New NSF grant, and commitment to better science communication
In this debut post to our group blog, I’m excited to announce a new grant from the National Science Foundation (NSF): “Collaborative Research: CDS&E: Leveraging hardware acceleration for accurate particle dynamics in turbulent flows”¹. This project is a collaboration with Prof. Guillaume Blanquart of Caltech, who A.J. Fillo and I have been working with for a few years.
This three-year award of about $261,000 will support a full-time PhD student in the group (and half a month of my summer time each year), plus travel to a conference each year to present our progress.² The PhD student working on the project will also travel down to Caltech once a year to work closely with our collaborators.
The goal of this project is to improve our ability to model how nanoparticles—meaning particles that are 1 to 100 nanometers wide, or one billionth of a meter—move and evolve in complex, chaotic turbulent fluid flows. This could be soot that forms in internal combustion engines, or tiny metal or plastic particles emitted by consumer products (or even 3D printers!). The tools we will develop will allow us (and engineers in industry) to better predict the formation, growth, and destruction of these particles. This will help engine designers prevent the formation of soot, which hurts human health and the environment, or manufacturers increase yields of desirable nanoparticles, depending on the application.
We will do this by developing new methods to solve the complex equations needed to track large numbers of nanoparticles as they form, grow, and are eventually destroyed. Then, these will be connected with an existing computational modeling tool that simulates turbulent, chemically reacting fluid flows (for example: a flame in a jet engine).
Our work will take advantage of graphics processing units (GPUs) to perform the calculations for evolving nanoparticles. GPUs were originally developed for rapidly displaying content on our computer screens, but have exploded in computational power in the last decade or so (driven in large part by the demands of video games, and more recently cryptocurrency mining). Now GPUs are powerful processors that can handle thousands or millions of simultaneous calculations, perfectly suited to tracking the large numbers of nanoparticles we are studying. The new software we develop to implement these techniques will be shared openly for anyone else to use.
In addition to the research objectives, this project also includes educational and outreach plans. For one, it will support creating a video for NRG member A.J. Fillo’s Educational YouTube series LIB LAB that explains principles of computational fluid dynamics for the general public. We will also run Software Carpentry workshops, open to the Oregon State community, teaching students and researchers necessary computational skills (for example, working with the command line, version control, basics of Python programming).
Keep an eye out here for updates on this project! As we start on it and make progress, we will write followup posts explaining our work.
I am also committing to more frequently (and better) communicate our research work, through this blog. We write lots of technical papers about our work, and make those all openly accessible³, but they aren’t particularly easy to understand by non-experts. So, we are going to write more about our work, and explain just what all those papers are about.
¹ NSF award titles typically contain one or more prefixes that indicate some funding program or category of the grant. In this case, “Collaborative Research” means that our grant is associated with another that shares the same title (Guillaume/Caltech’s grant)—for these joint projects, we actually write a single joint proposal. “CDS&E” means this project is mainly sponsored by the Computational and Data-enabled Science & Engineering program, which supports projects that develop new computational or data-analysis techniques to support scientific and engineering breakthroughs.
² About 25% of that total grant money goes to the university as “Facilities and Administrative” costs, otherwise known as overhead. This money keeps the lights on, helps pay support and administrative staff, and goes to other costs not specific to any one project. About 60% of the total funds (78% of the non-overhead total) are dedicated to student support: student salary, benefits, and tuition/fees.
³ We either post the “author-accepted” versions of our articles on repositories like arXiv or engrXiv, so that the content of papers are free to read, or publish in open-access journals. We also make an effort to share all of the computer code and data we generate for our research; most of our code can be found at the group GitHub organization.