Validating Lighting Simulation in the Studio

Validating Lighting Simulation in the Studio Thinking about our luminous environment helps us not only explore the future of our studio space but also test the tie between simulation and reality.

Natural light complements artificial light at the WWLTV studio headquarters.

Effective architecture is ultimately motivated by the human experience. To design high performance buildings that enhance occupant health and comfort, we have to consider environmental factors such as lighting. Analysis of both natural and artificial light (using Autodesk Insight for Revit1 at Eskew+Dumez+Ripple) helps us check that our designs perform optimally and provide the intended experience in a given space. Although light modeling at EDR is mainly focused on daylight analysis, artificial light brings forth complexity that we ought to be able to faithfully model, even without the help of an electrical engineer. With such a powerful way to guide the design process—not simply used

post hoc—we should be confident that the tool accurately reflects the physical world.

The effort to validate this simulation tool has fortuitous overlap with a side project at EDR. We are consistently trying to improve our own space and use it as an environment for experimentation.

Developing an open studio space with optimal lighting is a way that we can practice what we preach about sustainable design and occupant comfort. In this post, we will use our own studio’s exploration of potential future lighting schemes as a way to demonstrate what we did and what we learned when assessing a simulation tool.

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Exploring Better Studio Lighting The studio’s goal was to create a lighting scheme that would achieve the recommended ambient light level of about 30 footcandles for an open office. 2 Our current studio’s open plan features desks grouped into linear clusters—with a low partition down the “spine” of each—and other programs (e.g., conference rooms, pin-up spaces) interspersed across the space.

In this exercise, we exploited the current desk arrangements to test potential interventions for light.

The existing lights include indirect lamps in the bays

of the ceiling as well as small spotlights around some peripheral spaces and walls. The schemes that we considered for the analysis were: three or four 6.5-foot tall direct/indirect floor lamps along each spine (partition between rows of desks), a double row of linear direct/indirect lights above each spine, and a denser grid of linear lights across the whole space (see studio diagram). In addition to the lighting choices, we considered ceiling surfaces that might reflect light differently: the existing concrete, white paint, and white acoustic panels.

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Connecting Simulation and the Physical World The statistician George Box said that “all models are wrong, but some are useful.� Is our use of models for lighting analyses useful? We used a threepronged approach to assess the lighting analysis tool. Simulation is what helps to forecast the luminous environment (during and after design). With access to the same light fixtures and environmental conditions in real life, it is possible to corroborate output of the simulation with measurements. And if that is not possible, the amount of light expected to fall on the desk can be estimated using calculations.

These methods together help ensure that our tools

are valid and can be used reliably to inform design.

As a baseline for comparison with the simulation of existing conditions, we used a light meter to measure real light levels around the studio on a clear day at 9AM, 12PM, and 3PM. This process would eventually act as a calibration for existing conditions of the model when the only light sources were sunlight and peripheral lights, which were consistent among analyses. Later, the calibrated model would serve as a starting point for the judgment of the other light schemes.

Output of lighting analysis as a gradient map (left) and data points (right).

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Modeling the Environment Looking around the studio and the model, we saw that there were several elements to investigate.

To make sure the sunlight was appropriate and reflected real life measurements, we oriented the model to True North and modified the date. We then confirmed the accuracy of the visual light transmittance (VLT) of the glazing. VLT is the percentage of light that passes through the glass.3 We checked the building’s VLT by measuring the

light levels in front of and in back of the glass door at front of the building. The measured VLT of our glass was larger than we had previously thought, so we adjusted the glass in the digital model, which improved the accuracy of the analysis. Although this helped achieve the measured values around the windows, some values deviated from real measurements.

The next step was to adjust the solar reflectance (SR) values of the materials in the studio. SR is the ability of a surface to reflect sunlight.4 Higher SR values would spread any present light, potentially making the studio feel brighter. There was some approximation when finding SR values because most values in the literature are for roof materials like asphalt, cement, and ceramic shingles.

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Another important part of the setup was establishing

were reasonable, we used the manufacturers’

the correct light sources beyond sunlight. We were

information about the lights (i.e., total lumen output,

able to model the existing conditions by tracking

directional distribution, and the angle of the spread

down information about the existing luminaires and

of light) to estimate the footcandles at desk height

adding or correcting their photometric files. We then

(see diagram (a)). Further, we changed the spacing,

found and modified Revit light families to model

height, and photometric files of the luminaires to

the proposed light configurations. Some of these

troubleshoot and see if the model was responding

families from manufacturers were not displaying

in a logical way. With all of this investigation, we

properly in the model, and the analysis results did

also checked against common sense and played

not match our intuition, potentially necessitating

with real lights—like a desk task lamp at different

adjustments. As a check to see if analysis results

heights—for comparison.

Using the angle of spread (α in diagram; see photometric graph (b)) and the height h of the light off of the desk surface, we determined radius r, which we then used to calculate the area A of light shining on the desk. (α is rarely ever given by the manufacturer, so we used a couple values for conservative and estimates.) Luminance, in imperial footcandles or metric lux, is then the lumens per unit area.

This photometric graph uses polar coordinates to show a luminaire’s distribution of intensity. The distance from the center does not correspond to physical distance but rather luminous intensity. For example, this luminaire’s highest intensity is about 5° away from the vertical. In addition, this graph can indicate the widest spread of light, which we used as α in my calculation of footcandles.

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Results Ultimately, the simulation results were reasonably close to real measurements from the studio (a subset of samples is shown). Many regions of the simulation were within as little as one footcandle of actual values. However, some areas like the windows deviated from reality at different times of

day. Inaccuracies could be due to factors including slight cloud cover and inconsistencies in the meter during measurements and imperfect modeling of the digital environment (i.e., not accounting for items on the desks and window sills). Of course, further tweaking would result in even higher accuracy.

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After going through the validation process, we could run the analyses confidently with Insight. We tested all the ceiling-luminaire combinations at four times of day using a date close to our real life measurements.

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Conclusions Using complementary components in the investigation, we helped validate the efficacy of a simulation tool while also exploring potential improvements to our studio lighting. We constructed a fairly accurate simulation of our office environment by taking into account model geometry, materiality (glazing VLT, material SR values), and light sources (placement, fixtures, photometry, sun direction and date/time). We checked the accuracy of the modeled existing lights and the daylight component by taking real life measurements, and we checked the modeled proposed lights by calculating the expected footcandles at desk height.

These methods allowed us to forecast the look and performance of our options so that we can make informed design and business decisions. For example, putting 3 direct/indirect floor lamps along the spine of each cluster of desks would provide

ample light on the work surface but not enough beyond those area. They would act as high contrast task lighting instead of more uniform ambient lighting. A linear light system would be more invasive and expensive but might create more effective uniform lighting. Out of these proposed options, this last design (with white acoustical panels) would provide the most optimal conditions for our studio in terms of light and sound.

There is a larger point about simulation in general: models are models. Simplifications of reality let us manipulate variables, and models always deviate from real life systems somehow. The more you tweak the model, the higher the accuracy and complexity. We found that exploring the nuances of simulation could form a more complete picture of an environment, helping to inform design.

References 1. Autodesk. (2017). Insight Lighting Analysis Help. Retrieved from https://forums.autodesk.com/autodesk/ attachments/autodesk/19/1006/2/insight-lighting-analysis-help.pdf 2. Recommended Practice for Office Lighting (RP-1-12). (2012). New York, NY: Illuminating Engineering Society of North America.

3. Excellence in Design for Greater Efficiency. (n.d.). EDGE User Guide for All Building Types Version 2.1.

Retrieved from https://www.edgebuildings.com/edge-user-guide-for-all-building-types-version-2-1/ 4. United States Green Building Council. (n.d.). Solar reflectance index (SRI). Retrieved from https://www. usgbc.org/glossary/term/5590

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