Genetic Algorithms in Optimum Concrete Design

Engr. Alden Balili, my graduate thesis advisee did a research on the application of genetic algorithms (GA) in the optimum design of reinforced concrete (RC) space frames considering seismic provisions of the code. The process of GA and its application to the optimization of space frames is in the figure below. Initially, the sizes of the beams and columns of the space frame are randomly selected which becomes the initial population. These sizes are then used by a separate Finite Element Analysis program to determine the member forces which are required in the design of the members including the amount of steel reinforcements. A database of the beam and column sections is used in the design process. The provisions of the National Structural Code of the Philippines (2001) are incorporated in the fitness evaluation of the solution or individual to satisfy the strength and serviceability requirements. The GA procedures of selection, cross-over, mutation and leader reproduction are then applied to generate a new population of solutions. He conducted GA simulations to determine the behavior of the optimization procedure using the different GA procedures like binary vs gray coding, leader reproduction and mutation. Based on his simulations, a new type of leader reproduction called modified leader reproduction was proposed. It was found out that this feature improved the effectiveness and efficiency of the concrete optimization algorithm to acquire the optimal values.

A paper on this study will be presented at the IABSE 2009 Conference at Bangkok, Thailand on Sept. 9-11, 2009.

A Neural Network Model for Confined RC Column

Artificial Neural Networks (ANN) are information – processing systems whose architecture mimic the biological system of the brain. Recently, civil engineers have utilized ANN for various applications especially in the modeling of civil engineering systems.

In my case, I developed an ANN model for predicting the confined compressive strength and strain of a circular reinforced concrete column. The model has seven input nodes: (1) unconfined concrete cylinder strength, f’c; (2) concrete core diameter, d, where the core is the part of the section enclosed by the centroidal axis of the hoop or ties; (3) column height, H; (4) yield strength of lateral reinforcement, fyh; (5) volumetric ratio of lateral reinforcement; (6) tie spacing, s ; and (7) vertical steel or longitudinal reinforcement ratio. The two output nodes, on the other hand, represent the peak stress or compressive strength of confined concrete circular column, f’cc and the strain, ecc , at peak stress. Shown below is the GUI of the Visual Basic program of the ANN model.

The predictions of the compressive strength or peak stress, f’cc, of confined concrete columns and the corresponding strain, ecc, have been a subject of various researches, both analytical and experimental. The values of these two parameters are usually used in the analytical models developed for describing the stress-strain relationship for confined concrete.

You may run the ANN model at http://mysite.dlsu.edu.ph/faculty/oretaa. Go to the Software section. Papers on the model can also be downloaded from this site.