Evaluation of test loads by means of Bayes' theorem.

Abstract

For existing structures, load tests are often carried out to demonstrate the load-bearing capacity. Reasons for this can be found in a number of unknowns regarding the design loads, the materials used and their current condition, the design assumptions and even system behaviour. Because of this, a different (higher) load bearing capacity can sometimes be obtained than on the basis of simple calculation models. Unfortunately, codes or guidance is lacking as to what load level such a test should be carried out for, and there is even discussion about the sense of such large-scale tests.

Mechanical considerations regarding the structural response obviously also play a role and are briefly explained, but do not form the main part of this contribution. Using the Bayes theorem, an answer can be given to the question what the failure probability is of a structure in case the structure has passed a load test of a given load level. The failure probability of the existing structure is handled as prior knowledge which might be estimated based on expert judgement. After performing a load test till a certain level, the posterior can be calculated expressing the failure probability of the system after it successfully passed a load test.

To the best of our knowledge, this is the first time that this issue has been addressed in a probabilistic way for buildings. The results show the benefits of (heavy) test loads to obtain an idea about the reliability of existing structures. In that way, the approach is of great practical importance to enable a valorisation of the existing (historical) building stock. In this sense, this contribution helps to achieve the set of sustainability goals, as responsible reuse of entire structures leads to major energy savings, even more so than recycling or the use of new sustainable materials.