language: generic script: ./bootstrap && ./configure && make all && make check && make distcheck matrix: include: - os: linux env: COMPILER_NAME=gcc CXX=g++-5 CC=gcc-5 addons: apt: sources: - ubuntu-toolchain-r-test packages: - autotools-dev - g++-5 - os: linux env: COMPILER_NAME=clang CXX=clang++-3.8 CC=clang-3.8 addons: apt: sources: - ubuntu-toolchain-r-test - llvm-toolchain-precise-3.8 packages: - autotools-dev - clang-3.8
11 December 2016
28 October 2014
My dissertation, Reducing turbulence- and transition-driven uncertainty in aerothermodynamic heating predictions for blunt-bodied reentry vehicles, appeared online today in the University of Texas Library system. Bonus points if you find the typo in the abstract that I accidentally inserted during my final day of editing. Triple word score if you browse through the introductory chapter and ask me questions—my hope is that it is fairly accessible.
Content from Chapter 6, Characteristics of the Homogenized Boundary Layers at Atmospheric Reentry-like Conditions, will be presented at APS DFD 2014 at Stanford in a few weeks. Man, I need to finish those slides...
Very cool is that, as of today, NASA is testing the Orion MPCV on December 4th. That means soon they'll be some real flight data against which my simulation-based predictions found in Chapter 7, Detecting Turbulence-Sustaining Regions on Blunt-Bodied Reentry Vehicles, can be compared.
Happily, the dissertation source code attachments appear to have been preserved too. That said, the GitHub suzerain and ESIO repositories should be preferred over the electronic dissertation attachments for anything other than sleuthing out precisely what I implemented in my thesis. I've already written about the openly available data sets generated for the work.
(Image courtesy of NASA)
11 August 2014
This past week I successfully defended my doctoral dissertation. Two of the three direct numerical simulation data sets I generated during my thesis research are online at turbulence.ices.utexas.edu if anyone's interested:
05 June 2014
I finally cleaned up my compressible, turbulent channel results computed with my thesis code, Suzerain. The dataset includes instantaneous planar averages of 180+ quantities collected in situ during the production runs along with rigorous sampling error estimates for the final ensemble results.
If you want to quickly visualize something, a little wrapper utility makes it a snap. So, without further ado, gratuitous eye candy generated with
summary_surf.py -C 256 -f coleman3k15.h5 bar_u_v bar_u bar_v: