UROP: Through sharing our project at the UROP Symposium, we have learned the value of sharing my knowledge with others while also learning from those who are equally as passionate about STEM as we are. FERCo: We were planning our visit to FERCo (Fossil Energy Research Corporation) to use their blackbody source to calibrate the color sensor of our smartphone …

One issue we faced with our data analysis was that our program was picking up the background data and including that in the analysis. We are only interested in the pixels of the charcoal or wood that is burning. Our new program can get rid of the background data and examine only the pixels of interest. The camera has certain …

We cut out ~1.5 inch cube pieces of wood (poplar, rock maple, red oak, red alder, hickory, hem fir, and walnut) to compare their radiating spectral profiles and temperatures when red hot. We lit these pieces on fire, blew out the flame, and used our spectrometer to find the spectral profile. We also had attached a thermocouple to the surface …

The image shows a 532 nm wave with our blue-green filter. It is from an image of the charcoal at different shutter speeds. We tried to make sure the charcoal temperature remained constant so we could assume constant temperature. According to our data, the data from the red and blue channels gets saturated around 0.003 shutter speed, and the data …

We have the color filter array characterized, but now we are looking into gamma correction to understand how the jpeg compression affects the original picture. A gamma correction is an operation an image compression (jpeg) applies to a picture in order to correct brightness. The picture shows an example (taken from learnopengl.com) of what gamma correction does. Gamma correction is …

This quarter we’re working on determining temperature from an image. What we’ve done this first week is test out different things we can take these images of. We did a bit of this last quarter, but with our code and analysis nearing completion, we will start gathering images of it this quarter. Last quarter we worked with charcoal briquettes, which …

We wanted to find the error of our data using the root mean square (RMS), so we looked at 7 images for each data point in the graph shown, and separated the channels (RGB channels) and calculated the RMS using MatLab function. We eventually analyzed ~200 images, and found only a small error. We have been preparing another test set-up …

Our camera set up consists of a tungsten lamp (we’re using tungsten because its spectral profile is an ideal, smooth, continuous curve) that emits light through a monochrometer, about 2.5 feet away. The monochromter splits the light and yields a narrow wavelength spectrum. This is the light we’re taking pictures of (and analyzing). The data referred to in our last …

We are making good progress! We’ve accurately determined the temperature of our heating rod at different potentiometer settings with a type K, glass braided thermocouple. Our thermocouple is connected to an amplifier that converts the voltage (from the thermocouple) into temperature readings with an Arduino. With the glowing rod heated to 360 K and 953 K (the maximum temperature our …

“Fall quarter was engaging and full of discoveries.” “Fall quarter was bumpy, but essential.” “Fall quarter taught me more about teamwork and perseverance.” As you can see from our team, Fall quarter was a learning and growing experience together, and we’ve since then taken what we’ve learned from and restructured to make ourselves more efficient and productive. We’ve abolished the …