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.

中文翻译：

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用于大型有限元模型的高效不确定性管理的通用软件

本文的目的是证明可以在可承受的成本内对大型复杂模型进行随机分析。随机分析为组件和系统的分析和设计提供了一种更现实的方法，尽管通常对计算要求很高。因此，需要采用高效的方法和高性能计算来减少执行时间。提出了一种通用软件，它提供了确定性求解器（即有限元求解器）、不确定性管理和高性能计算的有效算法之间的集成。该软件适用于广泛的应用，包括优化分析、生命周期管理、可靠性和风险分析、疲劳和断裂模拟、稳健设计。