Abstract
The dynamic identification of the modal parameters of a structure, in order to gain control of its functionality under operating conditions, is currently under discussion from a scientific and technical point of views. The experimental observations obtained through structural health monitoring (SHM) are a useful calibration reference of numerical models (NMs). In this paper, the procedures for the identification of modal parameters in historical bell towers using a stochastic subspace identification (SSI) algorithm are presented. Then, NMs are manually calibrated on the identification’s results. Finally, the applicability of a genetic algorithm for the automatic calibration of the elastic parameters is considered with the aim of searching for the properties of the autochthonous material, in order to reduce modelling error following the model assurance criterion (MAC). In this regard, several material values on the same model are examined to see how to approach the evolution and the distribution of these features, comparing the characterization proposed by the genetic algorithm with the results considered by the manual iterative procedure.
Highlights
Recent technological and code developments within civil engineering require buildings to be designed and verified from both a static and dynamic point of view
The age of buildings and materials, along with the lack of appropriate maintenance, negatively affect the global performance of existing constructions. All these specific problems lead to a search for accurate numerical models (NMs), usually with the finite element method (FEM) [6,7,8,9], through which it is possible to understand the real conditions of the structure with the intention of making predictions on its dynamic behavior [10] and design and plan effective maintenance interventions
While the Latin hypercube sampling (LHS) is a statistical method that generates random samples of parameter values coming from a multidimensional distribution, and the Bayesian model updating is a model approach that uses probability to represent all uncertainty within the model, the genetic algorithm [27,28,41,42] is a heuristic search approach that reflects the process of natural selection
Summary
Recent technological and code developments within civil engineering require buildings to be designed and verified from both a static and dynamic point of view. For long-term SHM, the output of this process is periodically updated, giving information on the ability of the structure to perform its intended function along time, considering the inevitable aging and degradation resulting from operational environments [18,19] After extreme events, such as earthquakes, or accidents such as blast loading and floods, SHM is used for a rapid condition screening to provide, in near real time, reliable information regarding the integrity of the structure [20,21,22]. The differences obtained from the two procedures are analyzed [29,30,31,32]
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