New features in CODAP

Our Common Online Data Analysis Platform (CODAP) software provides an easy-to-use web-based data analysis tool, geared toward middle and high school students, and aimed at teachers and curriculum developers. CODAP is already full of amazing features. We’re excited to announce several new features! Continue reading

Importing and analyzing models created by other CAD software in Energy3D

Fig. 1: Solarize a COLLADA model in Energy3D
Fig.2: A house imported from SketchUp's 3D Warehouse
Energy3D is a relatively simple CAD tool that specializes in building simulation and solar simulation. Its current support for architectural design is fine, but it has limitations. It is never our intent to reinvent the wheel and come up with yet another CAD tool for architecture design. Our primary interest is in physics modeling, artificial intelligence, and computational design. Many users have asked if we can import models created in other CAD software such as SketchUp and then analyze them in Energy3D.

Fig. 3: A house imported from SketchUp's 3D Warehouse
I started this work yesterday and completed the first step today. Energy3D can now import any COLLADA models (*.dae files) on top of a foundation. The first step was the inclusion of the mesh polygons in the calculation of solar radiation. The polygons should be able to cast shadow on any object existing in an Energy3D model. This means that, if you have a 3D model of a neighboring building to the target building, you can import it into Energy3D so that it can be taken into consideration when you design solar solutions for your target. Once you import a structure, you can always translate and rotate it in any way you want by dragging its foundation, like any existing class of object in Energy3D.

Fig. 4: A house at night in Energy3D
Due to some math difficulties, I haven't figured out how to generate a solar radiation heat map overlaid onto the external surfaces of an imported structure that are exposed to the sun. This is going to be a compute-intensive task, I think. But there is a shortcut -- we can add Energy3D's solar panels to the roof of an imported building (Figure 1). In this way, we only have to calculate for these solar panels and all the analytic capabilities of Energy3D apply to them. And we can get pretty good results pretty quickly.

Fig. 5: A 3D tree imported from SketchUp's 3D Warehouse
Figures 2-4 show more examples of how houses designed with SketchUp look like in Energy3D after they are imported. This interoperability makes it possible for architects to export their work to Energy3D to take advantage of its capabilities of energy performance analysis.

Being able to import any structure into Energy3D also allows us to use more accurate models for landscapes. For instance, we can use a real 3D tree model that has detailed leaves and limbs, instead of a rough approximation (Figure 5). Of course, using a more realistic 3D model of a tree that has tens of thousands of polygons slows down the graphic rendering and simulation analysis. But if you can afford to wait for the simulation to complete, Energy3D will eventually get the results for you.

Why is Israel building the world’s tallest solar tower?

Fig. 1: Something tall in Negev desert (Credit: Inhabitat)
The Ashalim solar project (Figure 1) in the Negev desert of Israel will reportedly power 130,000 homes when it is completed in 2018. This large-scale project boasts the world’s tallest solar tower -- at 250 meters (820 feet), it is regarded by many as a symbol of Israel’s ambition in renewable energy.

Solar thermal power and photovoltaic solar power are two main methods of generating electricity from the sun that are somewhat complementary to each other. Solar tower technology is an implementation of solar thermal power that uses thousands of mirrors to focus sunlight on the top of a tower, producing intense heat that vaporizes water to spin a turbine and generate electricity. The physics principle is the same as a solar cooker that you have probably made back in high school.

Why does the Ashalim solar tower have to be so tall?

Surrounding the tower are approximately 50,000 mirrors that all reflect sun beams to the top of the tower. For this many mirrors to "see" the tower, it has to be tall. This is easy to understand with the following metaphor: If you are speaking to a large, packed crowd in a square, you had better stand high so that the whole audience can see you. If there are children in the audience, you want to stand even higher so that they can see you as well. The adults in this analogy represent the upper parts of mirrors whereas the children the lower parts. If the lower parts cannot reflect sunlight to the tower, the efficiency of the mirrors will be halved.

Fig. 2: Visualizing the effect of tower height
An alternative solution for the children in the crowd to see the speaker is to have everyone stay further away from the speaker (assuming that they can hear well) -- this is just simple trigonometry. Larger distances among people, however, mean that the square with a fixed area can accommodate less people. In the case of the solar power tower, this means that the use of the land will not be efficient. And land, even in a desert, is precious in countries like Israel. This is why engineers chose to increase the height of tower and ended up constructing the costly tall tower as a trade-off for expensive land.

Fig. 3: Daily output graphs of towers of different heights
But how tall is tall enough?

Fig. 4: Energy output vs. tower height
This depends on a lot of things such as the mirror size and field layout. The analysis is complicated and reflects the nature of engineering. With our Energy3D software, however, complicated analyses such as this are made so easy that even high school students can do. Not only does Energy3D provide easy-to-use 3D graphical interfaces never seen in the design of concentrated solar power, but it also provides stunning "eye candy" visualizations that clearly spell out the science and engineering principles in design time. To illustrate my points, I set up a solar power tower, copied and pasted to create an array of mirrors, linked the heliostats with the tower, and copied and pasted again to create another tower and another array of mirrors with identical properties. None of these tasks require complicated scripts or things like that; all they take are just some mouse clicks and typing. Then, I made the height of the second tower twice as tall as the first one and run a simulation. A few seconds later, Energy3D showed me a nice visualization (Figure 2). With only a few more mouse clicks, I generated a graph that compares the daily outputs of towers of different heights (Figure 3) and collected a series of data that shows the relationship between the energy output and the tower height (Figure 4). The graph suggests that the gain from raising the tower slows down after certain height. Engineers will have to decide where to stop by considering other factors, such as cost, stability, etc.

Note that, the results of the solar power tower simulations in the current version of Energy3D, unlike their photovoltaic counterparts, can only be taken qualitatively. We are yet to build a heat transfer model that simulates the thermal storage and discharge accurately. This task is scheduled to be completed in the first half of this year. By that time, you will have a reliable prediction software tool for designing concentrated solar power plants.

Modeling the six MW solar farm at the Palmer Metropolitan Airfield in Massachusetts

Fig. 1 Aerial view of PMA (courtesy of Borrego Solar)
Fig. 2 The polygon tool for drawing land parcels
The Palmer Metropolitan Airfield (PMA) solar farm (Figure 1) is the first and, at 6 MW, the largest Massachusetts Department of Energy Resources qualified brownfield project under the SREC II solar energy incentive program. The solar farm consists of 20,997 solar panels of three different types (5,161 Suniva, 13,851 Yingli, and 1,985 Canadian Solar), connected by 74 SMA string inverters. It is expected to produce an estimate of 8.5 GWh annually, enough to power 1,000 homes and offset 4,000 tons of carbon dioxide every year -- according to this news source. The PMA solar farm was engineered by our partner, Borrego Solar, the third largest company in the commercial solar market in the US.

Fig. 3 The Automatic Layout Wizard for solar rack arrays
The PMA solar farm is the first test of Energy3D's capacity of seriously designing utility-scale (greater than 1 or 5 MW, depending on your point of view) photovoltaic solar power plants. This design capacity was enabled by three critical new features that were added only recently to Energy3D (V6.2.2): 1) A tool to draw polygons that represent parcels of land for solar farms; 2) a tool to automatically generate solar panel and rack array layouts within selected parcels of land; and 3) accelerated graphical user interface and numerical simulation to handle 10,000+ solar panels (which I have blogged earlier this month).

Fig. 4 The result of the Automatic Layout Wizard
Since Energy3D can import an Earth view image from Google Maps, you can directly draw polygons on top of the image to trace the parcel of land for designing your solar farm (Figure 2). Note that if you have multiple parcels of land that are separate from one another, you may have to use multiple foundations in Energy3D as each foundation is allowed to have one and only one polygon for the time being.

Fig. 5 Heat map representations of output in four seasons.
Fig. 6 Annual yield vs. tilt angle
As soon as you are all set with your land plans, you can use the Automatic Layout Wizard of Energy3D to add solar panel rack arrays (Figure 3). This wizard will automatically generate the array layout within the selected land parcel and assign properties to the solar panels based on the parameters of your choice. For instance, you can select how many rows of solar panels you want to have on each rack (I picked four because that is what Google Maps shows about the setting in PMA). Figure 4 shows the result of applying the Automatic Layout Wizard to populate the three subfields of the PMA solar farm.
Fig. 7 Monthly yields vs. tilt angle

After the layout is done, you can always revise the field. You can drag any rack to resize or move it, delete it, copy and paste it, or add a new rack. The Automatic Layout Wizard is not the only way to add solar panel arrays. It is just a super fast way to add thousands of solar panels at once -- without the wizard, it would have been too time-consuming to manually add solar panel racks one by one. The solar panel field is always editable after a layout is applied.

Let's now check how close our model is to reality. The total number of solar panels of our model is 21,064 -- only 67 more than that of the real PMA solar farm (I had no information about the exact types of solar panels deployed in PMA, so I guessed and selected two different sizes 0.99m x 1.65m and 0.99m x 1.96m for different subfields).

In terms of the annual output, Energy3D predicts approximately 9.6 GWh, about 12% higher than the estimated output of 8.5 GWh by Borrego Solar. I currently do not have access to the real operational data, though.

Having created a computer model allows us to experiment with it to study how to optimize the design. For example, we can easily change the tilt angles of the arrays and investigate how the annual yield is affected. Figure 6 shows that a tilt angle close to the latitude (42 degrees) seems to result in the highest overall annual output.

But the total annual output is not necessarily the only criterion. Sometimes, it is necessary for solar companies to consider load balancing to guarantee stable outputs throughout the year (assuming that we want to minimize the use of base load from burning fossil fuels). It is, therefore, interesting to also take a look at the outputs across 12 months of a year. Figure 7 suggests that a smaller tilt angle will produce peak power in the summer, whereas a larger tilt angle will produce peak power in early fall. If the demand of electricity in the summer is higher than that in the fall, it may be more lucrative to position solar panels at a lower tilt angle.

Ten research papers utilizing Energy2D published in the past two years

Screenshots from recent papers that use Energy2D
Energy2D simulation of fire
Energy2D is a multiphysics simulation program that was created from scratch and is still under development (though its progress has slowed down significantly because my priority has been given to its Energy3D cousin). The software was originally intended to be a teaching and learning tool for high school students who are interested in studying engineering. Over the past two years, however, we have seen 10 research papers published in various journals and conferences that involved significant applications of Energy2D as a scientific research tool for modeling natural phenomena and engineering systems. The problems that these researchers simulated range from solar energy, industrial processes, geophysics, and building science. The authors come from universities from all over the world, including top-notch institutions in US, Europe, and China.

Energy2D simulation of thermal bridge
Among them, researchers from Delft University of Technology, Technical University of Darmstadt, and Eindhoven University of Technology wrote in their recent paper about the validity of Energy2D: "The software program Energy2D is used to solve the dynamic Fourier heat transfer equations for the Convective Concrete case. Energy2D is a relatively new program (Xie, 2012) and is not yet widely used as a building performance simulation tool. To gain more confidence in the predictions with Energy2D, an analytical validation study was therefore carried out first, inspired by the approach described in Hensen and Nakhi (1994). Those analytical solutions and the simulation results of the dynamic response to a 20°C temperature step change on the surface of a concrete construction with the following properties were compared for this research." They concluded that "the simulation results never divert from the exact solution more than 0.45°C and it is therefore considered acceptable to further use this model."

The publication of these papers and very positive user feedback suggest that Energy2D seems to have found itself an interesting niche market. Many scientists and engineers are unable to invest a lot of time and money on its complicated commercial counterparts. But they nonetheless need a handy simulation tool that is much more flexible, intuitive, and capable than formulas in books to deal with realistic geometry -- at least in 2D. This is where Energy2D comes into play.

Reaching this milestone is critically important to the free and open-source Energy2D software, whose future will be reliant on community support. Its modest popularity among scientists is a valid demonstration of the broader impact expected by the National Science Foundation that funded its development. One can only imagine that there are many more users who used the software in their workplace but didn't publish. Now that good words about it have spread, we expect the usage to continue and even accelerate. To better support our users, we have added a community forum recently. We also plan to work with Professor Bob Hanson to port the Java code to JavaScript through his SwingJS translator so that the program can run on more devices.

The list of these papers is as follows:
  1. Mahfoud Abderrezek & Mohamed Fathi, Experimental Study of the Dust Effect on Photovoltaic Panels' Energy Yield, Solar Energy, Volume 142, pp 308-320, 2017
  2. Dennis de Witte, Marie L. de Klijn-Chevalerias, Roel C.G.M. Loonen, Jan L.M. Hensen, Ulrich Knaack, & Gregor Zimmermann, Convective Concrete: Additive Manufacturing to Facilitate Activation of Thermal Mass, Journal of Facade Design and Engineering, Volume 5, No. 1, 2017
  3. Javier G. Monroy & Javier Gonzalez-Jimenez, Gas Classification in Motion: An Experimental Analysis, Sensors and Actuators B: Chemical, Volume 240, pp 1205-1215, 2017
  4. Tom Rainforth, Tuan Anh Le, Jan-Willem van de Meent, Michael A. Osborne, & Frank Wood, Bayesian Optimization for Probabilistic Programs, 30th Conference on Neural Information Processing Systems, Barcelona, Spain, 2016
  5. E. Rozos, I. Tsoukalas, & C. Makropoulos, Turning Black into Green: Ecosystem Services from Treated Wastewater, 13th IWA Specialized Conference on Small Water and Wastewater Systems, Athens, Greece, 2016
  6. W. Taylor Shoulders, Richard Locke, & Romain M. Gaume, Elastic Airtight Container for the Compaction of Air-Sensitive Materials, Review of Scientific Instruments, Volume 87, 063908, 2016
  7. Zachary R. Adam, Temperature Oscillations near Natural Nuclear Reactor Cores and the Potential for Prebiotic Oligomer Synthesis, Origins of Life and Evolution of Biospheres, Volume 46, Issue 2, pp 171-187, 2016
  8. Jiarui Chen, Shuyu Qin, Xinglong Wu, & Paul K Chu, Morphology and Pattern Control of Diphenylalanine Self-Assembly via Evaporative Dewetting, ACS Nano, Volume 10, No. 1, pp 832-838, 2016
  9. Atanas Vasilev, Geothermal Evolution of Gas Hydrate Deposits: Bulgarian Exclusive Economic Zone in the Black Sea, Comptes rendus de l‘Académie bulgare des Sciences, Volume 68, No. 9, pp 1135-1144, 2015
  10. Pedro A. Hernández, et al., Magma Emission Rates from Shallow Submarine Eruptions Using Airborne Thermal Imaging, Remote Sensing of Environment, Volume 154, pp 219-225, November 2014

Learning Everywhere taking inspiration from two partners, At-Bristol and Exploradôme

Innovative applications of technology are found virtually everywhere, transforming all kinds of spaces into opportunities for STEM learning that move beyond the walls of classrooms and past schooltime hours. Persistent engagement and interest in meaningful learning activities and practices can spur an enduring pursuit of science.

Our Learning Everywhere initiative is exploring, prototyping, and creating new learning experiences—including exhibits, mobile apps, and user tracking technologies—that connect and coordinate learning across museums and bridge in-school and out-of-school time. To survey new learning spaces and interactive technologies, we visited two of our Learning Everywhere partners, At-Bristol and Exploradôme, as well as other science centers in the London and Paris areas, including the Science Museum of London and the City of Science and Industry at La Villette.

Chad Dorsey and Sherry Hsi at the entrance of At-Bristol Science Center.

Chad Dorsey and Sherry Hsi at the entrance of At-Bristol Science Center.

Donning our bracelets printed with unique barcode IDs at the entrance, we explored the many At-Bristol exhibits, scanning our bracelets to collect and compare our data with data from other visitors. At some stations, we learned how the creators of Wallace and Gromit, from Aardman Animations’ studios also in Bristol, made their great movies before creating our own stop-motion animations. A quick scan of our wrists saved these animations to a website where we could access them later. Other parts of our experience, from scatterplots of our height compared to other visitors to videos of ourselves on slow-motion “startle-cam” added themselves into our electronic portfolio during the visit. We even found ourselves wearing bee wings and performing a waggle dance to mimic bee behaviors in an exhibit about the mysterious lives of bees! This and other digital artifacts from our visit served as opportunities for further conversation and inquiry back home, and as a source of fun for our families. (Needless to say, the bee dance video was a source of great enjoyment, but it will not be showing up publicly on Instagram any time soon!)

At-Bristol Science Center’s animation exhibits area.

At-Bristol Science Center’s animation exhibits area.

Our visit to London coincided with the grand opening of Wonder Lab at the Science Museum of London. Our guide, Dave Patten, Head of New Media there, showed us the spacious, colorful interactive gallery designed to encourage visitors to collaborate, play, and learn from conversation. In another exhibition, Engineer Your Future, teens and young adults use their personal mobile devices in public gallery spaces to design vehicles, then launch and control them on a huge public screen! Other large-screen and combined physical-digital exhibits featured different design-oriented and competitive games on energy, vehicle design, and different engineering careers.

Science Museum of London’s WonderLab the evening before its grand opening.

Science Museum of London’s WonderLab the evening before its grand opening.

The many heads of Dave Patten from the Science Museum of London in a Wonder Lab exhibit.

The many heads of Dave Patten from the Science Museum of London in a Wonder Lab exhibit.

Moving farther south, we visited the Cité des Sciences et de l’Industrie in Paris, where an immense, airy space houses corners with multiple galleries of permanent and temporary exhibitions. Among them, designed areas invite reflection and discussion among school groups or individuals. In a highlight of the visit, François Vescia, Senior International Project Manager at the museum, gave us a tour of their fabrication laboratory, Carrefour Numerique. This public space is a wonderland of design and making, custom created to invite design collaboration and discussions that merge seamlessly into design and construction of physical prototypes and objects. Visitors access materials and machinery from e-textile design, milling machines, 3D printers, and laser and vinyl cutters to turn their visions into reality. Drop-in and scheduled programs and workshops and in-person support are available, and visitors can begin designing projects digitally in the multimedia lab, then move next door to fabricate them.

Chad Dorsey, Francois Vescia, and Sherry Hsi at Parc de la Villette, an area in Paris, known for the Cité des Sciences et de l'Industrie science museum.

Chad Dorsey, Francois Vescia, and Sherry Hsi at Parc de la Villette, an area in Paris, known for the Cité des Sciences et de l’Industrie science museum.

Entrance to the Fab Lab at the City of Sciences and Industry in Paris.

Entrance to the Fab Lab at the City of Sciences and Industry in Paris.

Taking the train to the southern suburbs of Paris, we visited the Exploradôme, where we met Goery Delacote, its founder and a longstanding member of the Concord Consortium Board of Trustees. Goery toured us among the great exhibits packed into the floor of this small museum, where the motto is “Not touching is not allowed!” Playing like kids (and some of us were!), we explored visual perception phenomena, dug holes for water in a version of the AR Sandbox Sherry helped create and worked together to launch six-foot smoke rings that rose to the ceiling.

Goery Delacôte, Sherry Hsi, and Chad Dorsey at the entrance of Exploradome in Vitry-sur-Seine south east of Paris. Colors from the building were selected from colors found around the local neighborhood.

Goery Delacôte, Sherry Hsi, and Chad Dorsey at the entrance of Exploradome in Vitry-sur-Seine south east of Paris. Colors from the building were selected from colors found around the local neighborhood.

The thoughtful curation and orchestration of interactive exhibits throughout our Learning Everywhere tour was inspiring, as was the innovative use of technology to engage visitors and extend museum experiences beyond the visit. As we collate and catalog these experiences and technologies as part of the project work, we look forward to working further with museums and other out-of-school institutions to bridge and extend learning everywhere.

Making smoke rings collaboratively at the Exploradome with Goery Delacôte and Sherry Hsi.

Making smoke rings collaboratively at the Exploradome with Goery Delacôte and Sherry Hsi.

Making virtual lakes by digging in the Augmented Reality Sandbox exhibit at the Exploradome.

Making virtual lakes by digging in the Augmented Reality Sandbox exhibit at the Exploradome.

Exploring optical illusions and visualization puzzles at the Exploradome with Goery Delacôte.

Exploring optical illusions and visualization puzzles at the Exploradome with Goery Delacôte.

Accelerating solar farm design in Energy3D with a new model of solar panel racks

Fig. 1: A solar farm of 5,672 solar panels on 8/16 in Boston
The solar simulation in Energy3D is based on discretizing a solar panel, a reflector, a solar water heater, a window, or any other surface into many small cells (mesh), calculating the solar radiation to the centers of the cells, and then summing the results up to obtain the total energy output. For example, a photovoltaic solar panel can be divided into 6x10 cells (this is also because many residential versions of solar panels are actually designed to have 6x10 solar cells). The simulation runs speedily when we have only a few dozen solar panels such is in the case of rooftop solar systems.

Fig. 2: Simulation of 5,672 solar panels on 8/16 in Boston
Unlike rooftop solar systems, large-scale solar farms typically involve thousands of solar panels (mega utility-scale solar farms may have hundreds of thousands of solar panels). If we use the same discretization method for each panel, the simulation would run very slowly (e.g., the speed drops to 1% when the number of solar panels are 100 times more). This slowdown basically makes Energy3D impractical to use by those who cannot afford to wait such as students in the classroom who need to get the results quickly.

Fig. 3: The result of the accelerated model
Fig. 4: The result of the original model
Luckily, solar panel arrays are often installed on parallel long racks in many solar farms (Figure 1). For such solar panel arrays, a lot of calculations could be spared without compromising the overall accuracy of the simulation too much. This allows us to develop a more efficient model of numeric simulation to do solar radiation calculation and even explore methods that use non-uniform meshes to better account for areas that are more likely to be shaded, such as the lower parts of the solar panel arrays. By implementing this new model, we have succeeded in speeding up the calculation dramatically. For example, the daily solar simulation of a solar farm consisting of more than 5,000 solar panels took about a second on my Surface Book computer (Figure 2 -- in this scene I deliberately added a couple of trees so that you can see the result of shading). With the previous model I would probably have to wait for hours to see the result and the graphics card of my computer would take a very deep breath to render more than 5,000 dynamic textures. This is a huge improvement.

Figures 3 and 4 show a comparison of the simulation results between the new and old models. Quantitatively, the total output of the new model is 93.63 kWh for the selected day of June 22 in Boston, compared with 93.25 kWh from the original model. Qualitatively, the color shading patterns that represent the distribution of solar radiation in the two cases are also similar.

The new rack model supports everything about solar panels. It has a smart user interface that allows the user to draw racks of any size and in any direction -- it automatically trims off any extra length so that you will never see a partial solar panel on a rack. When tracking systems are used with long, linear racks, there is only one way to do it -- horizontal single-axis tracker (HSAT). The new model can handle HSAT with the same degree of speed-up. For other trackers such as the vertical single-axis tracker (VSAT) or the altazimuth dual-axis trackers (AADAT), the speed-up will not be as significant, however, as the inter-rack shading is more dynamically complex and each rack must be treated independently.

By Popular Demand: Printable NGSS Pathfinder

The Next Generation Science Standards (NGSS) provide a framework and examples of three-dimensional learning. Soon after they were released, we created the NGSS Pathfinder to help educators find their way through the core ideas, crosscutting concepts, and science and engineering practices that make up the NGSS. This intuitive tool allows you to consider some of the myriad paths possible, and links to free Concord Consortium resources for any given path.

NGSS Pathfinder

We’ve had lots of positive feedback about the NGSS Pathfinder, including many requests for a printable version. And since we love to give educational resources away for free, we’ve made a printable version of the Pathfinder available. Feel free to use it for handouts, full-size posters, or anything else. We’re especially excited about the idea of people creating laminated posters so they can draw their own paths!

As always, you can continue to use the online NGSS Pathfinder to create interactive links from core ideas to science and engineering practices and crosscutting concepts, and get access to free resources for your selected path. Our computational models and probe-based activities bring important learning within new reach. Students using such technology-based activities also gain wide experience with crosscutting concepts—from scales in space and time to energy and systems—across domains in science, math, and engineering.

The NGSS Pathfinder graphics are licensed under the Creative Commons Attribution 4.0 license (CC BY 4.0), so you’re welcome to use them under those terms. If you share the graphics online, please attribute the Concord Consortium and include a link to https://concord.org.

Infrared Street View won Department of Energy’s JUMP competition

Creating an infrared street view using SmartIR and FLIR ONE
Our Infrared Street View (ISV) program has won the JUMP Competition sponsored jointly by CLEAResult, the largest provider of energy efficiency programs and services in North America, and the National Renewable Energy Laboratory (NREL), a research division of the US Department of Energy (DOE). This JUMP Competition called for innovations in using smartphones' sensing capabilities to improve residential energy efficiency. Finalists were selected from a pool of submitted proposals and invited to make their pitches to the audience at the CLEAResult Energy Forum held in Austin, TX on October 4-6, 2016. There is only one winner among all the good ideas for each competition. This year, we just happened to be one.

IR homework
We envision the Infrared Street View as an infrared (IR) counterpart of Google's Street View (I know, I know, this is probably too big to swallow for an organization that is a few garages small). Unlike Google's Street View in the range of visible light, the Infrared Street View will provide a gigantic database of thermal images in the range of invisible IR light emitted by molecular vibrations related to thermal energy. If you think about these images in a different way, they actually are a massive 3D web of temperature data points. What is the value of this big data? If the data are collected in the right way, they may represent the current state of the energy efficiency of our neighborhoods, towns, cities, and even states. In a sense, what we are talking about is in fact a thermographic information system (TIS).

We are not the only group that realized this possibility (but we are likely the first one that came up with the notion and name of TIS). A few startup companies in Boston area have worked in this frontier earlier this decade. But none of them has tapped into the potential of smartphone technologies. With a handful of drive-by trucks or fly-by drones with a bunch of mounted infrared cameras, it probably would take these companies a century to complete this thermal survey for the entire country. Furthermore, the trucks can only take images from the front of a building and the drones can only take images from above, which mean that their data are incomplete and cannot be used to create the thermal web that we are imagining. In some cases, unsolicited thermal scan of people's houses may even cause legal troubles as thermal signatures may accidentally disclose sensitive information.

Our solution is based on FLIR ONE, a $200-ish thermal camera that can be plugged into a smartphone (iOS or Android). The low cost of FLIR ONE, for the first time in history, makes it possible for the public to participate in this thermal survey. But even with the relatively low price tag, it is simply unrealistic to expect that a lot of people will buy the camera and scan their own houses. So where can we find a lot of users who would volunteer to participate in this effort?

Let's look elsewhere. There are four million children entering the US education system each year. Every single one of them is required to spend a sizable chunk of their education on learning thermal science concepts -- in a way that currently relies on formalism (the book shows you the text and math, you read the text and do the math). IR cameras, capable of visualizing otherwise invisible heat flow and distribution, is no doubt the best tool for teaching and learning thermal energy and heat transfer (except for those visually impaired -- my apology). I think few science teachers would disagree with that. And starting this year, educational technology vendors like Vernier and Pasco are selling IR cameras to schools.

What if we teach students thermal science in the classroom with an IR camera and then ask them to inspect their own homes with the camera as a homework assignment? At the end, we then ask them to acquire their parents' permissions and contribute their IR images to the Infrared Street View project. If millions of students do this, then we will have an ongoing crowdsourcing project that can engage and mobilize many generations of students to come.

Sensor-based artificial intelligence
We can't take students' IR images seriously, I hear you criticizing. True, students are not professionals and they make mistakes. But there is a way to teach them how to act and think like professionals, which is actually a goal of the Next Generation Science Standards that define the next two or three decades of US science education. Aside from a curriculum that teaches students how to use IR cameras (skills) and how to interpret IR images (concepts), we are also developing a powerful smartphone app called SmartIR. This app has many innovations but two of them may lead to true breakthroughs in the field of thermography.

Thermogram sphere
The first one is sensor-based intelligence. Modern smartphones have many built-in sensors, including the visible light cameras. These sensors and cameras are capable of collecting multiple types of data. The increasingly powerful libraries of computer vision only enrich this capability even more. Machine learning can infer what students are trying to do by analyzing these data. Based on the analysis results, SmartIR can then automatically guide students in real time. This kind of artificial intelligence (AI) can help students avoid common mistakes in infrared thermography and accelerate their thermal survey, especially when they are scanning buildings independently (when there is no experienced instructor around to help them). For example, the SmartIR app can check if the inspection is being done at night or during the day. If it is during the day (because the clock says so or the ambient light sensor says so), then SmartIR will suggest that students wait to do their scan until nightfall eliminates the side effect of solar heating and lowers the indoor-outdoor temperature difference to a greater degree. With an intelligent app like this, we may be able to increase the quality and reliability of the IR images that are fed to the Infrared Street View project.
Virtual infrared reality (VIR) viewed with Google Cardboard

The second one is virtual infrared reality, or VIR in short, to accomplish true, immersive thermal vision. VIR is a technology that integrates infrared thermography with virtual reality (VR). Based on the orientation and GPS sensors of the phone, SmartIR can create what we called a thermogram sphere and then knit them together to render a seamless IR view. A VIR can be uploaded to Google Maps so that the public can experience it using a VR viewer, such as Google's Cardboard Viewer. We don't know if VIR is going to do any better than 2D IR images in promoting the energy efficiency business, but it is reasonable to assume that many people would not mind seeing a cool (or hot) view like this while searching their dream houses. For the building science professionals, this may even have some implications because VIR provides a way to naturally organize the thermal images of a building to display a more holistic view of what is going on thermally.

With these innovations, we may eventually be able to realize our vision of inventing a visual 3D web of thermal data, or the thermographic information system, that will provide a massive data set for governments and companies to assess the state of residential energy efficiency on an unprecedented scale and with incredible detail.

Geological models to help students explore the Earth

Geoscience poses many questions. Why are there continents and oceans? How do mountains form? Why do volcanoes form in some areas and not others? What causes earthquakes to be more frequent in some areas than others? Why are oil, diamond, gold, and other deposits clustered in particular areas rather than being spread evenly across the world?

Teaching geoscience poses significant challenges. Experiments with Earth’s geology are impossible, and many of the natural processes that shape Earth, such as sedimentation, folding, and faulting, take place out of sight, over unimaginably long time periods. We think that technology has the potential help to transform how geoscience is taught and understood.

From the people who brought you High-Adventure Science comes the GEODE (Geological Models for Explorations of Dynamic Earth) project. Funded by the National Science Foundation, the new project aims to design dynamic, interactive, computer-based models and curricula to help students understand how Earth’s surface and subsurface features are shaped. As in the High-Adventure Science modules, GEODE modules will incorporate real-world data and computational models, with a focus on making scientific arguments based on evidence.

The GEODE  project, a partnership between the Concord Consortium and The Pennsylvania State University, held a kickoff brainstorming session Monday, September 27. Principal Investigator Amy Pallant and Co-PI Hee-Sun Lee, both of the Concord Consortium, and Co-PI Scott McDonald of Penn State organized a meeting to begin developing a plate tectonics model to accompany the recently developed Seismic Explorer.

In Seismic Explorer, students can see patterns of earthquake data, including magnitude, depth, location, and frequency.

In Seismic Explorer, students can see patterns of earthquake data, including magnitude, depth, location, and frequency.

seismicexplorer-cross-section

Students can make a cross-section to see a three-dimensional view of the earthquakes in an area.

Professional geologists, geoscience educators, and software developers reviewed the currently available models and simulations of plate motion, earthquake waves, sedimentation, folding, and faulting, and discussed ways to make these concepts accessible to middle and high school students.

We look forward to sharing more models and activities as they are developed over the next few years!