Modeling of unsteady transitional boundary layers

In turbomachinery, a considerable proportion of the blade surface area can be covered by transitional boundary layers. This means that accurate prediction of the profile loss and boundary layer behavior in general depends on the accurate modeling of the transitional boundary layers, especially at low Reynolds numbers. This paper presents a model for determining the intermittency resulting from the unsteady transition caused by the passage of wakes over a blade surface. The model is founded on work by Emmons (1951) who showed that the intermittency could be calculated from a knowledge of the behavior of randomly formed turbulent spots. The model is used to calculate the development of the boundary layer on the rotor of a low Reynolds number single-stage turbine. The predictions are compared with experimental results obtained using surface-mounted hot-film anemometers and hot-wire traverses of the rotor midspan boundary layer at two different rotor-stator gaps. The validity and limitations of the model are discussed.

Intermittency transport modeling of separated flow transition

An intermittency transport model is proposed for modeling separated-flow transition. The model is based on earlier work on prediction of attached flow bypass transition and is applied for the first time to model transition in a separation bubble at various degrees of free-stream turbulence. The model has been developed so that it takes into account the entrainment of the surrounding fluid. Experimental investigations suggest that it is this phenomena which ultimately determines the extent of the separation bubble. Transition onset is determined via a boundary layer correlation based on momentum thickness at the point of separation. The intermittent flow characteristic of the transition process is modeled via an intermittency transport equation. This accounts for both normal and streamwise variation of intermittency and hence models the entrainment of surrounding flow in a more accurate manner than alternative prescribed intermittency models. The model has been validated against the well established T3L semicircular leading edge flat plate test case for three different degrees of free-stream turbulence characteristic of turbomachinery blade applications.

Modeling of MOS-side carrier injection in trench-gate IGBTs

A compact trench-gate IGBT model that captures MOS-side carrier injection is developed. The model retains the simplicity of a one-dimensional solution to the ambipolar diffusion equation, but at the same time captures MOS-side carrier injection and its effects on steady-state carrier distribution in the drift region and on switching waveforms. © 2007 IEEE.

Gaussian mixture modeling with Gaussian process latent variable models

Density modeling is notoriously difficult for high dimensional data. One approach to the problem is to search for a lower dimensional manifold which captures the main characteristics of the data. Recently, the Gaussian Process Latent Variable Model (GPLVM) has successfully been used to find low dimensional manifolds in a variety of complex data. The GPLVM consists of a set of points in a low dimensional latent space, and a stochastic map to the observed space. We show how it can be interpreted as a density model in the observed space. However, the GPLVM is not trained as a density model and therefore yields bad density estimates. We propose a new training strategy and obtain improved generalisation performance and better density estimates in comparative evaluations on several benchmark data sets. © 2010 Springer-Verlag.

Trimeresurus stejnegeri snake venom plasminogen activator - Site-directed mutagenesis and molecular modeling

The specific plasminogen activator from Trimeresurus stejnegeri venom (TSV-PA) is a serine proteinase presenting 23% sequence identity with the proteinase domain of tissue type plasminogen activator, and 63% with batroxobin, a fibrinogen clotting enzyme from Bothrops atrox venom that does not activate plasminogen. TSV-PA contains six disulfide bonds and has been successfully overexpressed in Escherichia coli (Zhang, Y., Wisner, A., Xiong, Y. L,, and Bon, C, (1995) J. Biol. Chem. 270, 10246-10255), To identify the functional domains of TSV-PA, we focused on three short peptide fragments of TSV-PA showing important sequence differences with batroxobin and other venom serine proteinases. Molecular modeling shows that these sequences are located in surface loop regions, one of which is next to the catalytic site, When these sequences were replaced in TSV-PA by the equivalent batroxobin residues none generated either fibrinogen-clotting or direct fibrinogenolytic activity, Two of the replacements had little effect in general and are not critical to the specificity of TSV-PA for plasminogen. Nevertheless, the third replacement, produced by the conversion of the sequence DDE 96a-98 to NVI, significantly increased the K-m for some tripeptide chromogenic substrates and resulted in undetectable plasminogen activation, indicating the key role that the sequence plays in substrate recognition by the enzyme.

Modeling and electrical measurement of transport AC loss in HTS-based superconducting coils for electric machines

AC loss can be a significant problem for any applications that utilize or produce an AC current or magnetic field, such as an electric machine. The authors are currently investigating the electromagnetic properties of high temperature superconductors with a particular focus on the AC loss in coils made from YBCO superconductors. In this paper, a 2D finite element model based on the H formulation is introduced. The model is then used to calculate the transport AC loss using both a bulk approximation and modeling the individual turns in a racetrack-shaped coil. The coil model is based on the superconducting stator coils used in the University of Cambridge EPEC Superconductivity Group's superconducting permanent magnet synchronous motor design. The transport AC loss of a stator coil is measured using an electrical method based on inductive compensation using a variable mutual inductance. The simulated results are compared with the experimental results, verifying the validity of the model, and ways to improve the accuracy of the model are discussed. © 2010 IEEE.

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.