No Arabic abstract
This paper describes the model updating procedure implemented in NOSA-ITACA, a finite-element code for the structural analysis of masonry constructions of historical interest. The procedure, aimed at matching experimental frequencies and mode shapes, allows fine-tuning calculation of the free parameters in the model. The numerical method is briefly described, and some issues related to its robustness are addressed. The procedure is then applied to a simple case study and two historical structures in Tuscany, the Clock Tower in Lucca and the Maddalena bridge in Borgo a Mozzano.
Limit analysis is a computationally efficient tool to assess the resistance and the failure mode of structures but does not provide any information on the displacement capacity, which is one of the concepts which most affects the seismic safety. Therefore, since many researchers did not consider limit analysis as a possible tool for the seismic assessment of structures, its widespread employment has been prevented. In this paper this common belief is questioned and the authors show that limit analysis can be useful in the evaluation of the seismic performance of frame structures. In particular, to overcome the limitation on the possibility to evaluate the displacements of a structure based on a limit analysis approach, an approximated capacity curve is reconstructed. The latter is based on a limit analysis strategy, which takes into account the second order effects, and evaluates the displacement capacity considering a post-peak softening branch and a threshold on the allowed plastic rotations. Then, based on this simplified capacity curve, an equivalent single degree of freedom system is defined in order to assess the seismic performance of frame structures. The proposed simplified strategy is implemented in a dedicated software and the obtained results are validated with well-established approaches based on nonlinear static analyses, showing the reliability and the computational efficiency of this methodology
This study presents a meshless-based local reanalysis (MLR) method. The purpose of this study is to extend reanalysis methods to the Kriging interpolation meshless method due to its high efficiency. In this study, two reanalysis methods: combined approximations CA) and indirect factorization updating (IFU) methods are utilized. Considering the computational cost of meshless methods, the reanalysis method improves the efficiency of the full meshless method significantly. Compared with finite element method (FEM)-based reanalysis methods, the main superiority of meshless-based reanalysis method is to break the limitation of mesh connection. The meshless-based reanalysis is much easier to obtain the stiffness matrix even for solving the mesh distortion problems. However, compared with the FEM-based reanalysis method, the critical challenge is to use much more nodes in the influence domain due to high order interpolation. Therefore, a local reanalysis method which only needs to calculate the local stiffness matrix in the influence domain is suggested to improve the efficiency further. Several typical numerical examples are tested and the performance of the suggested method is verified.
The prediction of thermo-mechanical behaviour of heterogeneous materials such as heat and moisture transport is strongly influenced by the uncertainty in parameters. Such materials occur e.g. in historic buildings, and the durability assessment of these therefore needs a reliable and probabilistic simulation of transport processes, which is related to the suitable identification of material parameters. In order to include expert knowledge as well as experimental results, one can employ an updating procedure such as Bayesian inference. The classical probabilistic setting of the identification process in Bayess form requires the solution of a stochastic forward problem via computationally expensive sampling techniques, which makes the method almost impractical. In this paper novel stochastic computational techniques such as the stochastic Galerkin method are applied in order to accelerate the updating procedure. The idea is to replace the computationally expensive forward simulation via the conventional finite element (FE) method by the evaluation of a polynomial chaos expansion (PCE). Such an approximation of the FE model for the forward simulation perfectly suits the Bayesian updating. The presented uncertainty updating techniques are applied to the numerical model of coupled heat and moisture transport in heterogeneous materials with spatially varying coefficients defined by random fields.
In this paper, we investigate the collective synchronization of system of coupled oscillators on Barab{a}si-Albert scale-free network. We propose an approach of structural perturbations aiming at those nodes with maximal betweenness. This method can markedly enhance the network synchronizability, and is easy to be realized. The simulation results show that the eigenratio will sharply decrease to its half when only 0.6% of those hub nodes are under 3-division processes when network size N=2000. In addition, the present study also provides a theoretical evidence that the maximal betweenness plays a main role in network synchronization.
The preliminary analyses on a multiscale model of intestinal crypt dynamics are here presented. The model combines a morphological model, based on the Cellular Potts Model (CPM), and a gene regulatory network model, based on Noisy Random Boolean Networks (NRBNs). Simulations suggest that the stochastic differentiation process is itself sufficient to ensure the general homeostasis in the asymptotic states, as proven by several measures.