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Research Projects

Projects are posted below; new projects will continue to be posted through February. To learn more about the type of research conducted by undergraduates, view the 2017 Research Symposium Abstracts.

This is a list of research projects that may have opportunities for undergraduate students. Please note that it is not a complete list of every SURF project. Undergraduates will discover other projects when talking directly to Purdue faculty.

You can browse all the projects on the list, or view only projects in the following categories:

Innovative Technology/Design

 

Experimental Characterization and Thermal Modeling of Dynamic Heat Loads on Microscale Two-Phase Cooling Systems

Research categories:  Aerospace Engineering, Computational/Mathematical, Electronics, Innovative Technology/Design, Material Science and Engineering, Mechanical Systems, Physical Science
School/Dept.: Mechanical Engineering
Professor: Justin Weibel
Preferred major(s): Mechanical, Chemical, or Aerospace Engineering
Desired experience:   Students interested in thermal fluids are encouraged to apply. Course work in fluid mechanics and heat transfer is highly recommended. A basic understanding of MATLAB programming is preferred.

High-performance electronic devices generate large amounts of waste heat and rely on effective cooling systems to dissipate these heat loads and maintain safe operating temperatures. Microscale two-phase cooling strategies that allow liquid coolant to boil during the heat removal process offers a promising solution. However, dynamic operation of the electronic devices can trigger two-phase flow instabilities that compromise the cooling performance; these instabilities and their effect on device operation are not well understood. In this project, a SURF student will work with a PhD student in the Cooling Technologies Research Center (https://engineering.purdue.edu/CTRC/). Opportunities are available for students with interests in modeling and/or experimental work. Microscale two-phase flow experiments will be used investigate the effects of various dynamic heating profiles on the flow behavior, using high-speed visualizations and other measurement techniques. Experimental data will be used to model the effect of cooling performance on electronic devices.

 

Purdue AirSense: An Air Pollution Sensing Network for West Lafayette

Research categories:  Agricultural, Chemical, Civil and Construction, Computer Engineering and Computer Science, Electronics, Environmental Science, Innovative Technology/Design, Mechanical Systems, Nanotechnology, Physical Science
School/Dept.: Civil Engineering
Professor: Brandon Boor
Preferred major(s): The position is open to students from all STEM disciplines.
Desired experience:   Proficient in Python, Java, MATLAB; experience with Raspberry Pi or Arduino.

Air pollution is the largest environmental health risk in the world and responsible for 7 million deaths each year. We are presently developing a new air pollution sensing network for the Purdue campus to monitor and analyze air pollutants in real-time. We are recruiting an undergraduate student to assist with the development of our Raspberry Pi-based air quality sensor module. You will be responsible for integrating the Raspberry Pi with air quality sensors, developing laboratory calibration protocols, building an environmental enclosure for the sensors, creating modules on our website for real-time data analysis and visualization, and maintaining state-of-the-art aerosol instrumentation at our central air quality monitoring site at the Purdue Agronomy Center for Research and Education (ACRE).

 

Surface Enhancement using Severe Plastic Deformation

Research categories:  Aerospace Engineering, Computational/Mathematical, Innovative Technology/Design, Material Science and Engineering, Mechanical Systems, Nanotechnology
School/Dept.: Materials Engineering
Professor: David Bahr
Preferred major(s): MSE, ME, or AAE
Desired experience:   Mechanical behavior courses, mechanical testing laboratory experience.

Modifying the surface of metals using shot peening, burnishing, and other plastic deformation processing is common in industry. However, we have limited ability to predict performance of how shot peened materials change properties due to complex interactions between residual stresses and microstructural changes. This project, tied to an industrial consortium, will focus on developing a combined model that predicts both recrystallization and residual stresses using a combination of experimental measurements and predictive computational models in common engineering alloys. The student will gain experience in preparing samples for metallographic inspection, performing hardness testing and optical microscopy, and using basic finite element simulations.