Gas Surface Interactions Lab

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New journal article in JCP

May 27th, 2017

New journal article in the Journal of Computational Physics:

This paper presents a new data-driven adaptive computational model for simulating turbulent flow, where partial-but-incomplete measurement data is available. The model automatically adjusts the closure coefficients of the Reynolds-averaged Navier–Stokes (RANS) k–ω turbulence equations to improve agreement between the simulated flow and the measurements. This data-driven adaptive RANS k–ω (D-DARK) model is validated with 3 canonical flow geometries: pipe flow, backward-facing step, and flow around an airfoil. For all test cases, the D-DARK model improves agreement with experimental data in comparison to the results from a non-adaptive RANS k–ω model that uses standard values of the closure coefficients. For the pipe flow, adaptation is driven by mean stream-wise velocity data from 42 measurement locations along the pipe radius, and the D-DARK model reduces the average error from 5.2% to 1.1%. For the 2-dimensional backward-facing step, adaptation is driven by mean stream-wise velocity data from 100 measurement locations at 4 cross-sections of the flow. In this case, D-DARK reduces the average error from 40% to 12%. For the NACA 0012 airfoil, adaptation is driven by surface-pressure data at 25 measurement locations. The D-DARK model reduces the average error in surface-pressure coefficients from 45% to 12%.

Li, Z., Zhang, H., Bailey, S. C., Hoagg, J. B., and Martin, A., “A Data-Driven RANS k-ω approach for modeling turbulent flows,” Journal of Computational Physics, vol. 345, 2017, pp. 111–131.




New journal article!

May 17th, 2017

A new journal article was recently published in the International Journal of Heat and Mass Transfer:

Material properties and oxidation behavior of low-density felts used as substrates for conformal carbon/ phenolic ablators were compared with those of a rigid carbon fiber preform used to manufacture heritage lightweight ablators. Synchrotron X-ray micro-tomography measurements were performed to character- ize the materials’ microstructure at the scale of the fibers. Using the tomography voxels as computational grids, tortuosity in the continuum regime, and room temperature conductivity were computed. Micro- scale simulations of the oxidation of carbon fibers were carried out using a random walk model for oxy- gen diffusion and a sticking probability law to model surface reactions. The study shows that, due to a higher porosity and lower connectivity, the felt materials have lower thermal conductivity but a faster recession rate than that of the rigid preform. Challenges associated with computations based on micro-tomography are also discussed.

[1] Panerai, F., Ferguson, J. C., Lachaud, J. R., Martin, A., Gasch, M. J., and Mansour, N. N., “Analysis of rigid and flexible substrates for lightweight ablators based on X-ray micro-tomography,” International Journal of Heat and Mass Transfer, Vol. 108, Part A, May 2017, pp. 801–811.
DOI: 10.1016/j.ijheatmasstransfer.2016.12.048