PREFACE

This book covers the basic topics of computational stochastic mechanics, while focusing on the stochastic analysis of structures in the framework of the finite element method (FEM). It is addressed to students of the postgraduate programme of the School of Civil Engineering at the National Technical University of Athens (NTUA). It is a self-contained book and aims at establishing a solid background on stochastic and reliability analysis of structural systems, such that it will enable future engineers to better manage the concepts of analysis and design in the presence of uncertainty as imposed in almost all modern engineering requirements. Computational stochasticmechanics is a field of mechanics that first appeared in the 70s in order to describe mechanical systems that show unpredictable behavior due to inherent uncertainty. Since then, it has evolved into a self-contained and prolific science field and has brought forth a wide range of sophisticated and well-established methodologies for the quantification of uncertainties inherent in engineering systems. Due to the rapidly growing availability of large-scale and low-cost computer power, the intensive computational demands of these techniques are becoming more and more manageable. This fact, has made the quantification of uncertainty increasingly popular in the engineering community; the progress achieved over the last decade in applying the theory of stochastic processes within the framework of classical engineering has led into higher levels of structural reliability with respect to traditional empirical safety factor approaches, both in terms of safety and economy. As a result, design engineers can now take rational and quantified risk mitigation measures to face the random nature of various parameters (material and geometric properties, loading conditions, etc). Parameter uncertainty quantification and methods to predict uncertainty propagation on the response of structural systems have become an essential part of the analysis and design of engineering applications. Stochastic analysis and in particular the Stochastic Finite Element Method (SFEM), is a valuable and versatile tool for the