Multi-objective optimization of a composite orthotropic bridge with RSM and NSGA-II algorithm

To address the problems of pavement damage and fatigue cracking of orthotropic steel deck (OSD) in bridges with traditional asphalt overlay, an innovative composite bridge deck composed of OSD with open ribs and ultrahigh performance concrete (UHPC) layer was proposed. This paper firstly investigates the stress responses of fatigue-prone details in the composite bridge deck by refined two-scale finite element analysis. The results show that the rib-to-deck joint can achieve an infinite fatigue life, while the floorbeam detail of rib-to-floorbeam joint indicates finite fatigue life. Then, approximate regression models of stress ranges of fatigue details and structure weight were derived via both the central composite design and response surface method. The analysis of correlation and variance demonstrates that the response surface models are significant and sufficiently accurate to predict the objective responses. And 3-D response surface plots were developed to display the interaction effect between each pair of structural parameters on objective responses. Finally, to improve the fatigue performance for achieving an infinite fatigue life under relatively low structure weight, the multi-objective optimization was executed by an Improved Non-dominated Sorting Genetic Algorithm (NSGA-II). The obtained Pareto front shows that there is a strong competition between the stress range of fatigue-prone detail and structure weight. Under the principle of relatively low structure weight, the obtained structural parameters satisfying infinite fatigue life imply that the deck plate thickness is 10 mm, and the floorbeam spacing is 2.4 m as well as the floorbeam thickness is not less than 12 mm.

Automated summary

A novel composite bridge deck with open ribs and ultrahigh performance concrete (UHPC) layer was proposed to address pavement damage and fatigue cracking in orthotropic steel deck (OSD) bridges. Stress responses of fatigue-prone details were investigated through finite element analysis, and regression models were derived to predict stress ranges of fatigue details and structure weight. Multi-objective optimization using an Improved Non-dominated Sorting Genetic Algorithm (NSGA-II) showed a strong competition between stress range of fatigue-prone details and structure weight under the principle of relatively low structure weight, resulting in specific structural parameters for infinite fatigue life.