On computations of the integrated space shuttle flowfield using overset grids

Numerical simulations using the thin-layer Navier-Stokes equations and chimera (overset) grid approach were carried out for flows around the integrated space shuttle vehicle over a range of Mach numbers. Body-conforming grids were used for all the component grids. Testcases include a three-component overset grid - the external tank (ET), the solid rocket booster (SRB) and the orbiter (ORB), and a five-component overset grid - the ET, SRB, ORB, forward and aft attach hardware, configurations. The results were compared with the wind tunnel and flight data. In addition, a Poisson solution procedure (a special case of the vorticity-velocity formulation) using primitive variables was developed to solve three-dimensional, irrotational, inviscid flows for single as well as overset grids. The solutions were validated by comparisons with other analytical or numerical solution, and/or experimental results for various geometries. The Poisson solution was also used as an initial guess for the thin-layer Navier-Stokes solution procedure to improve the efficiency of the numerical flow simulations. It was found that this approach resulted in roughly a 30 percent CPU time savings as compared with the procedure solving the thin-layer Navier-Stokes equations from a uniform free stream flowfield

Electrochemical micromachining: An Introduction

Copyright © 2016 The Author(s). Electrochemical machining (ECM) is a relatively new technique, only being introduced as a commercial technique within the last 70 years (1). A lot of research was conducted in the 1960s and 1970s but research on electrical discharge machining (EDM) around the same time slowed ECM research (2). The main influence for the development of ECM came from the aerospace industry where very hard alloys were required to be machined without leaving a defective layer in order to produce a component which would behave reliably (3). ECM was primarily used for the production of gas turbine blades (2) or to machine materials into complex shapes that would be difficult to machine using conventional machining methods (4). Tool wear is high and the metal removal rate is slow when machining hard materials with conventional machining methods such as milling. This increases the cost of the machining process overall and this method creates a defective layer on the machined surface (3). Whereas with ECM there is virtually no tool wear even when machining hard materials and it does not leave a defective layer on the machined surface. This paper reviews the application of electrochemical machining with regards to micro-manufacturing and present state of the art micro ECM considering different machined materials, electrolytes and conditions used.The research reported in this article was supported by the European Commission within the project ‘Minimizing Defects in Micro-Manufacturing Applications (MIDEMMA)’ (FP7-2011-NMP-ICT-FoF-285614)

On solving the compressible Navier-Stokes equations for unsteady flows at very low Mach numbers

The properties of a preconditioned, coupled, strongly implicit finite difference scheme for solving the compressible Navier-Stokes equations in primitive variables are investigated for two unsteady flows at low speeds, namely the impulsively started driven cavity and the startup of pipe flow. For the shear-driven cavity flow, the computational effort was observed to be nearly independent of Mach number, especially at the low end of the range considered. This Mach number independence was also observed for steady pipe flow calculations; however, rather different conclusions were drawn for the unsteady calculations. In the pressure-driven pipe startup problem, the compressibility of the fluid began to significantly influence the physics of the flow development at quite low Mach numbers. The present scheme was observed to produce the expected characteristics of completely incompressible flow when the Mach number was set at very low values. Good agreement with incompressible results available in the literature was observed

Application of viscous-inviscid interaction methods to transonic turbulent flows

Two different viscous-inviscid interaction schemes were developed for the analysis of steady, turbulent, transonic, separated flows over axisymmetric bodies. The viscous and inviscid solutions are coupled through the displacement concept using a transpiration velocity approach. In the semi-inverse interaction scheme, the viscous and inviscid equations are solved in an explicitly separate manner and the displacement thickness distribution is iteratively updated by a simple coupling algorithm. In the simultaneous interaction method, local solutions of viscous and inviscid equations are treated simultaneously, and the displacement thickness is treated as an unknown and is obtained as a part of the solution through a global iteration procedure. The inviscid flow region is described by a direct finite-difference solution of a velocity potential equation in conservative form. The potential equation is solved on a numerically generated mesh by an approximate factorization (AF2) scheme in the semi-inverse interaction method and by a successive line overrelaxation (SLOR) scheme in the simultaneous interaction method. The boundary-layer equations are used for the viscous flow region. The continuity and momentum equations are solved inversely in a coupled manner using a fully implicit finite-difference scheme

Intra- and inter-individual genetic differences in gene expression

Genetic variation is known to influence the amount of mRNA produced by a gene. Given that the molecular machines control mRNA levels of multiple genes, we expect genetic variation in the components of these machines would influence multiple genes in a similar fashion. In this study we show that this assumption is correct by using correlation of mRNA levels measured independently in the brain, kidney or liver of multiple, genetically typed, mice strains to detect shared genetic influences. These correlating groups of genes (CGG) have collective properties that account for 40-90% of the variability of their constituent genes and in some cases, but not all, contain genes encoding functionally related proteins. Critically, we show that the genetic influences are essentially tissue specific and consequently the same genetic variations in the one animal may up-regulate a CGG in one tissue but down-regulate the same CGG in a second tissue. We further show similarly paradoxical behaviour of CGGs within the same tissues of different individuals. The implication of this study is that this class of genetic variation can result in complex inter- and intra-individual and tissue differences and that this will create substantial challenges to the investigation of phenotypic outcomes, particularly in humans where multiple tissues are not readily available.

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Emergent global patterns of ecosystem structure and function from a mechanistic general ecosystem model

Anthropogenic activities are causing widespread degradation of ecosystems worldwide, threatening the ecosystem services upon which all human life depends. Improved understanding of this degradation is urgently needed to improve avoidance and mitigation measures. One tool to assist these efforts is predictive models of ecosystem structure and function that are mechanistic: based on fundamental ecological principles. Here we present the first mechanistic General Ecosystem Model (GEM) of ecosystem structure and function that is both global and applies in all terrestrial and marine environments. Functional forms and parameter values were derived from the theoretical and empirical literature where possible. Simulations of the fate of all organisms with body masses between 10 µg and 150,000 kg (a range of 14 orders of magnitude) across the globe led to emergent properties at individual (e.g., growth rate), community (e.g., biomass turnover rates), ecosystem (e.g., trophic pyramids), and macroecological scales (e.g., global patterns of trophic structure) that are in general agreement with current data and theory. These properties emerged from our encoding of the biology of, and interactions among, individual organisms without any direct constraints on the properties themselves. Our results indicate that ecologists have gathered sufficient information to begin to build realistic, global, and mechanistic models of ecosystems, capable of predicting a diverse range of ecosystem properties and their response to human pressures

Structure-based design of highly selective inhibitors of the CREB binding protein bromodomain

Chemical probes are required for preclinical target validation to interrogate novel biological targets and pathways. Selective inhibitors of the CREB binding protein (CREBBP)/EP300 bromodomains are required to facilitate the elucidation of biology associated with these important epigenetic targets. Medicinal chemistry optimization that paid particular attention to physiochemical properties delivered chemical probes with desirable potency, selectivity, and permeability attributes. An important feature of the optimization process was the successful application of rational structure-based drug design to address bromodomain selectivity issues (particularly against the structurally related BRD4 protein)

Electrochemical Nanoprobes for Single-Cell Analysis

The measurement of key molecules in individual cells with minimal disruption to the biological milieu is the next frontier in single-cell analyses. Nanoscale devices are ideal analytical tools because of their small size and their potential for high spatial and temporal resolution recordings. Here, we report the fabrication of disk-shaped carbon nanoelectrodes whose radius can be precisely tuned within the range 5–200 nm. The functionalization of the nanoelectrode with platinum allowed the monitoring of oxygen consumption outside and inside a brain slice. Furthermore, we show that nanoelectrodes of this type can be used to impale individual cells to perform electrochemical measurements within the cell with minimal disruption to cell function. These nanoelectrodes can be fabricated combined with scanning ion conductance microscopy probes, which should allow high resolution electrochemical mapping of species on or in living cells

Advanced Computational Thermal Studies and their Assessment for Supercritical-Pressure Reactors (SCRs)

The goal of this laboratory / university collaboration of coupled computational and experimental studies is the improvement of predictive methods for supercritical-pressure reactors. The general objective is to develop supporting knowledge needed of advanced computational techniques for the technology development of the concepts and their safety systems