid mechanics. More specifically, the focus has been on the use of the method for the propagation of the stochastic structural responses due to the extensive amount of contributions in this context. Numerical examples presented in the literature are listed in this regard, in order to shed some light on the range of applications, especially in terms of the probabilistic dimensionality of the problem. Furthermore, the recently emerging utilization of the method within the modeling of uncertain input parameters is covered briefly. With this contribution, it is aimed to present an overview on the state-ofart of the P-C literature and the capabilities of the method.

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