If you’re an architect or designer working in the built environment, I’d guess science wasn’t your favorite subject in high school. Acutesqueamishness was an impediment for me. Forget cutting frogs open, I still can’t even look at a needle. My career in the biological sciences was over before it began.
What would scientific research look like in an architectural firm? Would we ask questions and formulate hypotheses to answer them? Would we conduct experiments, control variables, manage complexity, observe and analyze test results? And would we record our findings and apply what we have learned to refine the hypotheses?
Sure. Why not? Think of it this way: we create drawings and models that are analogs for things that must go through an extraordinarily complex process in order to become real. We’re dealing with a vast amount of uncertainty and we need to trust our time-tested methods in order to achieve the intended results. Plus, we have committed to incrementally reduce the energy use of those analogous creations.
Therefore, if we want the results of our time-tested methods to improve, we need to be more rigorous about our processes. I propose we do some actual research.
And in the spirit of this blog, I offer Bergmeyer’s experiments as a case study.
My hat is off to the design firms I know that employ building scientists or have trans-disciplinary research groups in house. We admire and respect what you do. But if you don’t mind, we’re going to borrow your methodology.
Here we go. Lab coats and goggles? On.
By itself, we find the question “how do we meet the AIA 2030 Commitment energy use reduction standards?” is too broad to be practicable. But as much of our work is interior architecture, most of our projects’ intended energy use can be estimated by using Lighting Power Density. So to make progress on AIA 2030 goals, we need to improve our cumulative design LPD.
Here’s where complexity and uncertainty factor in: for our retail work, energy codes give exceptions and allowances for display lighting and fixture lighting. The LPD numbers we get from engineers only count general illumination. So we’re having a hard time getting our arms around how an actual LPD is even calculated.
But creation is a patient search, right? And a good design process starts with a good question. Ergo, our restated (and researchable) question: How can we effectively improve LPD across all our design work?
And our hypothesis: If we can create our own approach to calculating LPD – either a software plug-in or a calculation methodology – and we provide this approach to our design teams, that should produce a reduction in firmwide LPD.
Our investigation will be in three stages: first, we will explore the feasibility of creating either a software plug-in or a calculation method for actual LPD versus code-compliant LPD. After we create the tool, we’ll pick several projects as a control group. Some teams will use the tool, some will not.
After project design phases are complete, we’ll record the LPDs and compare the results. We’ll also interview the designers who worked with our tool to see how useful it was. Finally, we’ll record the results and publish a report of our findings. On our website. In six months. We hereby promise.
It isn’t likely that we’ll make Scientific American or Engineering News Record. But if we can move the needle (ugh! Again with the needles!) on energy efficiency just a bit, I’d call it research well done. We’ll keep you posted.
This post originally appeared on the blog of Principal Mike Davis, FAIA.