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Published in Oscar Osvaldo Marquez-Calvo, Advancing Robust Multi-Objective Optimisation Applied to Complex Model-Based Water-Related Problems, 2020
Latin Hypercube sampling is employed. The sample consists of n = 1,000 demand pattern vectors u. For each pattern, the optimisation problem is solved using LOC, obtaining 1,000 Pareto-quasi optimal sets.
Analytical Derivation of Seismic Fragility Curves for Historical Masonry Structures Based on Stochastic Analysis of Uncertain Material Parameters
Published in International Journal of Architectural Heritage, 2019
Savvas Saloustros, Luca Pelà, Francesca R. Contrafatto, Pere Roca, Ioannis Petromichelakis
The main aim of this work is to contribute to the discussion on the possibility to apply probabilistic approaches for the seismic assessment of complex historical masonry structures in which a complete knowledge of the material properties is difficult. The presented results open new potential lines of research for the probabilistic seismic assessment of historical masonry structures, such as the study of the effect of the uncertainty related to the seismic hazard or the geometry of structural members. The study carried out on the representative bay structure of Santa Maria del Mar church in Barcelona encourages the possibility of investigating the seismic vulnerability of additional macro-elements of the same structure and the use of more complex 3D models. At the same time, it emerges the need for a definition of specific seismic damage limit states specifically associated with different structural typologies of irregular masonry structures (e.g. churches, cathedrals, palaces), beside the already investigated case of common masonry buildings. As for the proposed methodology based on Monte Carlo stochastic simulation, specific issues requiring further research are those related to the analysis of the effect of the sample size for different typologies of historical structures. To this end, the choice of different sampling strategies (e.g. Latin Hypercube Sampling, orthogonal sampling) can improve the efficiency of the sampling process.