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Non-probabilistic design of structures is a matter of assigning values to the uncertain parameters involved in the design problem from an often closed, bounded and convex set. The mathematical problem is then to ensure that the prescribed safety constraints are satisfied for all the points of this set. Probabilistic design of structures on the other hand works with assigning probability distributions to the uncertain parameters involved and by requiring that the safety constraints are satisfied with high probabilities. Through an ellipsoidal representation of uncertainty, the link between these methodologies is illustrated and discussed in this article. Specific focus is placed on scenarios where due to lack of underlying data, only the first and second moment information can be established, but where the use of parametric probability distributions might be controversial. The recent generalizations of the classical Chebychev and Gauss inequalities are utilized in this respect. A numerical example is used for illustration.

THE COMMON BASIS FOR PROBABILISTIC AND NON-PROBABILISTIC DESIGN OF STRUCTURES UNDER DIFFERENT DEGREES OF DATA AVAILABILITY