This project developed an integrated parametric model in Dynamo, supported by an accompanying ontology, to explore the design of metro stations with above-ground buildings. The ontology provides a systematic description of system structure, dependencies, and constraints, supporting user understanding of how design parameters influence the parametric model. Dynamo, in turn, operationalizes this knowledge by generating quantitative outputs that can directly inform early-stage planning and design decisions. Together, these two layers support a clear understanding of how design decisions propagate across the integrated system.
The model currently focuses on operational energy efficiency and capacity as its primary performance outputs. This focused scope allows designers and planners to quickly evaluate the implications of key design decisions across different urban contexts. By prioritizing a limited set of influential parameters, the model is efficient at capturing essential relationships between geometry, capacity, and energy-related performance.
A possible improvement in the future would be to fine-tune the measurements of certain performance indicators. As of now, station box depth does not directly affect the ventilated air volume, which is the measured indicator for energy demand in our model. In practice, increased depth may influence ventilation energy demand due to longer air paths, higher pressure losses, and more complex mechanical systems. Similarly, stormwater vault performance is evaluated solely through storage volume relative to sealed surface area, without accounting for site-specific geotechnical or hydrological conditions such as soil permeability or drainage rates. These simplifications mean that the results are best interpreted as relative performance indicators rather than absolute predictions. They are still able, however, to provide a basis for informed decision-making during early planning stages.
The model fulfils two primary functions: design exploration and design comparison. As a design exploration tool, it allows planners and engineers to vary key parameters to explore the available design space based on constraints such as plot size and availability, with focus on its capacity and operational energy demand performance. As a design comparison tool, the model enables different design options to be evaluated under consistent boundary conditions, making trade-offs between spatial efficiency and envelope performance explicit. Together, these functions demonstrate the flexibility of the model in addressing a range of planning challenges encountered during early-stage metro station design.
The model also demonstrates strong potential as a decision-support and pre-screening tool. Its outputs, envelope U-values, passenger capacity, ventilated air volume, excavation volume, and stormwater storage can be readily transferred to more detailed simulation environments, including energy modelling tools like EnergyPlus or material and cost estimation workflows. In this sense, the model provides a valuable bridge between conceptual design and detailed analysis, helping to narrow down feasible and promising design alternatives at an early stage.
Overall, the project highlights the value of combining ontology-based system structuring with parametric modelling for integrated infrastructure design. While further development is required to capture more detailed operational behavior and site-specific conditions, the current model successfully reveals key trade-offs between spatial capacity, energy-related performance, and system configuration. With targeted extensions and external coupling, the model has clear potential to evolve into a more comprehensive and robust planning support tool for metro station design in diverse urban environments.