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What is Parametric Modeling?

July 9, 2013

Over coffee last week with Jonah Ross, a fellow parametric designer with Zimmer Gunsel Frasca here in Portland, our conversation turned to the term “parametric modeling,” how ill-defined it is, with so many different meanings and contexts. Does modeling in Rhino/Grasshopper make you parametric? Can you be parametric in Revit? Is it form? Is it structural analysis? Or are you parametric because you have little slider knobs and can manipulate your model?

So yesterday I was pleased when another colleague, a traditional architect, asked me what the term meant. This time I had a clearer answer to give him: parametric modeling is way to introduce the scientific method to your design process.

In science you first define a control experiment or observation point. From there you vary one or more independent variables to explore a space of possibilities. You gain understanding about the space of study by restricting yourself to just a few variables and observing the effect on the problem as a whole.

A parametric model uses precisely the same approach. We first create a base model, say a building that is 100 ft. by 100 ft. by 1 story tall. We next  identify the variable or variables we wish to study, such as the building’s height. We can now study how our building design changes in relation to that one variable’s changing value. How we evaluate the results depends on our design interests.

Perhaps it is floor/area ratios vs. building height. Or shadow studies. Or simply design aesthetics and whether we like a shorter or taller building. Using an independent variable and comparing how it changes our base design allows us to quickly and efficiently explore the design space affected by that parameter.

Parametric models are not necessarily computational. But unlike creating multiple physical models of the same problem, it is relatively easy to modify and analyze successive cases using 3d computational tools.

Control and independent variables

A parametric model with initial control state and independent variables to change it.

It’s important to remember that the  independent variable does not have to be a number controlled by a slider in a Grasshopper script. While anything in a computer model can ultimately be boiled down to numbers, specifically 1’s and 0’s, in a design study we may want to be more abstract. A parameter could be a curve defining the shape of a dome, for example, as in the Parametric Nervi study of the Palazzetto dello Sport model I developed when first studying parametric models. Rhino knows the mathematics of the curve I’ve drawn to define the shape of Nervi’s dome. But as a designer, I only want to think about that curve and what it does to the shape of the dome as I manipulate it, not about the numbers. In this instance I would not use a slider to explore my parameter space. Instead I would change the shape of the curve directly and if I want, save the different variations I try.

Curve parameters

This model of Nervi’s Palazzetto uses curves instead of numbers as parameters. Here the two red circles define the beginning and ending of the dome and the arc connecting them defines its shape.

An additional advantage of using a parametric approach is the opportunity to study not just the individual data points tested, but the overall response of the design to the changing values of the variable. If we change our proposed building’s height from 1 story to 100 in steps of 1 and the neighborhood association starts threatening lawsuits after we get to 40 stories, we’ve learned something important about the responsiveness of our design problem to that variable. We can thus derive a “feel” for the variable – how much the design resists or whether the variable is inconsequential – as we change it back and forth.

Because of the immensity of the multidimensional design space architects face each day, the thought of using the scientific method to explore it is indeed overwhelming. Just as a scientific experiment becomes useless with too many variables, a parametric model can become ridiculously difficult to create and maintain. We can, however, identify critical portions of the design space and specific variables under our control and, using a parametric approach, explore that specific response to its changing values.

Obviously there is a trade-off between over-analyzing a design problem and meeting budget and overhead constraints and tight delivery schedules. But by first using forethought and intuition to identify the right set of variables to study, a parametric model can be an enormously valuable tool in real and practical design processes.

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