A comparison of stochastic process models for definition of design contours

So-called design contour methods are frequently applied for large and complex structures in order to minimize the number of time-consuming structural analyses. These methods are based on first identifying extreme environmental conditions with a given probability of exceedance based on the relevant joint distribution function. These conditions are located along a level surface (i.e. “contour”) in the space of load parameters. As the second step, response analyses are performed for a selection of extreme conditions which are located along this contour. The highest response level which is obtained as a result of these analyses is then applied for design purposes.This approach is based on a representation of the underlying stochastic processes in terms of a sequence of piecewise constant levels. In the present paper, the extreme environmental conditions which are obtained based on such a model are compared to those obtained by instead applying a continuous process model. Furthermore, various alternative and relevant definitions of design contours are compared for the two-component case.In the present analysis, mainly stochastic processes which represent load parameters are considered. However, the approach for identification of level surfaces is of a general nature and can be applied to any types of random vector processes.