NCSI: Compressible Rayleigh-Taylor Instability with Large Density Ratios (Apprentice Position)

Status	Completed
Mentor Name	Denis Aslangil
Mentor's XSEDE Affiliation	PI of the start-up allocation
Mentor Has Been in XSEDE Community	1-2 years
Project Title	Compressible Rayleigh-Taylor Instability with Large Density Ratios (Apprentice Position)
Summary	Students will investigate Rayleigh-Taylor instability (RTI) occurs between the acceleration subjected two fluids interface where the heavy fluid sits on top of the light fluid. Current scientific literature is vastly investigated the RTI under the incompressible assumption, however in many applications such as in high-density energy processes like inertial confinement fusion (ICF) and supernova formations the incompressible assumption is no longer valid. In this study, a new set of simulations will be performed to investigate the compressibility effects on two-dimensional (2D) RTI with two species with large density differences.
Job Description	The student will perform high-resolution turbulence simulations and write post-processing scripts. She/he needs to have prior experience with Linux-based operating systems and at least one of the coding languages (Python/C++/Julia or Fortran). Students need to be motivated to advance their knowledge in the field of fluid dynamics, numerical methods, and coding.
Computational Resources	The student will use the mentor's start-up allocation at XSEDE systems, mainly on Stampede2. In addition, the student(s) will use the mentor's reserved allocation at the University of Alabama HPC systems.
Contribution to Community	The project aims to encourage STEM students to pursue advanced degrees in the area of exascale computations. The project aims to introduce the HPC systems, parallel computing, and challenging engineering problems such as turbulence closure. The main contribution of the project aims to prepare one or two STEM students for future XSEDE projects by training them in coding, parallel computing, and HPC systems.
Position Type	Apprentice
Training Plan	The student will mainly perform 2D direct numerical simulations (DNS) of the compressible Rayleigh-Taylor instability with different density ratios, post-process the turbulence data, and be responsible for archiving the generated data. In addition, she/he will 1. need to make minor changes in the input file of the DNS code to change the initial density ratio between the two mixing fluids and to change the resolution to explore the convergence of the results. 2. write short python scripts to plot the time evolution of the flow and compare the density ratio effects on compressible RTI. If the mentor could hire a second student, the second student would extend the investigated Reynolds numbers. She/he will write short python scripts to plot spatial evolution off the flow at different time instants. Both students will share their scripts in a common folder and attend weekly meetings in the m3s lab to present their progress to the graduate students and mentor, Dr. Aslangil.
Student Prerequisites/Conditions/Qualifications	Took Fluid Dynamics course, and at least one numerical methods/coding or relevant class Experience with one of the coding languages (Python/Fortran/C++ or Julia) Motivation to learn advanced fluid dynamics and compressible flow concepts, and Linux based operating systems Motivation to present their work at the international fluid dynamics conferences
Duration	Semester
Start Date	01/17/2022
End Date	04/10/2022