The power of modelling in building design

By Andrea Frisque, Senior Associate and Building Performance Engineer at Stantec and instructor of the MEL in High-Performance Buildings

We’ve seen the benefits of data modelling and digital transformation in manufacturing, environmental science, medicine and other industries. When applied to building design, parametric modelling offers a powerful tool for understanding the implications of design decisions on a wide range of criteria.

In traditional energy models, you set up a relatively narrow field of parameters – which could include building geometry, insulation, glazing and mechanical systems – and then run the model to see the predicted performance of the proposed building design. If you want to change a design element, you run another simulation.

The new parametric models take classic energy simulations to a new level, leveraging multiple algorithms to create a comprehensive building model that takes into account many different metrics, all at once.

For example, a client may want a building to meet certain performance levels related to greenhouse gas emissions, thermal energy demand and embodied carbon to reach certification requirements. They may want to ensure the building design addresses other important considerations, such as the amount of interior space with access to views and daylight.

We can incorporate all possible design parameters and their various combinations into our model to explore how the criteria can be met through different design solutions. Similarly, we can adjust our designs and see the impact, be it on energy efficiency, natural light or total cost. It’s a very interactive process.

I teach two classes in the Master of Engineering in Leadership in High Performance Buildings program, and my students use energy models in both courses. I want them to know first-hand the value of building simulations within a project framework, and to develop an appreciation of the models’ limitations and constraints.

And there are constraints. From the perspective of pure physics, the accuracy of these simulations is high. The uncertainty lies in our assumptions and in how the buildings are actually used.

That’s one reason I ask students to incorporate their own assumptions about ventilation, occupancy schedules, equipment use and other criteria when developing a model for a new-build. The variation in results emphasizes the wide-ranging impact of our assumptions.

Looking ahead, one can imagine that it will become increasingly common to continue refining our parametric models for proposed buildings, adding in more criteria and layering in more data. We’re at the point technologically where the model can be used by an advanced manufacturing facility to create customized building components – the windows, joints and walls – enabling faster and lower-cost construction.

For us as engineers and architects working in this field, parametric models offer a useful way to explore the quantitative impact of key decisions, while also providing support for valuable conversations with our clients about trade-offs in their high-performing buildings.