Effects of soil fabric on behaviors of granular soils: Microscopic modeling

The effects of initial soil fabric on behaviors of granular soils are investigated by using Distinct Element Method (DEM) numerical simulation. Soil specimens are represented by an assembly of non-uniform sized spheres with different initial contact normal distributions. Isotropically consolidated triaxial compression loading and extension unloading in both undrained and drained conditions are simulated for vertically- and horizontally-sheared specimens. The numerical simulation results are compared qualitatively with the published experimental data and the effects of initial soil fabric on resulting soil behaviors are discussed, including the effects of specimen reconstitution methods, effects of large preshearing, and anisotropic characteristics in undrained and drained conditions. The effects of initial soil fabric and mode of shearing on the quasi-steady state line are also investigated. The numerical simulation results can systematically explain that the observed experimental behaviors of granular soils are due principally to their conditions of the initial soil fabric. This outcome provides insights into the observed phenomena in microscopic view. © 2011 Elsevier Ltd.

Modeling evaporation effects in conditional moment closure for spray autoignition

Simulations of an n-heptane spray autoigniting under conditions relevant to a diesel engine are performed using two-dimensional, first-order conditional moment closure (CMC) with full treatment of spray terms in the mixture fraction variance and CMC equations. The conditional evaporation term in the CMC equations is closed assuming interphase exchange to occur at the droplet saturation mixture fraction values only. Modeling of the unclosed terms in themixture fraction variance equation is done accordingly. Comparison with experimental data for a range of ambient oxygen concentrations shows that the ignition delay is overpredicted. The trend of increasing ignition delay with decreasing oxygen concentration, however, is correctly captured. Good agreement is found between the computed and measured flame lift-off height for all conditions investigated. Analysis of source terms in the CMC temperature equation reveals that a convective-reactive balance sets in at the flame base, with spatial diffusion terms being important, but not as important as in lifted jet flames in cold air. Inclusion of droplet terms in the governing equations is found to affect the mixture fraction variance field in the region where evaporation is the strongest, and to slightly increase the ignition delay time due to the cooling associated with the evaporation. Both flame propagation and stabilization mechanisms, however, remain unaffected. © 2011 Taylor & Francis.

A FEniCS-based programming framework for modeling turbulent flow by the Reynolds-averaged Navier-Stokes equations

Finding an appropriate turbulence model for a given flow case usually calls for extensive experimentation with both models and numerical solution methods. This work presents the design and implementation of a flexible, programmable software framework for assisting with numerical experiments in computational turbulence. The framework targets Reynolds-averaged Navier-Stokes models, discretized by finite element methods. The novel implementation makes use of Python and the FEniCS package, the combination of which leads to compact and reusable code, where model- and solver-specific code resemble closely the mathematical formulation of equations and algorithms. The presented ideas and programming techniques are also applicable to other fields that involve systems of nonlinear partial differential equations. We demonstrate the framework in two applications and investigate the impact of various linearizations on the convergence properties of nonlinear solvers for a Reynolds-averaged Navier-Stokes model. © 2011 Elsevier Ltd.

A novel short neurotoxin, cobrotoxin c, from monocellate cobra (Naja kaouthia) venom: isolation and purification, primary and secondary structure determination, and tertiary structure modeling

A novel short neurotoxin, cobrotoxin c (CBT C) was isolated from the venom of monocellate cobra (Naja kaouthia) using a combination of ion-exchange chromatography and FPLC. Its primary structure was determined by Edman degradation. CBT C is composed of 61 amino acid residues. It differs from cobrotoxin b (CBT B) by only two amino acid substitutions, Thr/Ala11 and Arg/Thr56, which are not located on the functionally important regions by sequence similarity. However, the LD50 is 0.08 mg/g to mice, i.e. approximately five-fold higher than for CBT B. Strikingly, a structure-function relationship analysis suggests the existence of a functionally important domain on the outside of Loop III of CBT C. The functionally important basic residues on the outside of Loop III might have a pairwise interaction with alpha subunit, instead of gamma or delta subunits of the nicotinic acetylcholine receptor (nAChR). (C) 2002 Elsevier Science Inc. All rights reserved.

Structural analysis of human CCR2b and primate CCR2b by molecular modeling and molecular dynamics simulation

CCR2b, a chemokine receptor for MCP-1, -2, -3, -4, plays an important role in a variety of diseases involving infection, inflammation, and/or injury, as well as being a coreceptor for HIV-1 infection. Two models of human CCR2b (hCCR2b) were generated by h

Modular risk modeling and management of water infrastructure disaster incidents

Water supply and wastewater control are critical elements of society's infrastructure. The objective of this study will be to provide a generic risk assessment tool to provide municipalities and the nation as a whole with a quantifiable assessment of their vulnerability to water infrastructure threats. The approach will prioritize countermeasures and identify where research and development is required to further minimize risk. This paper outlines the current context, primary concerns and state-of-the art in critical infrastructure risk management for the water sector and proposes a novel approach to resolve existing questions in the field. The proposed approach is based on a modular framework that derives a quantitative risk index for varied domains of interest. The approach methodology is scaleable and based on formal definitions of event probability and severity. The framework is equally applicable to natural and human-induced hazard types and can be used for analysis of compound risk events.