Bionic Optimization of Concrete Structures by Evolutionary Algorithms

Abstract

Floor slabs represent a large volume of concrete in buildings. The goal of this research is to achieve a structure that has an optimized bearing capacity. The optimization implies economic efficiency and sustainability. This paper describes a bionic optimization process that is applied in a project of the German Research Foundation (DFG) Priority Programme called “Concrete light. Future concrete structures using bionic, mathematical and engineering formfinding principles”. The project involves adaption of three different natural structures that lead to a natural flow of forces. These natural structures are (a) spider webs, (b) hollow parts of bones and (c) geometries of structures such as the bottom side of water lilies or seashells.

This scientific paper deals with the implementation of an optimization process for a configuration of reinforcement inspired by a spider web. Evolutionary Algorithms (EAs) are used for the development and optimization of an innovative and useful configuration of reinforcement.

The EAs use reproduction, mutation and selection as mechanisms, inspired by biological evolution, to solve technical problems gradient-free. In this project the EA is combined with physical nonlinear finite element analyses. The EA is embedded into a C# application, in which the slab structure is generated and the finite element programme is started. The quality of the results is characterized by the fitness of each individual (reinforcement configuration), which is, for this example, the midspan displacement of the generated slab multiplied by the steel volume per slab. Accordingly, the midspan displacement is to be minimized during the process, with the minimum possible amount of reinforcement. The optimization variables are the angles and the number of rebars per slab. Several constrains need to be included to get comparable results between the developed slabs and the conventional slabs with orthogonally configured reinforcement.

This paper presents the results of an optimized reinforcement configuration thus found by EA and comparisons with the behaviour of conventional slabs with a similar reinforcement ratio.

Keywords::

• optimization
• bionic
• formfinding
• Evolutionary Algorithms
• structural concrete
• reinforcement configuration