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Tabular water properties interface for Hydra-TH :

Carpenter, John H.; Belcourt, Kenneth N.

Completion of the CASL L3 milestone THM.CFD.P6.03 provides a tabular material properties capability to the Hydra code. A tabular interpolation package used in Sandia codes was modified to support the needs of multi-phase solvers in Hydra. Use of the interface is described. The package was released to Hydra under a government use license. A dummy physics was created in Hydra to prototype use of the interpolation routines. Finally, a test using the dummy physics verifies the correct behavior of the interpolation for a test water table. 3

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TYPE SAND Report YEAR 2013
DOIOSTI

A multiresolution spatial parametrization for the estimation of fossil-fuel carbon dioxide emissions via atmospheric inversions

Ray, Jaideep R.; Lee, Jina L.; Lefantzi, Sophia L.; van Bloemen Waanders, Bart G.

The estimation of fossil-fuel CO2 emissions (ffCO2) from limited ground-based and satellite measurements of CO2 concentrations will form a key component of the monitoring of treaties aimed at the abatement of greenhouse gas emissions. To that end, we construct a multiresolution spatial parametrization for fossil-fuel CO2 emissions (ffCO2), to be used in atmospheric inversions. Such a parametrization does not currently exist. The parametrization uses wavelets to accurately capture the multiscale, nonstationary nature of ffCO2 emissions and employs proxies of human habitation, e.g., images of lights at night and maps of built-up areas to reduce the dimensionality of the multiresolution parametrization. The parametrization is used in a synthetic data inversion to test its suitability for use in atmospheric inverse problem. This linear inverse problem is predicated on observations of ffCO2 concentrations collected at measurement towers. We adapt a convex optimization technique, commonly used in the reconstruction of compressively sensed images, to perform sparse reconstruction of the time-variant ffCO2 emission field. We also borrow concepts from compressive sensing to impose boundary conditions i.e., to limit ffCO2 emissions within an irregularly shaped region (the United States, in our case). We find that the optimization algorithm performs a data-driven sparsification of the spatial parametrization and retains only of those wavelets whose weights could be estimated from the observations. Further, our method for the imposition of boundary conditions leads to a 10computational saving over conventional means of doing so. We conclude with a discussion of the accuracy of the estimated emissions and the suitability of the spatial parametrization for use in inverse problems with a significant degree of regularization.

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TYPE SAND Report YEAR 2013
DOIOSTI
Results 6676–6700 of 9,998
Results 6676–6700 of 9,998