NCSI: Statistical Description of Turbulent Wall-bounded Flows

Status	Completed
Mentor Name	Guillermo Araya
Mentor's XSEDE Affiliation	XSEDE-allocation PI
Mentor Has Been in XSEDE Community	4-5 years
Project Title	Statistical Description of Turbulent Wall-bounded Flows
Summary	Turbulence is mainly characterized by randomness, chaos and a disparate range of turbulent scales and mixing. Applications can be found in drag reduction, heat transfer enhancement, aeroacoustic noise control and mixing enhancement. In recent years, the discipline of fluid dynamics has been reliant to high-performance computational simulations as a means of predicting flow behavior and understanding the thin zone around a solid immersed in a viscous fluid flow, the so called "boundary layer." Furthermore, turbulent boundary layers that evolve along the flow direction are ubiquitous. Computationally speaking, this type of boundary layer (i.e., spatially-developing boundary layer) poses an enormous challenge, due to the need for accurate and time dependent in flow turbulence information. Direct Numerical Simulation (DNS) is a numerical tool that resolves all turbulence scales; thus, it aims to provide high spatial/temporal flow data. In this project, we will employ a large dataset of direct simulations of turbulent boundary layers in order to perform a structural analysis of boundary layer parameters based on high order statistics of velocity, pressure and temperature fluctuations, such as quadrant analysis, skewness, flatness, probability density function (PDF) and power spectra. The major objectives of the proposed study are two-fold: (i) to understand the effect of different external conditions such as streamwise pressure gradient, Reynolds number dependency and compressibility, on the boundary layer structure, (ii) to evaluate the analogy between the velocity and thermal field.
Job Description	The apprentice position is at the High Performance Computing and Visualization Lab (HPCVL) www.uprm.edu/hpcvl/ at the Dept. of Mechanical Engineering in the U. of Puerto Rico-Mayaguez (UPRM). The undergraduate student intern will work on a post-processing code in the area of C++ platform programming with GPU capabilities (CUDA) to mitigate the performance issues as well as with open source codes. The principal objectives/tasks of this internship can be summarized as follows: - Develop a C++ code for managing/reading a large database of Direct Numerical Simulation (DNS) related to spatially-developing turbulent boundary layers. - Compute high order statistics. Some routines (to be called) are already developed for second/third moment statistics.
Computational Resources	The DNS database is distributed in Ranch (TACC) and Blue Waters (NCSA). These simulations were performed in Stampede2 under XSEDE computational allocation #TG-CTS170006. The intern will be set as a user of this account in order to get access to the TACC computational resources. In addition, the intern will be able to use workstations located at the HPCVLab.
Contribution to Community
Position Type	Apprentice
Training Plan	The intern will initially receive training on fluid mechanics, turbulence, data management, Unix programming, data transfer, C++ and Fortran at the HPCVL lab by the PI and other skilled students. The purpose of this position is to encourage students from underrepresented communities to pursue STEM careers at a graduate level.
Student Prerequisites/Conditions/Qualifications	N/A
Duration	Semester
Start Date	01/15/2019
End Date	05/31/2019