WIT Press


Heuristic Optimization Of Prestressed Concrete Precast Pedestrian Bridges

Price

Free (open access)

Paper DOI

10.2495/OP090111

Volume

106

Pages

10

Page Range

121 - 130

Published

2009

Size

251 kb

Author(s)

J. V. Martí, F. González-Vidosa & J. Alcalá

Abstract

This paper deals with the economic optimization of prestressed concrete precast pedestrian bridges typically used in public works construction. These bridges are made of a precast concrete beam that integrates an upper reinforced concrete slab for the pedestrian traffic. The beam has a U-shape cross-section. Typical span lengths range from 20 to 40 m and the width ranges from 3.00 to 6.00 m. The study shows the efficiency of heuristic optimization by the simulated annealing (SA) and the threshold accepting (TA) algorithms. The evaluation of solutions follows the Spanish Code for structural concrete. Stress resultants and envelopes of these structures are computed by direct calculation. Design loads are in accordance with the national IAP Code for road bridges. The algorithms are applied to a typical pedestrian bridge of 40 m of span length and 6.00 m of width. This example has 59 discrete design variables for the geometry of the beam and the slab, materials in the two elements and active and passive reinforcement. The evaluation module includes the limit states that are commonly checked in design: flexure, shear, deflections, etc. The application of the SA and TA algorithms requires the calibration of the initial temperature and threshold, the number of variables modified in each iteration, the length of the Markov chains and the reducing coefficient. Each heuristic is run nine times so as to obtain statistical information about the minimum, average and deviation of the results. The best result has a cost of 27,586 euros for the SA algorithm and 27,570 euros for the TA algorithm. Finally, solutions and run times indicate that heuristic optimization is a forthcoming option for the design of real prestressed structures. Keywords: economic optimization, heuristics, concrete structures, structural design.

Keywords

economic optimization, heuristics, concrete structures, structural design.