Stochastic turbulence modeling in RANS simulations via Multilevel Monte Carlo

A multilevel Monte Carlo (MLMC) method for quantifying model-form uncertainties associated with the Reynolds-Averaged Navier-Stokes (RANS) simulations is presented. Two, high-dimensional, stochastic extensions of the RANS equations are considered to demonstrate the applicability of the MLMC method. The first approach is based on global perturbation of the baseline eddy viscosity field using a lognormal random field. A more general second extension is considered based on the work of [Xiao et al.(2017)], where the entire Reynolds Stress Tensor (RST) is perturbed while maintaining realizability. For two fundamental flows, we show that the MLMC method based on a hierarchy of meshes is asymptotically faster than plain Monte Carlo. Additionally, we demonstrate that for some flows an optimal multilevel estimator can be obtained for which the cost scales with the same order as a single CFD solve on the finest grid level.Comment: 40 page

Density Functional Calculations On First-Row Transition Metals

The excitation energies and ionization potentials of the atoms in the first transition series are notoriously difficult to compute accurately. Errors in calculated excitation energies can range from 1--4 eV at the Hartree-Fock level, and errors as high as 1.5eV are encountered for ionization energies. In the current work we present and discuss the results of a systematic study of the first transition series using a spin-restricted Kohn-Sham density-functional method with the gradient-corrected functionals of Becke and Lee, Yang and Parr. Ionization energies are observed to be in good agreement with experiment, with a mean absolute error of approximately 0.15eV; these results are comparable to the most accurate calculations to date, the Quadratic Configuration Interaction (QCISD(T)) calculations of Raghavachari and Trucks. Excitation energies are calculated with a mean error of approximately 0.5eV, compared with \sim 1\mbox{eV} for the local density approximation and 0.1eV for QCISD(T). These gradient-corrected functionals appear to offer an attractive compromise between accuracy and computational effort.Comment: Journal of Chemical Physics, 29, LA-UR-93-425

The grain of Greek voices

Law, ritual, myth, education-through-dance (khoreia), invective, games, wisdom, praise, lament--almost every verbal institution imaginable employed stylized language, formulaic diction, characteristic rhythms, or time-honored performance habits. They were transmitted wholly, or partly, without writing.Not

Revisiting the Tenascins: Exploitable as Cancer Targets?

For their full manifestation, tumors require support from the surrounding tumor microenvironment (TME), which includes a specific extracellular matrix (ECM), vasculature, and a variety of non-malignant host cells. Together, these components form a tumor-permissive niche that significantly differs from physiological conditions. While the TME helps to promote tumor progression, its special composition also provides potential targets for anti-cancer therapy. Targeting tumor-specific ECM molecules and stromal cells or disrupting aberrant mesenchyme-cancer communications might normalize the TME and improve cancer treatment outcome. The tenascins are a family of large, multifunctional extracellular glycoproteins consisting of four members. Although each have been described to be expressed in the ECM surrounding cancer cells, tenascin-C and tenascin-W are currently the most promising candidates for exploitability and clinical use as they are highly expressed in various tumor stroma with relatively low abundance in healthy tissues. Here, we review what is known about expression of all four tenascin family members in tumors, followed by a more thorough discussion on tenascin-C and tenascin-W focusing on their oncogenic functions and their potential as diagnostic and/or targetable molecules for anti-cancer treatment purposes