Uncertainty & Reliability Analysis of Structural Dynamical Systems

this paper various methods to analyze structural systems under stochastic dynamic loading are qualitatively compared. While the Karhunen-Lo eve expansion proved to be advantageous when uncertainty estimation is required, (advanced) Monte Carlo simulation procedures are recommended for reliability estimates. The computational efficiency of the methods play an important role w.r.t. practical applications. A further quantitative benchmark study is recommen

Developments in Stochastic Structural mechanics

Uncertainties are a central element in structural analysis and design. But even today they are frequently dealt with in an intuitive or qualitative way only. However, as already suggested 80 years ago, these uncertainties may be quantified by statistical and stochastic procedures. In this contribution it is attempted to shed light on some of the recent advances in the now established field of stochastic structural mechanics and also solicit ideas on possible future developments

Computational Stochastic Structural Analysis (COSSAN)- A Software Tool

The paper provides an overview of the current status of the COSSAN [1, 2] software developed at the Institute of Engineering Mechanics of the Leopold Franzens University, Innsbruck, Austria, EU. Two options provided by COSSAN are described: (1) A 'Stand Alone Tool Box' which is an event driven modular general purpose code and (2) the 'Third Party Communication Tools' which allow to employ deterministic Third Party (FE-) codes for stochastic analysis without the need to access and modify the third party source code. The Stand Alone Tool Box covers a fairly wide field of stochastic methods including various sampling techniques, random fields, fatigue analysis, reliability based optimization, random vibration, Monte Carlo simulation and FE-analysis. The Third Party Communication Tools are designed to extend existing deterministic FE-codes for considering uncertainties and consequently perform stochastic analyses using methods based on Monte Carlo procedures

Abstract Mechanics & Analysis ⋆

In this paper the need for a rational treatment of uncertainties in structural mechanics and analysis is reasoned. It is shown that the traditional deterministic conception can be eas-ily extended by applying statistical and probabilistic concepts. The so-called Monte Carlo simulation procedure is the key for those developments, as it allows the straightforward use of the currently used deterministic analysis procedures. A numerical example exemplifies the methodology. It is concluded that uncertainty anal-ysis may ensure robust predictions of variability, model verification, safety assessment, etc

STOCHASTIC ANALYSIS OF FATIGUE CRACK GROWTH

Due to cost and time limitations, experiments for fatigue crack growth are only feasible below certain cycle numbers. In this paper, it is investigated whether or not fatigue crack growth laws allow for an extrapolation of the statistics of the cycle number to reach a certain crack length from limited experimental data, and hence reduce costs

ABSTRACT The Effects of Uncertainties in Structural Analysis

Uncertainties are generally unavoidable in structural analysis and design. While in traditional procedures these uncertainties are treated in a qualitative way, which is mainly based on experience, modern approaches contain, more rational i.e. quantitative attempts, e.g. using statistical and probabilistic methods for their assessment. Hence with this approach the analysis of the propagation of uncertainties through a structural system the assessment of its reliability, etc. becomes feasible