What is the impact of operable glazing fraction on thermal comfort and natural ventilation potential?

PROJECT INFORMATION

Graphic Name:  What is the impact of operable glazing fraction on thermal comfort and natural ventilation potential?

Submitted by: Carl Sterner

Firm Name: Sefaira

Other contributors or acknowledgements (optional) 

What tools did you use to create the graphic?

  • Sefaira

  • Adobe Photoshop

  • SketchUp

What kind of graphic is this? Scatter Plot

Primary Inputs: Building geometry (zoned) with glazing; location (weather file); envelope properties, internal conditions, and HVAC parameters.

Primary Outputs: Comfort: % occupied hours within setpoint range (dry bulb temperature). Free area: the ratio of operable window area to floor area for each zone, measured against a target of 5%.

GRAPHIC INFORMATION

What are we looking at?

The graphic is showing two pieces of data relevant for determining the optimal amount of operable glazing for natural ventilation. The first chart (on the left) shows the impact of increasing operable glazing on predicted thermal comfort (the percent of occupied hours with dry bulb temperatures within setpoints). Thermal comfort improves until approximately 75% of glazing is operable, and tops out at 72% of occupied hours being comfortable. The second graphic (on the right) shows the current design’s “free area” -- the ratio of operable window area to floor area for each zone. A free area of 5% is a typical target value for naturally ventilated buildings, and has been codified in standards such as BREEAM in the UK and Title 24 in California. This graphic shows that a number of the building’s zones fail to meet this prescriptive criteria as currently designed. Taken together, the graphics indicate that more operable glazing is needed in many of the zones in order to provide good natural ventilation.

How did you make the graphic?

  1. Modeled building geometry in SketchUp

  2. Uploaded the model to the Sefaira web application

  3. Set up the various simulations (envelope, internal conditions, and HVAC parameters)

  4. Ran a Response Curve for Operable Glazing %, looking at the impact on Thermal Comfort. Exported the resulting graphic.

  5. Ran a Free Area assessment, with a target of 5% free area. Exported the resulting graphic.

  6. Combined the two graphics in Photoshop

What specific investigation questions led to the production of this graphic?

  • Is there enough operable window area in each zone to provide good natural ventilation?

How does this graphic fit into the larger design investigations and what did you learn from producing the graphic?

This graphic was combined with other analyses related to the window area, related to daylighting and solar gain. The purpose of these combined investigations was to evaluate whether the glazing strategy and facade design was effective from energy, daylight, and natural ventilation perspectives. The initial glazing ratios were fairly conservative, and the analyses showed that the design would benefit from more glazing in many of the zones, for both natural ventilation and daylighting.

What was successful and/or unique about the graphic in how it communicates information?

The graphic summarizes and clearly presents fairly complex analysis, making the results actionable. It is easy to see how operable glazing affects comfort, and where the problem areas are in the existing design.

What would you have done differently with the graphic if you had more time/fee?

More clearly connected to two graphs, perhaps by finding a way to put them both in terms of absolute glazing area. The Response Curve is currently terms of % of glazing that is operable, while the Free Area chart is currently based on operable glazing area. This makes it difficult to clearly relate the two.

What is the impact of building massing on annual energy end uses and heat gains & losses?

PROJECT INFORMATION

Graphic Name: What is the impact of building massing on annual energy end uses and heat gains & losses? 

Submitted by: Carl Sterner

Firm Name: Sefaira

Other contributors or acknowledgements (optional) 

What tools did you use to create the graphic?

  • Sefaira

  • Excel

  • Adobe Photoshop

  • SketchUp

What kind of graphic is this? Bar chart

Primary Inputs: Building geometry, and location- and building-use-specific assumptions related to building envelope (utilizing prescriptive values from ASHRAE Std. 90.1) and mechanical systems (utilizing system templates in Sefaira).

Primary Outputs:

  1. Annual energy end use breakdown, normalized per square foot (kWh/ft2/yr)

  2. Sources of heat gain and heat loss, shown as a % of total heat gains and total heat losses (rather than in BTUs)

GRAPHIC INFORMATION

What are we looking at?

The graphic is designed to assess the relative performance of the three massing options, and to provide enough information to help the design team come up with possible strategies for improvement. The bars on the left show energy end uses, normalized per square foot to facilitate quick comparison. For example, one can quickly see that the third option has the highest heating energy use per square foot among the three designs.

On the right are two bars showing annual sources of Heat Gains and Heat Losses, which shed additional light on the heating and cooling end uses. For example, the third option’s “Heat Losses” bar reveals much higher conduction losses through walls than the other options. Because the envelope properties are held constant in this analysis, this difference is due to the greater wall area (higher surface-area-to-volume ratio) of this design compared to the others.

How did you make the graphic?

  1. Created massings in SketchUp and performed energy analysis using Sefaira.

  2. Exported perspective images from SketchUp (without glazing, in order to maintain focus on massing and not facade design).

  3. Logged results in Excel, including total energy end uses and annual heat gains and heat losses.

  4. Normalized the results based on the floor area of each massing.

  5. Created graphs in Excel.

  6. Combined the graphs and model images in Photoshop, added a gray background, and adjusted text and alignment.

What specific investigation questions led to the production of this graphic?

  • Which design option performs best, and why?

  • What is driving the energy use of each design option?

  • What is driving the heating and cooling loads of each design option?

  • What strategies could improve the performance of each design option?

How does this graphic fit into the larger design investigations and what did you learn from producing the graphic?

This graphic is a very early-stage analysis. The most important learning is where to focus moving forward -- in this case, on plug loads, glazing U-factor, and wall R-value. The graphic is designed to generate questions and hypotheses -- for instance, “How high would the wall R-value have to be in Option 3 for it to perform as well as Option 2?” These questions are the logical next steps for subsequent analyses..

What was successful and/or unique about the graphic in how it communicates information?

Analysis alone rarely determine a design’s direction. Instead, such analyses are successful if they provide insight on why a design performs the way it does, and what can be done to improve that performance. This graphic sought to provide just the right information to inform decision-making, presented as clearly as possible. We avoided pie charts, as these are more difficult to compare. We used common-sense colors (e.g. red for heating, blue for cooling), and kept them consistent across all charts (e.g. lighting and equipment are the same in both the “end uses” and “heat gains” charts. The result is legible, aesthetically compelling, and above all useful for quickly assessing a design, understanding the factors affecting performance, and generating clear, actionable hypotheses that can be tested with further analysis.

What would you have done differently with the graphic if you had more time/fee?

Experimented more with the color palette, and with alternate compositions for heat gains and losses.

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What is the impact of window-to-wall ratio on Energy Use Intensity (kBTU/ft2/yr)?

PROJECT INFORMATION

Graphic Name: What is the impact of window-to-wall ratio on Energy Use Intensity (kBTU/ft2/yr)?

Submitted by: Carl Sterner

Firm Name: Sefaira

Other contributors or acknowledgements (optional) 

What tools did you use to create the graphic?

  • Sefaira

  • Adobe Illustrator

  • SketchUp

What kind of graphic is this? Scatter Plot

Primary Inputs: Building geometry, location, and location- and building-use-specific assumptions related to building envelope (utilizing prescriptive values from ASHRAE Std. 90.1) and mechanical systems (utilizing system templates in Sefaira).

Primary Outputs: Energy Use Intensity in kBTU/sf/yr

GRAPHIC INFORMATION

What are we looking at?

This graphic shows how the optimum southern window-to-wall ratio (WWR) for a building changes as other elements of the design change--illustrating that WWR cannot be optimized in isolation, or sized based upon generic rules of thumb. Each row illustrates an optimum south WWR given a specific envelope and mechanical system design, and shows whether the calculated optimum aligns with the range described by a prescriptive rule of thumb (illustrated as a shaded bar on the sensitivity graph). The optimum WWR changes dramatically based upon the properties of the envelope and mechanical systems, ranging from 0% to 65%.

How did you make the graphic?

  1. Modeled building geometry in SketchUp

  2. Uploaded the model to the Sefaira web application

  3. Set up the various simulations (envelope, internal conditions, and HVAC parameters)

  4. For each scenario, a ran a Response Curve to find the optimum South Window-to-Wall ratio looking at the impact on EUI. Exported the resulting graphic.

  5. Used SketchUp to illustrate the optimum Window-to-Wall ratio for each scenario, and exported a high-resolution image of each.

  6. Combined the model image and Response Curve image in Illustrator, adding linework and descriptive text.

What specific investigation questions led to the production of this graphic?

  • What is the optimum south window-to-wall ratio for this design?

  • How do changes to the building envelope and mechanical systems affect the optimum?

  • How accurate are rules of thumb regarding WWR?

How does this graphic fit into the larger design investigations and what did you learn from producing the graphic?

The major takeaway was that WWR cannot be optimized in isolation from the rest of the design. While we knew this in theory, the magnitude of the variation was still startling. It was particularly interesting to see the difference between the option that used “Passive House windows” (U-0.15) and the full “Passive House” option that included high insulation, high air-tightness, and high-efficiency mechanical systems with energy recovery ventilation. The full Passive House design reduced heating loads to such an extent that the design did not benefit from as much solar gain, resulting in a small optimum WWR. This exercise reinforced the need for continual stimulation throughout the process to ensure the design stays on track as the design evolves.

What was successful and/or unique about the graphic in how it communicates information?

The image graphically communicates analysis results, which makes the variation in window-to-wall ratio immediately apparent. It illustrates how changes to inputs create wide variation in outputs, and that rules of thumb cannot be relied upon for optimum results.

What would you have done differently with the graphic if you had more time/fee?

The inputs for each scenario are summarized on the right-hand side of the graphic. I would have liked to better clarify inputs vs. outputs, and perhaps find a way to represent the inputs graphically through iconography or sparkline graphics, so viewers can better understand what was changing between the various scenarios.

What is the impact of orientation and WWR on the energy use?

PROJECT INFORMATION

Graphic Name:  What is the impact of orientation and WWR on the energy use?

Submitted by:

Firm Name:

Other contributors or acknowledgements (optional)

What tools did you use to create the graphic?

  • Sefaira

  • Excel

What kind of graphic is this?

Primary Inputs: Energy use comparison of higher glazing area with 40% WWR

Primary Outputs: Percentage increase in energy use

GRAPHIC INFORMATION

What are we looking at?

The graphic compares 2 orientations with different WWRs for the building. The baseline for both orientations is 40% WWR. The graphic compares the effect of increasing the WWR between 50% to 60% for all the facades. Given the higher glazing area in the 'triangular section' Facade D moves the needle on energy use in Orientation 1. However reorienting the building may help in reducing energy use while maintaining the same glazing area in the 'triangular section'.

How did you make the graphic?

Exported all the cases to excel and post processed it

What specific investigation questions led to the production of this graphic?

1) What is the effect of the orientation, given the higher glazing area n certain facades?

2) What is the effect of reducing the glazing area?

3) What is the effect of reorienting the building

4) What is the effect of various combinations of WWR with different orientations?

How does this graphic fit into the larger design investigations and what did you learn from producing the graphic?

Optimizing the facade, interior layout, circulation and other aspects of the architectural design would be affected by the orientation and the WWR.

What was successful and/or unique about the graphic in how it communicates information?

Stacked graph with 2 different scenarios quickly says which is the ' problematic facade in each of the cases.

What would you have done differently with the graphic if you had more time/fee?

Daylight or glare anaysis

What's the impact of different skylight geometries on daylight autonomy?

PROJECT INFORMATION

Graphic Name: What's the impact of different skylight geometries on daylight autonomy?

Submitted by: Andrew Corney, Product Director

Firm Name: Sefaira

What tools did you use to create the graphic? Sefaira

What kind of graphic is this? Graphic Matrix

GRAPHIC INFORMATION

What are we looking at?

This is a visual showing 4 roof light options for a medical office building project. It compares different strategies - applying simple roof lights, clerestory glazing, both or neither. It aims to use colour to communicate which parts of the floor plate benefit from the different options.

How did you make the graphic?

I took 4 screen captures from 4 analysis runs in the Sefaira plugin and combined them using powerpoint.

What specific investigation questions led to the production of this graphic?

How well do these daylight options improve the amount of daylight entering the top floor of the building?

How does this graphic fit into the larger design investigations and what did you learn from producing the graphic?

This graphic was developed for a competition.

One goal was to introduce as much daylight as possible into the building and communicate how the design solution was able to do that. We needed to identify the problem first (deep floor plate with partitions) then a solution that could solve it.

Four different roof light and energy options were being considered:

  • No Skylights - this was the base case and is the top right image. The analysis confirms that there is low daylight on the top floor. Including this image in the graphic helps baseline performance for the reader.
  • Clerestory windows
  • Flat Skylights
  • Both Clerestory windows and flat skylights

The graphic helped to identify how well the options compared in terms of achieving the goal of more daylight. It did this through:

  • Effective side-by-side comparison of results
  • Glanceable detail from a distance with extra detail provided close up

Looking at the graphic, it becomes clear that for most of the floor plate, the skylights were far more effective at bringing in natural light than the clerestory windows. The diagram helped the team hone in on a solution that combined skylights and a subset of clerestory windows to achieve this part of the project goal. It was presented in tandem with energy results.

What was successful and/or unique about the graphic in how it communicates information?

This graphic tool very little time to generate. It's a standard Sefaira output that I was able to make in about 10 minutes with the SketchUp model as a starting Point. It's great because for something that's very quick to generate, it clearly quantifies visually the differences between the options for a client who is not interested in numbers.

The graphic primarily uses colour to communicate the difference between options. This makes the 4 options glance-able for a lay person or for a person who is not close up to the diagram (eg in a presentation).

There is a scale provided on the image as well and importantly all images are shown at the same lighting scale to ensure a fair comparison between each.

I believe this graphic is successful because it does most of the important work for the reader:

  • Consistent scale and viewpoint
  • Intuitive use of colour to communicate performance
  • Key focus on a single piece of information (There is not a whole lot of other information to confuse the reader.)
  • Compares options fairly.

What would you have done differently with the graphic if you had more time/fee?

The graphic is great as is and we included more in the original study to communicate the impact on energy use as well.  Showing the analysis in tandem with external views of the model is always a good way to reinforce the bigger story and overall picture for the 4 different solutions.

What's the impact of facade design on thermal comfort?

PROJECT INFORMATION

Graphic Name: What's the impact of facade design on thermal comfort?

Submitted by: Andrew Corney           

Firm Name: Sefaira

What tools did you use to create the graphic? Sefaira

What kind of graphic is this? Floor Plan Heat Map

GRAPHIC INFORMATION

What are we looking at?

Provides a floor plan view of the building, coloured with information per zone describing whether they achieve a thermal comfort target.

The comfort target is shown in the criteria above. The user can quickly hone in on the zones that are failing one floor at a time.

By presenting the results in plan view, with the rooms shown, it presents results visually in a way that an audience familiar with the floor plate layout can process easily.

How did you make the graphic?

Sefaira makes these outputs automatically with any analysis run including thermal comfort.

What specific investigation questions led to the production of this graphic?

This graphic tries to help the designer understand “which zones are having the most trouble in my building” and then communicate that as needed to a wider team.

Traditionally consultants have to do this by:

  • Declaring for themselves what they expect the worst zone to be based on experience
  • Building thermal models of the zones that are declared as likely to be the worst

Relying on the trust between them on the design team to use that to steer design attention on those spaces.

This workflow is tedious and also in part risky, especially if the analyst is inexperienced and the reviewer is not privy to all the envelope details on a project.

The goal here is to help a designer hone in quickly on the spaces they should worry about first, while providing an easy way of proving that declaration to the rest of the design team.

How does this graphic fit into the larger design investigations and what did you learn from producing the graphic?

The graphic helps with facade design by identifying where thermal comfort goals are being missed. They should be incorporated into studies looking into peak loads, energy and daylight because all of these issues are affected by the envelope design.

The learning is that thermal comfort can be used as a design tool and that it can provide very helpful insight into how successfully a design is working.

What was successful and/or unique about the graphic in how it communicates information?

Thermal comfort analysis is typically time consuming and hard. It therefore requires a lot of preparation before analysis can be useful.

This graphic is helpful because it makes it really easy to see which spaces are struggling to meet the thermal comfort goals. It reduces the effort needed to hone in on the key spaces requiring attention and serves to prove visually the design team that those spaces are worse.

What would you have done differently with the graphic if you had more time/fee?

We ended up adding a gradient option to this graphic. The reason was so that people could identify which zones were just failing vs those that were the worst on the floor plate.

We’re interested in exploring how to convert this graphic into a comparative analysis, where a project has a series of design options and wants to compare PMV for the worst zone against those options and somehow communicate it on the floor plan.