Structural Identification to Improve Bridge Management

Abstract

This paper presents results from static loads tests performed on the new Langensand Bridge built in Switzerland. A systematic study of over 1000 models subjected to three load cases identifies a set of 11 candidate models through static measurements. Predictions using the set of candidate models are homogenous and show an averaged discrepancy ranging of 4 to 7% from the displacement measurements. All candidate models have values for material proprieties that are close to expected values. This finding confirms that the behaviour of the structure conforms to the design expectations. Comparing the candidate model set to a design model that takes into account only main structural elements shows that the structure has approximately 30% reserve capacity with respect to a typical deflection risk scenario according to Swiss codes. The population of candidate models may be used to understand and predict the behaviour of the full bridge prior to its completion.

Probabilistic-based assessment of existing steel-concrete composite bridges – Application to Sousa River Bridge

“…In order to perform the model identification, it is necessary to determine the threshold value, ε, that defines the fitness function convergence criteria. Thus, it is first necessary to identify and quantify the different sources of error [12,[23][24][25][34][35][36], see Table 4.…”