In the present study, the optimal seismic design of reinforced concrete (RC) buildings is obtained. For this purpose, genetic algorithms (GAs) are used through the technique NSGA-II (Nondominated Sorting Genetic Algorithm), thus a multiobjective procedure with two objective functions is established. The first objective function is the control of maximum interstory drift which is the most common parameter used in seismic design codes, while the second is to minimize the cost of the structure. For this aim, several RC buildings are designed in accordance with the Mexico City Building Code (MCBC). It is assumed that the structures are constituted by rectangular and square concrete sections for the beams, columns, and slabs which are represented by a binary codification. In conclusion, this study provides complete designed RC buildings which also can be used directly in the structural and civil engineering practice by means of genetic algorithms. Moreover, genetic algorithms are able to find the most adequate structures in terms of seismic performance and economy.
The present work shows the study of the distribution of current and electrochemical potential in the reinforcing steel by using as anode a layer of cement paste added with graphite powder and carbon fiber. The research was carried out on concrete slabs with w / c ratio of 0.5. Each slab is placed 12 steel rods. One of the slabs was contaminated with Cl- added in the mixing water 5% NaCl by weight. Was applied on each slab a layer thickness of 1cm conductive cement paste. Was measured current draw of each rod as well as the polarized potential. The use of a cement material conductive paste shows a good performance as anode in the PCCI reinforcing steel to achieve maintain polarized potential of-800mV.
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