The measured maximum resistance of a concrete or mortar specimen to axial compressive loading; expressed as force per unit crosssectional area; or the specified resistance used in design calculations.
Published in Chapter:
EC Techniques in the Structural Concrete Field
Juan L. Pérez (University of A Coroña, Spain), Belén González-Fonteboa (University of A Coroña, Spain), and Fernando Martínez-Abella (University of A Coroña, Spain)
Copyright: © 2009
|Pages: 6
DOI: 10.4018/978-1-59904-849-9.ch080
Abstract
Throughout the last decades, one of society’s concerns has been the development of new tools to optimize every aspect of daily life. One of the mechanisms that can be applied to this effect is what is nowadays called Artificial Intelligence (AI). This branch of science enables the design of intelligent systems, meaning that they display features that can be associated to human intelligence, search methods being one of the most remarkable. Amongst these, Evolutionary Computation (EC) stands out. This technique is based on the modelling of certain traits of nature, especially the capacity shown by living beings to adapt to their environment, using as a starting point Darwin’s Theory of Evolution following the principle of natural selection (Darwin, 1859). These models search for solutions in an automatized way. As a result, a series of search techniques which solve problems in an automatized and parallel way has arisen. The most successful amongst these are Genetic Algorithms (GA) and, more recently, Genetic Programming (GP). The main difference between them is rooted on the way solutions are coded, which implies certain changes in their processing, even though the operation in both systems is similar. Like most disciplines, the field of Civil Engineering is no stranger to optimization methods, which are applied especially to construction, maintenance or rehabilitation processes (Arciszewski and De Jong, 2001) (Shaw, Miles and Gray, 2003) (Kicinger, Arciszewski and De Jong, 2005). For instance, in Structural Engineering in general and in Structural Concrete in particular, there are a number of problems which are solved simultaneously through theoretical studies, based on physical models, and experimental benchmarks which sanction and adjust the former, where a large amount of factors intervene. In these cases, techniques based on Evolutionary Computation are capable of optimizing constructive processes while accounting for structural safety levels. In this way, for each particular case, the type of materials, their amount, their usage, etc. can be determined, leading to an optimal development of the structure and thus minimizing manufacturing costs (Rabuñal , Varela, Dorado, González and Martínez, 2005).