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 2018 Research Symposium Abstracts.

2019 projects will continue to be posted through January!

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:

Environmental Science

 

Indoor Air Pollution Research: From Nano to Bio

Research categories:  Agricultural, Bioscience/Biomedical, Chemical, Civil and Construction, Environmental Science, Life Science, Mechanical Systems, Nanotechnology, Physical Science
School/Dept.: Civil Engineering
Professor: Brandon Boor
Preferred major(s): Students from all majors are welcome to apply.
Desired experience:   Interest in studying contaminant transport in the environment, human health, air pollution, HVAC and building systems, microbiology, nanotechnology, and atmospheric science. Experience working in a laboratory setting with analytical equipment and coding with MATLAB, Python, and/or R. Passionate about applying engineering fundamentals to solve real-world problems.

Airborne particulate matter, or aerosols, represent a fascinating mixture of tiny, suspended liquid and solid particles that can span in size from a single nanometer to tens of micrometers. Human exposure to aerosols of indoor and outdoor origin is responsible for adverse health effects, including mortality and morbidity due to cardiovascular and respiratory diseases. The majority of our respiratory encounters with aerosols occurs indoors, where we spend 90% of our time. Through the SURF program, you will work on several ongoing research projects exploring the dynamics of nanoaerosols and bioaerosols in buildings and their HVAC systems.

Nanoaerosols are particles smaller than 100 nm in size. With each breath of indoor air, we inhale several million nanoaerosols. These nano-sized particles penetrate deep into our respiratory systems and can translocate to the brain via the olfactory bulb. These tiny particles are especially toxic to the human body and have been associated with various deleterious toxicological outcomes, such as oxidative stress and chronic inflammation in lung cells. Bioaerosols represent a diverse mixture of microbes (bacteria, fungi) and allergens (pollen, mite feces). Exposure to bioaerosols plays a significant role in both the development of, and protection against, asthma, hay fever, and allergies.

Your role will be to conduct measurements of nanoaerosols and bioaerosols in laboratory experiments at the Purdue Herrick Laboratories, as well as participate in a field campaign at Indiana University - Bloomington in collaboration with an atmospheric chemistry research group. You will learn how to use state-of-the-art air quality instrumentation and perform data processing and analysis in MATLAB.

More information: http://www.brandonboor.com/

 

Processing of innovative satellite remote sensing data for ocean and snow remote sensing

Research categories:  Aerospace Engineering, Computer Engineering and Computer Science, Electronics, Environmental Science, Physical Science
School/Dept.: AAE
Professor: James Garrison
Preferred major(s): ECE, AAE, Physics, EAPS
Desired experience:   Good programming skills, signal processing (ECE 301 or AAE301). Experience with software defined radio (USRP) will be a plus.

Reflectometry is a new approach to Earth remote sensing in microwave frequencies, using reflections of Global Navigation Satellite System (GNSS, e.g. GPS, Galileo, etc ...) signals from land and ocean surfaces as illumination source in a bistatic radar configuration. Through observing measurable changes in the properties of these signals, various features of the reflecting surfaces can be inferred.

Ocean surface winds is the most developed application for GNSS-Reflectometry (GNSS-R), with the launch of the CYGNSS constellation by NASA in 2016. CYGNSS data has been collected during the 2017 and 2018 Hurricane seasons, showing some capability for wind field measurements at a high spatial resolution. New models and algorithms are required, however, to optimally process these data and extract wind vectors with high sensitivity, especially at the higher wind speeds present in hurricanes. Development of these new models and algorithms requires the collection of high-quality data under carefully controlled conditions along with in situ training data provided by independent sources. With this goal in mind, Purdue has developed a wideband GNSS-R signal recorder which will be flown on the P-3 “Hurricane Hunter” aircraft operated by NOAA. This aircraft is capable of operating in extremely high winds and penetrating the Hurricane eye wall, in order to collect data inside developing tropical cyclones. GNSS-R data collected in this experiment will be compared with wind speed observations from other instruments on the P-3 aircraft, other satellite data, and model results. These comparisons will be used to develop and improved model for the extraction of ocean winds from CYGNSS and future satellite missions.

Snow Water Equivalent (SWE) is a representation of the total water stored in the snow pack. This is an important climate variable for the prediction of fresh water supplies as well as applications such as hydroelectric power. A new application of GNSS-R is measuring SWE as a change in phase of the reflected signal, a result of the slower propagation of the signal through the snow layer. Spaceborne measurements of SWE using GNSS-R have never been conducted. Special collections of CYGNSS data were conducted this year, in which raw signals (no on-board processing or compression) were collected in arcs spanning snow-covered regions in the Himalayan mountains.

SURF projects are proposed to support these two research goals for CYGNSS data. Both will involve extensive programming and data processing, using a “software defined radio” method that essentially implements all signal processing in software to operate on the full-spectrum of the recorded signal.

Applicants should have very strong programming skills, some knowledge of basic signal processing.

 

Remote sensing of soil moisture and forest biomass using P-band Signals of Opportunity: Model development and experimental validation

Research categories:  Agricultural, Aerospace Engineering, Electronics, Environmental Science, Physical Science
School/Dept.: AAE
Professor: James Garrison
Preferred major(s): ECE, AAE, Physics, ABE
Desired experience:   Basic signal processing (AAE 301 or ECE 301 or equivalent) desired. Students should know how to use basic hand tools, and be willing to work outdoors in agricultural or forest environments. A drivers license and reliable access to a car is required for field work.

Root Zone Soil Moisture (RZSM), defined as the water profile in the top meter of soil where most plant absorption occurs, is an important environmental variable for understanding the global water cycle, forecasting droughts and floods, and agricultural management. No existing satellite remote sensing instrument can measure RZSM. Sensing below the top few centimeters of soil, often through dense vegetation, requires the use of microwave frequencies below 500 MHz, a frequency range known as “P-band”. A P-band microwave radiometer would require an aperture diameter larger than 10 meters. Launching such a satellite into orbit will present big and expensive technical challenge, certainly not feasible for a low-cost small satellite mission. This range for frequencies is also heavily utilized for UHF/VHF communications, presenting an enormous amount of radio frequency interference (RFI). Competition for access to this spectrum also makes it difficult to obtain the required license to use active radar for scientific use.

Signals of opportunity (SoOp) are being studied as alternatives to active radars or passive radiometry. SoOp re-utilizes existing powerful communication satellite transmissions as “free” sources of illumination, measuring the change in the signal after reflecting from soil surface. In this manner, SoOp methods actually make use of the very same transmissions that would cause interference in traditional microwave remote sensing. Communication signal processing methods are used in SoOp, enabling high quality measurements to be obtained with smaller, lower gain, antennas.

Under NASA funding, Purdue and the Goddard Space Flight Center have developed an airborne prototype P-band remote sensing instrument to demonstrate the feasibility of a future satellite version. Complementing this technology development, a field campaign will be conducted for its third year the Purdue Agricultural research fields. This campaign will make reflected signal measurements from towers installed over instrumented fields. Measurements will be obtained over bare soil first, and then throughout the corn or soybean growth cycle. Complementing these remote sensing measurements, a comprehensive set of ground-truth data will also be collected for use in developing models and verifying their performance.

In Spring 2019 an additional experiment, using a small Unpiloted Aerial Vehicle (UAV), will be conducted in a forested area in collaboration with the School of Forestry and Natural Resources (FRN).

Work under this project will involve installing microwave electronic equipment in the field, writing software for signal and data processing, and making field measurements of soil moisture and vegetation properties.

Students interested in this project should have good programming skills and some experience with C, python and MATLAB. They should also have a strong background in basic signal processing. Experience with building computers or other electronic equipment will also be an advantage. Students should be willing to work outdoors and have an interest in applying their skills to solving problems in the Earth sciences, environment, or agriculture.

The project will involve regular travel to and from the local research field, so students should have a driving license and access to a car.