PSI - Issue 44

Francesco Nigro et al. / Procedia Structural Integrity 44 (2023) 1704–1711 F. Nigro, R. Falcone, E. Martinelli/ Structural Integrity Procedia 00 (2022) 000–000

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(reported in Fig. 4) is probably affected by the fact that the employed analysis method is not able to properly take into account the effects of an asymmetric plan distribution of the braces; • since the “as-built” structure belongs to the “C” class, local interventions (mainly concentrated at the 1 st story) are sufficient to achieve an upgrading to the “B” class; this should be a result of the fact that the columns of the 1 st story are characterized by a lack in ductility with respect to the members of other stories. The confinement interventions provided in the former case are able to enhance the seismic displacement capacity through a displacement capacity that leads the structure to the “B” class. 4. Conclusion The main objective of the present paper consists in outlining the capacity of a Soft-Computing procedure based on a Genetic Algorithm, that was firstly formulated by Falcone (2017), in supporting practitioners in the choice of the most suitable upgrading solution, which is usually a mind-boggling process. Examining the abovementioned results, it might be stated that the proposed GA has shown a good ability of exploration of the search space and a good adaptability to the different constraints imposed to it, since it is able to recognize which are the most suitable kind of intervention depending on the required level of upgrade. It is worth noticing that the procedure can be generalized to different optimization objectives, modifying the objective function, and varying the constraint imposed to the solution, ensuring to achieve an optimal solution that is also admissible from the engineering viewpoint. Moreover, the results obtained in the present work put in evidence some relevant issues (concerning either the algorithm input parameters or the analysis method), that can be pursued in order to increase the GA capacity to provide results that at the same time result to be “optimal” with respect to a predefined criterion and similar to the “intuitive engineering judgement”. References Baros, D.K., Dritsos, S. E., 2008. A simplified procedure to select a suitable retrofit strategy for existing RC buildings using pushover analysis. Journal of Earthquake Engineering, 12(6), 823-848. CNI, 2012. Elaboration of National Council of Engineers (CNI) Study Center on Istat, CRESME, and Civil Protection data. CNR-DT 200 R1/2013, 2013. Istruzioni per la progettazione, l’esecuzione ed il controllo di interventi di consolidamento statico mediante l’utilizzo di compositi fibrorinforzati. Darwin, C., 1859. In “ The origin of species by means of natural selection ”. Murray. J. London. Di Trapani, F., Sberna, A.P., Marano, G.C., 2022. A genetic algorithm-based framework for seismic retrofitting cost and expected annual loss optimization of non-conforming reinforced concrete frame structures. Computers and Structures 271, 106855. DM 17/01/2018, 2018. Italian Technical Code of Constructions; Ministerial Decree: Rome, Italy. DM 65, 07/03/2017, 2017. Allegato A: Linee guida per la classificazione del rischio sismico delle costruzioni. Ministerial Decree: Rome, Italy. EN 1998-3:2005, 2005. Design of structures for earthquake resistance. Part 3: Assessment and retrofitting of buildings. European Committee for Standardization, Bruxelles. European Environmental Agency, 2020. Land use. Available online at https://www.eea.europa.eu/themes/landuse/intro. Faella, C., Martinelli, E., Nigro, E., 2008. A rational strategy for seismic retrofitting of RC existing buildings. Proceedings of the 14th World Conference on Earthquake Engineering, Beijing, China, 12–17 October. Fajfar, P., 1999. Capacity Spectrum Method Based on Inelastic Demand Spectra. Earthquake Engineering and Structural Dynamics, 28(9), 979 993. Falcone, R., 2017. Optimal seismic retrofitting of existing RC frames through Soft-Computing approaches. PhD Course on Risk and Sustainability in Civil, Architectural and Environmental Engineering Systems, XXX Cycle, University of Salerno. Falcone, R., Carrabs, F., Cerulli, R., Lima, C., Martinelli, E., 2019. Seismic retrofitting of existing RC buildings: a rational selection procedure based on Genetic Algorithms. Structures 22, 310–326. Falcone, R., Lima, C., Martinelli, E., 2020. Soft computing techniques in structural and earthquake engineering: a literature review. Engineering Structures 207, 110269. Mazzoni, S., McKenna, F., Scott, M. H., Fenves, G. L., et al., 2006. “Open System for Earthquake Engineering Simulation User Command Language Manual”. Papavasileiou, G.S., Charmpis, D.C., Lagaros, N.D., 2020. Optimized seismic retrofit of steel-concrete composite buildings. Engineering Structures 213, 110573. Prezzario Campania LL.PP., 2016. PREZZARIO REGIONALE DEI LAVORI PUBBLICI ANNO 2016. Delibera della Giunta Regionale n. 359 del 13/07/2016.