Publicacións

@article{Pérez2013463,

title = {Genetic programming to improvement FIB model bond and anchorage of reinforcing steel in structural concrete},

author = {Juan Luis Pérez-Ordoñez and Ismael Vieito and Juan R. Rabuñal-Dopico and Fernando Martínez-Abella},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84880051047&doi=10.1007%2f978-3-642-38679-4_46&partnerID=40&md5=8c465cefe68f516db1ae8015be1b825b},

doi = {10.1007/978-3-642-38679-4_46},

issn = {03029743},

year  = {2013},

date = {2013-01-01},

urldate = {2013-01-01},

journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},

volume = {7902 LNCS},

number = {PART 1},

pages = {463-470},

abstract = {Starting from the FIB database, this work is aimed to analyze the current equations which predict the main datum that can be provided by bond tests: the ultimate bar stress when the failure is reached. Furthermore, Genetic Programming (GP) techniques are also applied in order to enhance the expression of the FIB, which achieves the best adjustment so far, giving rise to the new Model Code 2010. The final result shown is a highly predictive equation. The results are compared with those included in the Model Code and it is showed the influence of the main variables on the phenomenon (concrete strength, yield strength of steel, concrete cover, transverse reinforcement and diameter of the bar). © 2013 Springer-Verlag Berlin Heidelberg.},

note = {cited By 2},

keywords = {Bond test; Concrete cover; Concrete strength; Current equation; Predictive equations; Reinforcing steels; Structural concretes; Transverse reinforcement, Concretes, Genetic programming; Neural networks; Reinforced concrete},

pubstate = {published},

tppubtype = {article}

}