الفهرس 
Introduction to orthotropic steel decksOnly 14 pages are availabe for public view
 |  | from | 109 |  |  |
| | | from | 109 | | |
Abstract
We have two intents on originating design theories and computational models: automation and optimization. These two aspects are specifically significant in design of complex and large engineering structures. If there are complex interactions among features, then algorithms such as decision trees and neural networks work better, because they are specifically designed to discover these interactions. On computerizing fields such as conceptual design, material behaviour, damage detection and modeling of natural phenomenon etc., it is found to be intractable as it requires human expertise. Furthermore, in the early design stage, computerizing the information and knowledge is one of the main obstacles facing computer-based techniques, as it lacks tools for representation of designers’ expertise and anticipation. In addition to, on designing a structure, setting the right preliminary design factors reduces the number of reanalysis and redesign cycles. Consequently the concept of artificial neural networks is used, in this research, to develop an initiative design system for orthotropic bridge decks.For orthotropic decks a lot of progress has been made in the development of codes to aid in the design process, in addition to software tools for numerical analysis and design. However professional software tools will not aid the designer in choosing a preliminary economic layout at the preliminary design stage. Designers would go through iterative, lengthy and expensive procedures to reach the best configuration. The presented research provides a methodology to investigate the contingency of using artificial neural networks for conceptual design of orthotropic bridge decks. A neural network model was trained with different combinations of dimensions, where safety checks were previously performed on all of them. The resulting network can predict whether the deck is safe or not. Moreover, actual stresses and moments can be determined. It is found that this approach for the selection of orthotropic deck dimensions is a better and cost effective option compared with international codes or expert opinion. This research demonstrates how a new level in design automation is achieved through the ingenious use of a novel computational paradigm and new high–performance computer architecture.