Found 2 projects
Oral Presentation 1
11:00 AM to 12:30 PM
- Presenters
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- Kylie Dillon, Sophomore, Computer science, Lake Wash Tech Coll
- Sam F. (Sam) Wolf, Junior, Computer Science & Software Engineering
- Taylour Mills, Junior, Aeronautics & Astronautics
- Jay Quedado, Junior, Computer Engineering (Bothell)
- Alana Yao, Fifth Year, Computer Science & Software Engineering
- Mentors
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- Narayani Choudhury, Computer Science & Engineering, Mathematics, Physics, Lake Washington Institute of Technology, Kirkland
- Hany Roufael, Engineering & Mathematics, Physics, Lake Washington Institute of Technology
- Session
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Session O-1H: Applied Mathematics and Data Modeling
- 11:00 AM to 12:30 PM
There is currently extensive demand for optical media like CDROM, DVD and Blue ray disks for data storage with computer technologies. Here we combine mathematical modelling studies and photonic laser diffraction experiments to study the optimization of data storage in different types of optical media. Using calculus-based studies, we estimated the data storage capacities in these systems and calculated the CD, DVD and blue ray disk arc length and data storage linear densities. These are in good agreement with reported values. Using red, blue and green laser sources at our photonics lab, we conducted laser diffraction studies and estimated the line spacing of CDROM, DVD and Blue ray disks. The advancement from CDs to DVDs yields higher data storage densities. In the high capacity blue rays disks, because the physical structures called pits that store data on the disks become smaller, there are other challenges in realizing these smaller devices, which make it more expensive. The CD/DVD players' lasers operate at the diffraction limit resolution of light and provide maximum data capacity for their geometry. Magnetic media like floppy disks, hard disk and magnetic tapes are also used for computer data storage. We have estimated the maximum data storage capacity from magnetic floppy discs. We used curve fitting methods to analytically represent the magnetic read-back pulse as Lorentzian functions for data modeling. Our studies provide an integrated STEM learning of data storage in optical and magnetic media.
Oral Presentation 3
2:45 PM to 4:15 PM
- Presenters
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- Alana Yao, Fifth Year, Computer Science & Software Engineering
- Dave Edward (Dave) Diaz, Sophomore, Civil Engineering, Lake Wash Tech Coll
- Kylie Dillon, Sophomore, Computer science, Lake Wash Tech Coll
- Alex Klimecky
- Sam F. (Sam) Wolf, Junior, Computer Science & Software Engineering
- Mentor
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- Narayani Choudhury, Engineering, Mathematics, Physics, Lake Washington Institute of Technology, Kirkland
- Session
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Session O-3F: Applied Computer Science: Robots, AR, and More
- 2:45 PM to 4:15 PM
Solar power provides a renewable energy resource that reduces carbon footprints and lowers global warming. Solar panels use photovoltaics which convert light to electricity. Most commercial solar panels use silicon wafers. Electrons in these semiconducting silicon panels are freed by solar energy and are induced to travel through an electrical circuit, powering electrical devices or sending electricity to the grid. We have analyzed the reported crystal structure of silicon, which crystallizes in the same pattern as diamond and has a face centered cubic structure with lattice constant 5.4307 Å. We employed vector calculus-based methods to calculate the nearest-neighbor bond lengths (2.3516 Å) and bond angles (109.471o) of crystalline silicon. These calculated bond-lengths and angle values are in good agreement with reported data. We visualized the electronic charge-density of silicon. Using vector-calculus based methods, we derived the equation for the plane of the solar panel and estimated the power that a solar panel can produce. Real time data from solar panel grids are currently available from energy databases. We determined the total energy produced by a solar panel array over the course of a day by finding the area under the power-vs-time real-time data reported in energy databases using integral calculus-based methods. To understand seasonal variations, we compared solar energy production on a hot summer day and during an overcast winter day. Our studies provide a microscopic atomic level understanding of solar energy and provides an integrated study of mathematics with solar physics and engineering.