The accurate and efficient treatment of uncertainties in large-scale stochastic systems poses a major challenge in the field of computational stochastic mechanics. Current research efforts concentrate on the development of new and the improvement of existing methods in order to meet the needs of engineering practice. This session aims at presenting recent advances in this area. In this respect, topics of interest include but are not limited to:

• Random field simulation
• Methods for improving the efficiency of Monte Carlo simulation in large-scale applications
• Efficient algorithms to accelerate the solution of the resulting algebraic systems of equations
• Efficient finite element solution of stochastic partial differential equations
• Convergence and error estimation

Please note that papers that are found to fall outside the scope of this session may be considered for other sessions.