Self-supported aluminum thin films produced by vacuum deposition process

Self-supported aluminum thin film is produced by vacuum depositing the film on a polyvinyl formal resin film and then removing the resin by radiant heating in the vacuum. The aluminum film can be used as soon as the resin is eliminated

Efficient aerodynamic derivative calculation in three-dimensional transonic flow

ABSTRACTOne key task in computational aeroelasticity is to calculate frequency response functions of aerodynamic coefficients due to structural excitation or external disturbance. Computational fluid dynamics methods are applied for this task at edge-of-envelope flow conditions. Assuming a dynamically linear response around a non-linear steady state, two computationally efficient approaches in time and frequency domain are discussed. A non-periodic, time-domain function can be used, on the one hand, to excite a broad frequency range simultaneously giving the frequency response function in a single non-linear, time-marching simulation. The frequency-domain approach, on the other hand, solves a large but sparse linear system of equations, resulting from the linearisation about the non-linear steady state for each frequency of interest successively. Results are presented for a NACA 0010 aerofoil and a generic civil aircraft configuration in very challenging transonic flow conditions with strong shock-wave/boundary-layer interaction in the pre-buffet regime. Computational cost savings of up to 1 order of magnitude are observed in the time domain for the all-frequencies-at-once approach compared with single-frequency simulations, while an additional order of magnitude is obtained for the frequency-domain method. The paper demonstrates the readiness of computational aeroelasticity tools at edge-of-envelope flow conditions.</jats:p

Stable Irregular Dynamics in Complex Neural Networks

For infinitely large sparse networks of spiking neurons mean field theory shows that a balanced state of highly irregular activity arises under various conditions. Here we analytically investigate the microscopic irregular dynamics in finite networks of arbitrary connectivity, keeping track of all individual spike times. For delayed, purely inhibitory interactions we demonstrate that the irregular dynamics is not chaotic but rather stable and convergent towards periodic orbits. Moreover, every generic periodic orbit of these dynamical systems is stable. These results highlight that chaotic and stable dynamics are equally capable of generating irregular activity.Comment: 10 pages, 2 figure

Influence of gust modelling on free-flight aerofoils

Gust analysis is one key task during design and certification of new aircraft. In the industrial standard, the gust is modelled as a disturbance in velocity and is superposed with the general velocity field surrounding the aircraft. The shape, typically sinusoidal or 1-cos, is uniform in vertical direction and is not changing while travelling through the computational domain. These assumptions known as the field or disturbance velocity method facilitate an efficient way of simulating gust encounter within computational fluid dynamics methods. However, how this frozen gust model effects the accuracy of loads predictions compared to more-realistic models remains an open question. A novel approach to simulate a so-called resolved gust is presented herein. An initial perturbation of the x-velocity is prescribed using a 1-cos shape in two spatial directions. Disturbances in vertical velocity as well as density and pressure are developing after some simulated time. Results are compared to the field-velocity method using the CRANK aerofoil covering subsonic and transonic flow conditions. Lift and moment responses are analysed as well as time histories of velocities at different grid locations. Furthermore, a second aerofoil is added as a horizontal tail-plane to represent a large civil aircraft. This configuration is used to include the effects of flight dynamics while analysing the responses due to the two gust models

Rapid gust response simulation of large civil aircraft using computational fluid dynamics

ABSTRACTSeveral critical load cases during the aircraft design process result from atmospheric turbulence. Thus, rapidly performable and highly accurate dynamic response simulations are required to analyse a wide range of parameters. A method is proposed to predict dynamic loads on an elastically trimmed, large civil aircraft using computational fluid dynamics in conjunction with model reduction. A small-sized modal basis is computed by sampling the aerodynamic response at discrete frequencies and applying proper orthogonal decomposition. The linear operator of the Reynolds-averaged Navier-Stokes equations plus turbulence model is then projected onto the subspace spanned by this basis. The resulting reduced system is solved at an arbitrary number of frequencies to analyse responses to 1-cos gusts very efficiently. Lift coefficient and surface pressure distribution are compared with full-order, non-linear, unsteady time-marching simulations to verify the method. Overall, the reduced-order model predicts highly accurate global coefficients and surface loads at a fraction of the computational cost, which is an important step towards the aircraft loads process relying on computational fluid dynamics.</jats:p

Sequential Desynchronization in Networks of Spiking Neurons with Partial Reset

The response of a neuron to synaptic input strongly depends on whether or not it has just emitted a spike. We propose a neuron model that after spike emission exhibits a partial response to residual input charges and study its collective network dynamics analytically. We uncover a novel desynchronization mechanism that causes a sequential desynchronization transition: In globally coupled neurons an increase in the strength of the partial response induces a sequence of bifurcations from states with large clusters of synchronously firing neurons, through states with smaller clusters to completely asynchronous spiking. We briefly discuss key consequences of this mechanism for more general networks of biophysical neurons

Model reduction for gust load analysis of free-flying aircraft

The coupling of computational fluid dynamics and rigid body dynamics promises enhanced multidisciplinary simulation capability for aircraft design and certification. Industrial application of such coupled simulations is limited however by computational cost. In this context, model reduction can retain the fidelity of the underlying model while decreasing the computational effort. A model reduction technique is presented herein based on modal decomposition and projection of the non-linear residual function. Flight dynamics eigenmodes are obtained with an operator-based identification procedure which is capable of calculating these global modes of the coupled Jacobian matrix also for an industrial use case with nearly 50 million degrees-of-freedom. Additional modes based on proper orthogonal decomposition to describe the aerodynamic response due to gust encounter are combined with the eigenmode basis. Results are presented for initial disturbance analysis using flight dynamics modes only and for gust encounter simulations using the combined modal basis. Overall, the reduced model is capable of predicting the full order results accurately

Using Single Molecule mRNA Fluorescent \u3ci\u3ein Situ\u3c/i\u3e Hybridization (RNA-FISH) to Quantify mRNAs in Individual Murine Oocytes and Embryos

Changes in abundance of mRNAs during oocyte growth and maturation and during pre-implantation embryo development have been documented using quantitative real-time RT-PCR (qPCR), microarray analyses, and whole genome sequencing. However, these techniques require amplification of mRNAs, normalization using housekeeping genes, can be biased for abundant transcripts, and/or require large numbers of oocytes and embryos which can be difficult to acquire from mammalian species. We optimized a single molecule RNA fluorescence in situ hybridization (RNA-FISH) protocol, which amplifies fluorescence signal to detect candidate transcripts, for use with individual oocytes and embryos. Quantification using the software Localize showed patterns of Gdf9 and Pou5f1 mRNA expression in oocytes and embryos that were consistent with previously published data. Interestingly, low levels of Nanog mRNA were also accurately and reproducibly measured in oocytes and one- and two-cell embryos suggesting that RNA-FISH could be used to detect and quantify low abundance transcripts. Unlike other techniques, RNA-FISH is also able to detect changes in the localization patterns of mRNAs which may be used to monitor post-transcriptional regulation of a transcript. Thus, RNA-FISH represents an important technique to investigate potential mechanisms associated with the synthesis and stability of candidate mRNAs in mammalian oocytes and embryos

Counting Complex Disordered States by Efficient Pattern Matching: Chromatic Polynomials and Potts Partition Functions

Counting problems, determining the number of possible states of a large system under certain constraints, play an important role in many areas of science. They naturally arise for complex disordered systems in physics and chemistry, in mathematical graph theory, and in computer science. Counting problems, however, are among the hardest problems to access computationally. Here, we suggest a novel method to access a benchmark counting problem, finding chromatic polynomials of graphs. We develop a vertex-oriented symbolic pattern matching algorithm that exploits the equivalence between the chromatic polynomial and the zero-temperature partition function of the Potts antiferromagnet on the same graph. Implementing this bottom-up algorithm using appropriate computer algebra, the new method outperforms standard top-down methods by several orders of magnitude, already for moderately sized graphs. As a first application, we compute chromatic polynomials of samples of the simple cubic lattice, for the first time computationally accessing three-dimensional lattices of physical relevance. The method offers straightforward generalizations to several other counting problems.Comment: 7 pages, 4 figure

Nrf2 and Nrf2-related proteins in development and developmental toxicity : insights from studies in zebrafish (Danio rerio)

© The Author(s), 2015. This is the author's version of the work and is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Free Radical Biology and Medicine 88B (2015): 275-289, doi:10.1016/j.freeradbiomed.2015.06.022.Oxidative stress is an important mechanism of chemical toxicity, contributing to developmental toxicity and teratogenesis as well as to cardiovascular and neurodegenerative diseases and diabetic embryopathy. Developing animals are especially sensitive to effects of chemicals that disrupt the balance of processes generating reactive species and oxidative stress, and those anti-oxidant defenses that protect against oxidative stress. The expression and inducibility of anti-oxidant defenses through activation of NFE2-related factor 2 (Nrf2) and related proteins is an essential process affecting the susceptibility to oxidants, but the complex interactions of Nrf2 in determining embryonic response to oxidants and oxidative stress are only beginning to be understood. The zebrafish (Danio rerio) is an established model in developmental biology and now also in developmental toxicology and redox signaling. Here we review the regulation of genes involved in protection against oxidative stress in developing vertebrates, with a focus on Nrf2 and related cap’n’collar (CNC)-basic-leucine zipper (bZIP) transcription factors. Vertebrate animals including zebrafish share Nfe2, Nrf1, Nrf2, and Nrf3 as well as a core set of genes that respond to oxidative stress, contributing to the value of zebrafish as a model system with which to investigate the mechanisms involved in regulation of redox signaling and the response to oxidative stress during embryolarval development. Moreover, studies in zebrafish have revealed nrf and keap1 gene duplications that provide an opportunity to dissect multiple functions of vertebrate NRF genes, including multiple sensing mechanisms involved in chemical-specific effects.This work was supported in part by National Institutes of Health grants R01ES016366 (MEH), R01ES015912 (JJS), and F32ES017585 (ART-L).2016-06-2