Thursday, April 17, 2014

Green building design with Energy3D: How big should south-facing windows be?

Many people know that south-facing windows can help to heat a house in the winter because they let a lot of sunlight in. Exactly how much of the south-facing wall should we allocate to windows? What are the downsides? How can we avoid them? Our Energy3D software allows students to explore the problems and find the solutions.

Figure 1


Suppose we have a simple house like the one shown in Figure 1 and we are in the Boston area. Energy3D supports students to try a design choice, run a simulation, collect the data, analyze the result, and evaluate the solution -- all in real time as is shown in the video in this post. Energy3D's powerful simulation and analysis tools provide instantaneous feedback to students so that their design processes can be guided and informed by the scientific and engineering principles built in the software. Let's use the investigation of south-facing windows described above as an example.


Figure 2 (Excel graph)
Suppose a student follows the design trajectory as shown in Figure 1. A challenge is to keep the yearly energy cost needed to maintain the temperature of the house at 20℃ to be as low as possible. The student begins with adding a small window to the south side of the house. By running the seasonal energy analysis tool in Energy3D, she immediately discovers that, by adding a small window, she can cut the energy cost a bit. Then she enlarges the window and finds that more energy can be saved. So she goes on to increase the size of the window. However, she finds that, at some point, larger windows on the south side start to cost more energy. After she adds two large windows, the energy cost increases over 15%, compared with the case of no window at all. Figure 2 shows the energy cost, broken down to heater and AC, as a function of the window area. That doesn't quite make sense to her. So she has to stop and think about why.
Figure 3 (Energy3D graph)


The trend in Figure 2 suggests that, with the enlargement of windows on the south side, the cooling cost continues to rise while the heating cost levels off. A monthly breakdown in Figure 3 reveals this trend more clearly. As shown by the golden dashed line in Figure 2, the solar heating through the windows increases rapidly when their total area gets enlarged.

Figure 4 (Energy3D graph)
Figure 5 (Energy3D graph)
If she wants to keep the large window area in the south side (for natural lighting and sanity of the occupants!), she has to reduce the solar heating effect through the windows in the summer. One way to do this is to plant tall deciduous trees in front of the windows as shown in Figure 1. The trees provide shading for the windows in the summer but let sunlight shine through to the windows in the winter (in Energy3D, deciduous trees have leaves from May 1st to November 30th). Figure 4 shows the effect of the two deciduous trees on the solar gain through the two south-facing windows. From the graph, she can see that the trees cut down the solar heating in the summer. As a result, the AC cost is reduced, as shown in Figure 5, whereas the heating cost is almost unchanged.

She concludes that, with the trees planted to the south of the house, the net energy cost over a year can be decreased to lower than the case of no window at all, providing an acceptable solution that takes care of view, lighting, and landscaping.

The Energy3D graphs in this blog post show that students can keep the results of previous runs (the curve of each run is labeled by a number) and superimpose new data on top of them. As the data view can get quite complex, Energy3D provides options to turn on/off data types and runs. The embedded video shows how those features work for visualizing and analyzing the simulation results.

PS: Some readers may notice that our calculations predict higher AC cost in September than in August or July. This is because when those calculations were done, the house had no window on the east or west side. Adding windows to those sides, the AC cost will peak around July or August -- even when the trees are not present.

Sunday, April 6, 2014

Building performance analyses in Energy3D

Energy3D (Tree image credit: SketchUp Warehouse and Ethan McElroy)
A zero-energy building is a building with zero net energy consumption over a year. In other words, the total amount of energy used by the building on an annual basis is equal to or even less than the amount of renewable energy it produces through solar panels or wind turbines. A building that produces more renewable energy than it consumes over the course of a year is sometimes also called an energy-plus building. Highly energy-efficient buildings hold a crucial key to a sustainable future.


One of the goals of our Energy3D software is to provide a powerful software environment that students can use to learn about how to build a sustainable world (or understand what it takes to build such a world). Energy3D is unique because it is based on computational building physics, done in real time to produce interesting heat map visualization resembling infrared thermography. The connections to basic science concepts such as heat and temperature make the tool widely applicable in schools. Furthermore, at a time when teachers are required by the new science standards to teach basic engineering concepts and skills in classrooms, this tool may be even more relevant and useful. The easy-to-use user interface enables students to rapidly sketch up buildings of various shapes, creating a deep design space that provides many opportunities of exploration, inquiry, and learning.


In the latest version of Energy3D (Version 3.0), students can compute the energy gains, losses, and usages of a building over the course of a year. These data can be used to analyze the energy performance of the building under design. These results can help students decide their next steps in a complex design project. Without these simulation data to rationalize design choices, students' design processes would be speculative or random.

A complex engineering design project usually has many elements and variables. Supporting students to investigate each individual element or variable is key to helping them develop an understanding of the related concept. Situating this investigation in a design project enables students to explore the role of each concept on system performance. With the analytic tools in Energy3D, students can pick an individual building component such as a window or a solar panel and then analyze its energy performance. This kind of analysis can help students determine, for example, where a solar panel should be installed and which direction it should face. The video in this post shows how these analytic tools in Energy3D work.

Friday, March 28, 2014

Spring is here, let there be trees!

Trees in Energy3D.
Trees around a house not only add natural beauty but also increase energy efficiency. Deciduous trees to the south of a house let sunlight shine into the house through south-facing windows in the winter while blocking sunlight in the summer, thus providing a simple but effective solution that attains both passive heating and passive cooling using the trees' shedding cycles. Trees to the west and east of a house can also create significant shading to help keep the house cool in the summer. All together, a well-planed landscape can reduce the temperature of a house in a hot day by up to 20°C.

The tree to the south side shades the house in the summer.
With the latest version of Energy3D, students can add trees in designs. As shown in the second image in this blog post, the Solar Irradiation Simulator in Energy3D can visualize how trees shade the house and provide passive cooling in the summer.

The Solar Irradiation Simulator also provides numeric results to help students make design decisions. The calculated data show that the tree to the south of the house is able to reduce the sunlight shined through the window on the first floor that is closest to it by almost 90%. Students can do this easily by adding and removing the tree, re-run the simulation, and then compare the numbers. They will be able to add trees of different heights and types (deciduous or evergreen). There will be a lot of design variables that students can choose and test.

A design challenge is to combine windows, solar panels, and trees to reduce the yearly cost of a building to nearly zero or even negative (meaning that the owner of the house actually makes money by giving unused energy produced by the solar panels to the utility company). This is no longer just a possibility -- it has been a reality, even in a northern state like Massachusetts!

Monday, March 24, 2014

Learning analytics is the "crystallography" for educational research

To celebrate 100 years of dazzling history of crystallography, the year of 2014 has been declared by UNESCO as the International Year of Crystallography. To this date, 29 Nobel Prizes have been awarded to scientific achievements related to crystallography. On March 7th, the Science Magazine honored crystallographers with a special issue.

Why is crystallography such a big deal? Because it enables scientists to "see" atoms and molecules and discover the molecular structures of substances. One of the most famous examples is the discovery of the DNA helix by Rosalind Franklin in 1952, followed by Crick, Watson, and Wilkins' double helix model. Enough ink has been spilled on the importance of this discovery.

Science fundamentally relies on techniques such as crystallography for detecting and visualizing invisible things. Educational research needs this kind of techniques, too, to decode students' minds that are opaque to researchers. Up to this point, educational researchers depend on methods such as pre/post-tests, observations, and interviews. But these traditional methods are either insufficient or inefficient for measuring learning in complex processes such as scientific inquiry and engineering design. To achieve a level of truly "no child left behind," we will need to develop a research technique that can monitor every student for every minute in the classroom.

Such a technique has to be based on an integrated informatics system that can engage students with meaningful learning tasks, tease out what are in their minds, and capture every bit of information that may be indicative of learning. This involves development in all areas of learning sciences, including technology, curriculum, pedagogy, and assessment. Eventually, what we have is a comprehensive set of data through which we will sift to find patterns of learning or evaluate the effectiveness of an intervention.

The whole process is not unlike crystallography. At the end, it is the learning analytics that concludes the research. Today we are seeing a lot of learner data, but we probably have no idea what they actually mean. We can either say there is no significance in those data and shrug off, or we can try to figure out the right kind of data analytics to decipher them. Which attitude to choose probably depends on which universe we live in. But the history of crystallography can give us a clue. It was Max von Laue who created the first X-ray diffraction pattern in 1912. He couldn't interpret it, however. It wasn't until William Henry Bragg and William Lawrence Bragg's groundbreaking work later in the same year that scientists became able to infer molecular structures from those patterns. In educational research, the equivalent of this is the learning analytics -- a critical piece that will give data meaning.

For more information, read my new article "Visualizing Student Learning."