Optimizing Vents Layout and Configuration of Complex Urban Tunnels for Air Quality Control

We propose a systems approach and an optimization model for determining the number, locations, and capacities of upper vents in complex urban tunnels that minimize the overall installation and operation cost considering various siting and air quality control constraints. Based on steady-state modeling, we show that this vents layout problem is not easy even for the simplest tunnel. We formulate it as a nonlinear integer programming problem solved via the genetic algorithm. For demonstration, the method is applied to a case study of a newly built urban tunnel in Hangzhou, China. Results show that the optimal solutions are highly nontrivial if constraints such as discharge intensity and discharge proportions of nitrogen oxides at different vents and tunnel exits are imposed. Depending on constraints that have to be considered, the optimal vents cost varies significantly for the studied case from $22 000 to $90 000. The cost can be easily doubled with an additional air quality constraint. The model proves a useful quantitative tool for tunnel systems control.