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Abstract

The need for cost-efficient seismic design in limited time has led to the development of automated structural optimization methodologies. Genetic Algorithms (GA) belong to the class of stochastic, nature-inspired heuristic optimization algorithms. GA can be easily implemented and applied to advanced structural problems since they don’t require use of gradients of cost or constraints functions. Furthermore, they are able to identify global optima as opposed to local optimum solutions. Early efforts to optimise seismic design of concrete structures were based on traditional seismic design code approaches. The last two decades, performance- and deformation-based seismic design methodologies have emerged. These methodologies provide enhanced structural damage control for different earthquake intensities reducing both economic losses and human casualties. Lately, a fully-fledged performance- and deformation based design methodology has been incorporated in the fib Model Code for Concrete Structures MC2010, which is meant to serve as a guidance document for future design codes of concrete structures. To the best of author’s knowledge, there exists no study investigating optimum seismic design solutions in accordance with MC2010. The aim of this study is to develop a GAbased seismic design optimization framework for reinforced concrete frames in accordance with the provisions of both Eurocode 8 (EC8) and MC2010. Application of this framework to reinforced concrete frames is conducted and comparisons of the optimum solutions obtained by the two seismic design guidelines are made. The advantages and disadvantages of the two seismic design methodologies, in the context of structural optimization, are highlighted and discussed.

Publication Type:	Book Section
Additional Information:	© 2016 The Author.
Publisher Keywords:	Reinforced concrete, seismic, performance-based, Eurocodes, fib Model Code 2010, optimization, genetic-algorithms
Subjects:	T Technology > TA Engineering (General). Civil engineering (General)
Departments:	School of Science & Technology > Engineering

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