Science and Engineering Summer Apprentice Program

Science and Engineering Apprentice Program

The Science and Engineering Apprenticeship program puts research in engineering, computer science, physics, and math into the hands of students during the summer between high school and college. Students selected for the program often have their first experience working in a laboratory research-and-development environment and learn more about careers in their chosen fields of study.

Each apprentice completes a summer-long project and prepares a technical report and presentation outlining their work. The presentations are judged, with winners receiving special recognition and small cash prizes; the technical reports are combined into one larger publication and distributed to project sponsors, U.S. government officials, university administrators, and counselors at area high schools. In addition to their projects, the apprentices enjoy a tour of Lake Travis Test Station, attend technical seminars presented by ARL:UT’s research and support staff, and network during student socials that provide an opportunity for the students to discuss research projects with their peers.

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Science and Engineering Apprenticeships

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About the S&E

ARL:UT’s Science and Engineering Apprenticeship Program has been in effect since 1982 for students with an interest in aerospace, electrical, or mechanical engineering; computer science; geophysics; mathematics; or physics. Over 576 students have taken part. The program is competitive. U.S. citizenship is required, and preference is given to students planning to attend the University of Texas at Austin. Many participants return to ARL:UT in student and research positions and stay on to contribute for several years.

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  • Graduating high school senior entering a 4-year college or university in the upcoming fall semester
  • Available to work throughout the summer appointment period (Unpaid time off is available only for attendance of freshman college orientation).
  • Must have applied and been admitted to The University of Texas at Austin
  • U.S. Citizen
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Download the Application. Directions are included in the application (16 pages). Right click link to open in a new window. Return it to ARL:UT by U.S. mail or email by the date specified.

Apprentice flyer Download the Flyer. High school educators, please print and distribute this flyer to interested graduating seniors in your science and advanced math classes. Right click link to open in a new window.

Previous Student Projects

Below are abstracts from three student projects.

Student Presentations

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Effects of 3D printing parameters on acoustic transmission properties of polylactic acid

In fused-deposition modelling 3D printing, melted plastic is extruded in lines and deposited successively into a desired shape. This progressive, layer-based process yields parts with nonuniform internal structure. This project studied the effects of print orientation and infill line pattern on acoustic transmission of polylactic acid (PLA). 200x200x3mm test plates were printed with 100% infill at various orientations relative to the print bed, changing the internal layer geometry by extension. The plate was then submerged in an underwater acoustic testing tank between two hydrophones. A chirp containing frequencies from 1Khz to 1MHz was produced behind the plate, and recorded as it passed through the plate and to the other side. Along with frequency being varied, the effect of incidence angle on transmission was also tested by moving the receiving hydrophone. Transmission spectra were produced for each plate, showing acoustic transmission per angle-frequency pair. Despite internal layer geometries, tested plates were shown to be generally isotropic. This result indicates that 3D printed parts for acoustic applications can be printed to optimize time and energy, as print orientations and settings at 100% infill have minimal acoustic effect.
Liberal Arts and Science Academy, Austin, Texas, Advanced Technology Laboratory

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State-of-the-art tensor network simulations of random quantum supremacy circuits

Quantum computing promises a future reimagined with its powerful potential speedups over its classical counterpart. However, modern quantum hardware is limited by the number of qubits and depth of the circuits. Striving to accelerate progress in this area and ultimately develop better quantum hardware, we seek to construct a tensor network simulator of random quantum circuits. Working with random quantum circuits allows for the development of a simulator that performs well in almost all use-cases. With this, we can better benchmark quantum hardware while pushing the limits of both classical and quantum computation. Converting a quantum circuit to a tensor network is trivial. We then simplify the resulting network using a variety of techniques including rank simplification, split decomposition, and column reduction. Next, we bi-partition the simplified network into the head and tail according to a cut size target. Fixing the qubits of the head to the zero computational state, and enumerating over all bit string combinations in the tail, we achieve a state-of-the-art contraction scheme that calculates 64 times as many bit strings in less than half the time it takes for the next best simulation. Future expansion of this project extends to further improving contraction path methods, developing better quantum computing benchmarks, and pushing forward quantum hardware.
Cedar Ridge High School, Round Rock, Texas, Signal and Information Sciences Laboratory

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Smartphone celestial navigation

A digital zenith camera is an instrument capable of determining its location on Earth by observing the stars overhead, with impressive accuracy and precision. But they are large and heavy; a large SUV is typically required for transporting and deploying the equipment, while also relying on expensive optics. We explore the feasibility of using a smartphone, as a more portable and less expensive instrument, to produce a terrestrial position from the stars. A mobile app is developed to take pictures with configurable exposure duration and light sensitivity, and embeds the local time as well as tilts in the x-axis and y-axis, derived from accelerometer data, at the end of the exposure. Using the images captured with the app, additional software is run to extract and compare the star positions against asterisms formed from a star catalog to determine the celestial position of the image’s center. Subsequent use of the images’ timetags and tilt data helps to determine the user’s position on Earth from the celestial position of the stars in the smartphone’s images. An averaging of precision estimates in optical variation and accelerometer noise over 6 image collections of images taken at 19 second exposure time, 125 ISO, with a 79° field of view, yielded 0.0904° of overall system error, due to optical variations and accelerometer noise. Optical variations were the greatest contributor to overall system error. Additional work on minimizing optical variations should explore if coarser index file scales significantly change celestial position estimates, and explore how different lighting conditions affects solvability as well as celestial position estimates. Future work in addressing accelerometer noise should explore utilizing sensor fusion on modern smartphones, applying advanced noise filtering methods, or pursuing accelerometer specific low-pass filter optimization.
Dripping Springs High School, Dripping Springs, Texas, Space and Geophysics Laboratory

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Science and Engineering Apprentices are each assigned their own summer research project. This student is testing new underwater acoustic materials using near-field acoustic holography.

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