Optimal Deep Learning Assisted Design of Socially and Environmentally Efficient Steel Concrete Composite Bridges under Constrained Budgets

Abstract

Steel-concrete composite bridges are used as an alternative to concrete bridges because of their ability to adapt their geometry to design constraints and the possibility of reusing some of the materials in the structure. In this review, we report the research carried out on the design, behavior, optimization, construction processes, maintenance, impact assessment, and decision-making techniques of composite bridges in order to arrive at a complete design approach. In addition to a qualitative analysis, a multivariate analysis is used to identify knowledge gaps related to bridge design and to detect trends in research. An additional objective is to make visible the gaps in the sustainable design of composite steel-concrete bridges, which allows us to focus on future research studies. The results of this work show how researchers have concentrated their studies on the preliminary design of bridges with a mainly economic approach, while at a global level, concern is directed towards the search for sustainable solutions. It is found that life cycle impact assessment and decisionmaking strategies allow bridge managers to improve decision-making, particularly at the end of the life cycle of composite bridges.