Methane hydrate formation in Ulleung basin under conditions of variable salinity: reduced model and experiments

In this paper, we present a reduced model of methane hydrate formation in variable salinity conditions, with details on the equilibrium phase behavior adapted to a case study from Ulleung Basin. The model simplifies the comprehensive model considered by Liu and Flemings using common assumptions on hydrostatic pressure, geothermal gradient, and phase incompressibility, as well as a simplified phase equilibria model. The two-phase threecomponent model is very robust and efficient as well as amenable to various numerical analyses, yet is capable of simulating realistic cases. We compare various thermodynamic models for equilibria as well as attempt a quantitative explanation for anomalous spikes of salinity observed in Ulleung Basin

Adaptive Double-Diffusion Model and Comparison to a Highly Heterogeneous Micro-Model

Double-diffusion model is used to simulate slightly compressible fluid flow in periodic porous media as a macro-model in place of the original highly heterogeneous micro-model. In this paper, we formulate an adaptive two-grid numerical finite element discretization of the double-diffusion system and perform a comparison between the micro- and macro-model. Our numerical results show that the micro-model solutions appear to converge to the macro-model linearly with the parameter e of periodic geometry. For the two-grid discretization, the a priori and a posteriori error estimates are proved, and we show how to adapt the grid for each component independently.This is the publisher’s final pdf. The published article is copyrighted by Hindawi Publishing Corporation and can be found at: http://www.hindawi.com/.Keywords: Discretizations, Coal, Finite elements, Posteriori error estimators, Single phase flow, CO2 injection, Equations, Desorption, Medi

Pore-to-core simulations of flow with large velocities using continuum models and imaging data

We consider computational modeling of flow with small and large velocities at porescale and at corescale, and we address various challenges in simulation, upscaling, and modeling. While our focus is on voxel-based data sets from real porous media imaging, our methodology is verified first on synthetic geometries, and we analyze various scaling and convergence properties. We show that the choice of a voxel-based grid and REV size can lead up to 10-20% difference in calculated conductivities. On the other hand, the conductivities decrease significantly with flow rates, starting in a regime usually associated with the onset of inertia effects. This is accompanied by deteriorating porescale solver performance, and we continue our experiments up until about 50% reduction in conductivities, i.e., to Reynolds number just under 1. To account for this decrease, we propose a practical power-based fully anisotropic non-Darcy model at corescale for which we calculate the parameters by upscaling.Keywords: Upscaling, Inertia effects, Anisotropy, Forchheimer model, Flow in porous media, 76S05, 76M45, Navier–Stokes equations, Convergence, Porescale simulations, 76M50, Non-Darcy flo

RSK1 promotes murine breast cancer growth and metastasis

Introduction. Triple-negative breast cancer (TNBC), representing over 15% of all breast cancers, has a poorerprognosis than other subtypes. There is no effective targeted treatment available for the TNBC sufferers. Ribosomal S6 kinases (RSKs) have been previously proposed as drug targets for TNBC based on observations that 85% of these tumors express activated RSKs.Materials and methods. Herein we examined an involvement of RSK1 (p90 ribosomal S6 kinase 1) in a regulation of TNBC growth and metastatic spread in an animal model, which closely imitates human disease. Micewere inoculated into mammary fat pad with 4T1 cells or their RSK1-depleted variant. We examined tumorgrowth and formation of pulmonary metastasis. Boyden chamber, wound healing and soft agarose assays wereperformed to evaluate cells invasion, migration and anchorage-independent growth.Results. We found that RSK1 promoted tumor growth and metastasis in vivo. After 35 days all animals inoculatedwith control cells developed tumors while in the group injected with RSK1-negative cells, there were 75%tumor-bearing mice. Average tumor mass was estimated as 1.16 g and 0.37 g for RSK1-positive vs. -negativesamples, respectively (p < 0.0001). Quantification of the macroscopic pulmonary metastases indicated that micewith RSK1-negative tumors developed approximately 85% less metastatic foci on the lung surface (p < 0.001).This has been supported by in vitro data presenting that RSK1 promoted anchorage-independent cell growthand migration. Moreover, RSK1 knock-down corresponded with decreased expression of cell cycle regulatingproteins, i.e. cyclin D3, CDK6 and CDK4.Conclusions. We provide evidence that RSK1 supports tumor growth and metastatic spread in vivo as well asin vitro migration and survival in non-adherent conditions. Further studies of RSK1 involvement in TNBC progression may substantiate our findings, laying the foundations for development of anti-RSK1-based therapeuticstrategies in the management of patients with TNBC

Computational upscaling of inertia effects from porescale to mesoscale

This paper is included in the Proceedings, Part 1, of the International Conference on Computational Science 2009 (ICCS 2009) held in Baton Rouge, LA, USA, May 25-27, 2009.We propose algorithms for computational upscaling of flow from porescale (microscale) to lab scale (mesoscale). In particular, we solve Navier-Stokes equations in complex pore geometries and average their solutions to derive properties of flow relevant at lab scale such as permeability and inertia coefficients. We discuss two variants of tra-ditional discretizations: a simple algorithm which works well in periodic isotropic media and can be used when coarse approximations are needed, and a more complex one which is well suited for nonisotropic geometries. Convergence of solutions and averaging techniques are major concerns but these can be relaxed if only mesoscopic parameters are needed. The project is a proof-of-concept computational laboratory for porous me-dia which delivers data needed for mesoscale simulations by performing microscale computational simulations