Announcements of Opportunity
Special Note for SURF@JPL 2024
JPL is operating under a continuing resolution (meaning they are waiting for approval from Congress of NASA's 2024 budget). Additionally, due to other factors, JPL is concerned about a potential budget decrease. This will impact the number of summer internships available. We are working closely with JPL leadership to minimize the impact, but you can expect that AOs will likely not get posted until later this term. To accommodate this later timeline we will offer a second SURF@JPL application deadline. (This extension is for SURF@JPL only.)
- Students who find a JPL mentor early are encouraged to apply by the regular February 22 deadline. For applicants who meet this deadline, awards will be announced on April 1.
- Students who find a JPL mentor later will need to apply by April 19. Awards for this round of applications will be announced on May 6.
Students are also encouraged to apply to the JPL SIP program, which has an application deadline of March 29. For more information about SIP, visit: https://www.jpl.nasa.gov/edu/intern/apply/summer-internship-program
SURF@JPL: Announcements of Opportunity
Announcements of Opportunity are posted by JPL technical staff for the SURF@JPL program. Each AO indicates whether or not it is open to non-Caltech students. If an AO is NOT open to non-Caltech students, please DO NOT contact the mentor.
Announcements of Opportunity are posted as they are received. Please check back regularly for new AO submissions!
**Students applying for JPL projects should complete a SURF@JPL application instead of a "regular" SURF application.
**Students pursuing opportunities at JPL must be U.S. citizens or U.S. permanent residents.
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Project: |
Simulating Molecular and Particulate Transport in Spacecraft Environments
(JPL AO No. 15163)
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Disciplines: | Aerospace Engineering, Mathematical Modeling | ||||||||
Mentor: |
William Hoey,
(JPL),
william.a.hoey@jpl.nasa.gov, |
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Background: | Contamination Control is a critical discipline for space missions: molecular and particulate contamination can affect the performance of both spacecraft systems and science instrumentation. Missions attempting to detect organics and life signatures - like NASA's recently-launched Mars 2020 Perseverance Rover or its upcoming Europa Clipper - require particularly stringent levels of contamination control in support of their science objectives. Solving such challenges requires the development and use of complex, predictive mathematical models that combine theory with experimentally-collected data. Such challenges pose questions of mass transport that may be treated with continuum fluid dynamic methods (like CFD), rarefied gas dynamic methods (like DSMC), or various free-molecular methods (like ray-tracing or view factor schemes). | ||||||||
Description: | JPL Contamination Control develops and deploys a variety of computational physics codes to simulate physical transport processes of gas and particles in vacuum and in atmospheres. In 2024, JPL CC has several opportunities available for a skilled intern to apply and develop these codes. Examples of past internship projects in this vein include: the development of direct simulation Monte Carlo algorithms in application to thruster plume flows; the use of computational fluid dynamics (CFD) techniques in simulating rocket fairing depressurization during launch; the application of optimization and machine learning algorithms to synthesize large, experimentally-derived datasets of spacecraft hardware and materials outgassing properties; and the improvement of algorithms for numerically integrating view factors. | ||||||||
References: | https://doi.org/10.1088/1757-899X/1287/1/012002 ; https://doi.org/10.1117/12.2568127 ; https://doi.org/10.1109/AERO47225.2020.9172679 ; https://www.jpl.nasa.gov/missions/europa-clipper/ ; https://www.jpl.nasa.gov/missions/mars-sample-return-msr | ||||||||
Student Requirements: | A science or engineering major is ideal, with relevant coursework in chemistry and mathematical modeling preferred. All projects will require some experience with scripting in either MATLAB or Python. An intern may need to learn a scientific programming language, and learn to use a command-line interface to access high-performance computing resources. | ||||||||
Location / Safety: | Project building and/or room locations: . Student will need special safety training: . | ||||||||
Programs: |
This AO can be done under the following programs:
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