“Scaglia Rossa” experimental campaign and model updating for numerical damage evaluation

This paper outlines the characterization of masonry walls composed of “Scaglia Rossa”, a typical stone of the Apennine area between the Umbria and Marche Regions in Central Italy. The study focuses the assessment of the mechanical behavior by means of an experimental campaign carried out in the laboratory of the Polytechnic University of Marche, where the samples of “Scaglia Rossa” masonry, obtained from the controlled demolition of three school buildings, were reconstructed with the same techniques of the 1950s-'60s, and then tested in order to identify both the constituent materials, stone and mortar, and the composite masonry. The experimental tests were prior to a numerical analysis implemented by the adoption of a nonlinear model capturing the cracking behavior. The main mechanical parameters were then calibrated by means of an optimization algorithm of Levenberg-Marquardt, considering a continuous approach in macro-modelling techniques and obtaining resistance parameters not deriving directly from the experimental tests. The comparison between the results obtained from the Levenberg - Marquardt algorithm by changing the parameters of the damage model based on data given by the experimental campaign allowed to confirm the validity of the approach used

Mechanical characterization of “Scaglia Rossa” stone masonry through experimental and numerical analyses

This paper outlines the complete characterization of masonry walls composed of “Scaglia Rossa”, a typical stone of the Apennine area between the Umbria and Marche Regions in Central Italy. The study focuses the assessment of the mechanical behavior by means of an experimental campaign carried out in the laboratory of the Polytechnic University of Marche, where the samples of “Scaglia Rossa” masonry, obtained from the controlled demolition of three school buildings, were reconstructed with the same techniques of the 1950s-‘60s, and then tested in order to identify both the constituent materials, stone and mortar, and the composite masonry. The experimental tests were prior to a numerical analysis implemented by the adoption of a nonlinear model capturing the cracking behavior. The main mechanical parameters were then calibrated by means of an optimization algorithm of Levenberg-Marquardt, considering a continuous approach with both (i) macro- and (ii) micro-modelling techniques and obtaining resistance parameters not deriving directly from the experimental tests. The comparison between the results obtained from the Levenberg - Marquardt algorithm by changing the parameters of the damage model based on data given by the experimental campaign allowed to confirm the validity of the approach used

Dynamic Identification and Automatic Updating of the Numerical Model of a Masonry Tower

The actual dynamic behavior of the masonry civic Clock tower in a little village, heavily damaged by the recent 2016 seismic sequence of central Italy, is thoroughly investigated by means of a detailed numerical model built and calibrated using the experimental modal properties obtained through Ambient Vibration Tests. The goal is to update the uncertain parameters of the Finite Element Model (elastic moduli, mass densities, constraints, and boundary conditions) to minimize the discrepancy between experimental and numerical dynamic features. Due to the high nonlinear dependency of the objective function of this optimization problem on the afore-mentioned parameters, and the likely possibility to get trapped in local minima, a fully automated Finite Element Model updating procedure based on genetic algorithms and global optimization is used, leading to the successful estimation of the uncertain parameters of the tower. The results allowed to create a reference digital replica of the current structural condition of the tower and to set the performance standards that will help to optimize the control of the structural integrity over time

A Genetic Algorithm Procedure for the Automatic Updating of FEM Based on Ambient Vibration Tests

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

Combining operational modal analysis and genetic algorithms to understand the actual structural behavior of historical constructions

Evolution of technologies both in the fields of in situ investigations and Finite Element (FE) modeling strongly enhanced the possibility to understand the structural dynamic behavior of masonry historical constructions, allowing a periodic or continuous analysis of their response to environmental, anthropic, and exceptional actions and the formulation of accurate hypotheses about their future behavior, which is fundamental for Cultural Heritage preservation. In order to improve the assessment of the health status of historical buildings, inverse methods re-sorting to dynamic identification techniques are often used to provide experimentally verified data for the accurate calibration of FE models representative of the investigated structures. In this paper, vibration-based identification methods are coupled with an automatic FE model updating procedure to study the dynamic behavior of the Civic Tower of Ostra, Italy, and obtain baseline information for future comparative analyses. The experimental data obtained from two different campaigns of ambient vibration tests are used to update the mechanical characteristics of the detailed FE model of the tower. The updating process, unsolvable via common calibration procedures, is automatically managed through a powerful bio-inspired tool, i.e. the Genetic Algorithm (GA), allowing to closely reproduce the actual behavior of the tower

Out-of-plane seismic response of a masonry facade using distinct element methods

Damage surveys after earthquakes showed that unreinforced masonry buildings are prone to local failure modes related to out-of-plane mechanisms of walls caused by the poor connection with the orthogonal walls. Otherwise, if the masonry element rises isolated it may be subject to overturning mechanisms rather than in-plane collapse. Nowadays, several methods can be used to evaluate collapses. These methods require quite a high computational cost, not beneficial to practitioners. Advanced numerical models can be applied, such as the discrete element and non-smooth contact dynamics methods, which treat the masonry as a set of either rigid or deformable blocks that can slide and impact each other. In this paper, an ancient (isolated) masonry wall is analysed, and the results provide the first comparison between two numerical models to estimate the influence of the intervention placed on the top of the wall

Evolutionary numerical model for cultural heritage structures via genetic algorithms: a case study in central Italy

In this paper the actual dynamic behavior of the civic Clock tower of Rotella, a little village in central Italy heavily damaged by the recent 2016 seismic sequence, is thoroughly investigated by means of a detailed numerical model built and calibrated using the experimental modal properties obtained through Ambient Vibration Tests. The goal is to update the uncertain parameters of two behavioral material models applied to the Finite Element Model (elastic moduli, mass densities, constraints, and boundary conditions) to minimize the discrepancy between experimental and numerical dynamic features. A sensitivity analysis was performed with the definition of a metamodel to reduce the computational strain and try to define the necessary parameters to use for the calibration process. Due to the high nonlinear dependency of the objective function of this optimization problem on the parameters, and the likely possibility to get trapped in local minima, a machine learning approach was meant. A fully automated Finite Element Model updating procedure based on genetic algorithms and global optimization is used, leading to tower uncertain parameters identification. The results allowed to create a reference numerical replica of the structure in its actual health state and to assess its dynamic performances allowing better control over their future evolution