Ignition Delay Times of Kerosene (Jet-A)/Air Mixtures

Ignition of Jet-A/air mixtures was studied behind reflected shock waves. Heating of shock tube at temperature of 150 C was used to prepare a homogeneous fuel mixture. Ignition delay times were measured from OH emission at 309 nm and from absorption of He-Ne laser radiation at 3.3922 micrometers. The conditions behind shock waves were calculated by one-dimensional shock wave theory from initial conditions T1, P1, mixture composition and incident shock wave velocity. The ignition delay times were obtained at two fixed pressures 10, 20 atm for lean, stoichiometric and rich mixtures (ER=0.5, 1, 2) at an overall temperature range of 1040-1380 K.Comment: V.P. Zhukov, V.A. Sechenov, and A.Yu. Starikovskii, Ignition Delay Times of Kerosene(Jet-A)/Air Mixtures, 31st Symposium on Combustion, Heidelberg, Germany, August 6-11, 200

Nambu-Goto Strings from SU(N) Born-Infeld model

The spectrum of quenched Yang-Mills theory in the large-N limit displays strings and higher dimensional extended objects. The effective dynamics of string-like excitations is encoded into area preserving Schild action. In this letter, we bridge the gap between SU(N) gauge models and fully reparametrization invariant Nambu-Goto string models by introducing an extra matrix degree of freedom in the Yang-Mills action. In the large-N limit this matrix variable becomes the world-sheet auxiliary field allowing a smooth transition between the Schild and Nambu-Goto strings. The new improved matrix model we propose here can be extended to p-branes provided we enlarge the dimensionality of the target spacetime.Comment: 11pages, no figures, LateX2e; added discussio

Exploration of Possible Quantum Gravity Effects with Neutrinos II: Lorentz Violation in Neutrino Propagation

It has been suggested that the interactions of energetic particles with the foamy structure of space-time thought to be generated by quantum-gravitational (QG) effects might violate Lorentz invariance, so that they do not propagate at a universal speed of light. We consider the limits that may be set on a linear or quadratic violation of Lorentz invariance in the propagation of energetic neutrinos, v/c=[1 +- (E/M_\nuQG1)] or [1 +- (E/M_\nu QG2}^2], using data from supernova explosions and the OPERA long-baseline neutrino experiment.Comment: 8 pages, 6 figures, proceedings for invited talk by A.Sakharov at DISCRETE'08, Valencia, Spain; December 200

Singularity Structure and Stability Analysis of the Dirac Equation on the Boundary of the Nutku Helicoid Solution

Dirac equation written on the boundary of the Nutku helicoid space consists of a system of ordinary differential equations. We tried to analyze this system and we found that it has a higher singularity than those of the Heun's equations which give the solutions of the Dirac equation in the bulk. We also lose an independent integral of motion on the boundary. This facts explain why we could not find the solution of the system on the boundary in terms of known functions. We make the stability analysis of the helicoid and catenoid cases and end up with an appendix which gives a new example where one encounters a form of the Heun equation.Comment: Version to appear in JM

Floral Morphogenesis: Stochastic Explorations of a Gene Network Epigenetic Landscape

In contrast to the classical view of development as a preprogrammed and deterministic process, recent studies have demonstrated that stochastic perturbations of highly non-linear systems may underlie the emergence and stability of biological patterns. Herein, we address the question of whether noise contributes to the generation of the stereotypical temporal pattern in gene expression during flower development. We modeled the regulatory network of organ identity genes in the Arabidopsis thaliana flower as a stochastic system. This network has previously been shown to converge to ten fixed-point attractors, each with gene expression arrays that characterize inflorescence cells and primordial cells of sepals, petals, stamens, and carpels. The network used is binary, and the logical rules that govern its dynamics are grounded in experimental evidence. We introduced different levels of uncertainty in the updating rules of the network. Interestingly, for a level of noise of around 0.5–10%, the system exhibited a sequence of transitions among attractors that mimics the sequence of gene activation configurations observed in real flowers. We also implemented the gene regulatory network as a continuous system using the Glass model of differential equations, that can be considered as a first approximation of kinetic-reaction equations, but which are not necessarily equivalent to the Boolean model. Interestingly, the Glass dynamics recover a temporal sequence of attractors, that is qualitatively similar, although not identical, to that obtained using the Boolean model. Thus, time ordering in the emergence of cell-fate patterns is not an artifact of synchronous updating in the Boolean model. Therefore, our model provides a novel explanation for the emergence and robustness of the ubiquitous temporal pattern of floral organ specification. It also constitutes a new approach to understanding morphogenesis, providing predictions on the population dynamics of cells with different genetic configurations during development

Tunable Excitons in Biased Bilayer Graphene

Recent measurements have shown that a continuously tunable bandgap of up to 250 meV can be generated in biased bilayer graphene [Y. Zhang et al., Nature 459, 820 (2009)], opening up pathway for possible graphene-based nanoelectronic and nanophotonic devices operating at room temperature. Here, we show that the optical response of this system is dominated by bound excitons. The main feature of the optical absorbance spectrum is determined by a single symmetric peak arising from excitons, a profile that is markedly different from that of an interband transition picture. Under laboratory conditions, the binding energy of the excitons may be tuned with the external bias going from zero to several tens of meV's. These novel strong excitonic behaviors result from a peculiar, effective ``one-dimensional'' joint density of states and a continuously-tunable bandgap in biased bilayer graphene. Moreover, we show that the electronic structure (level degeneracy, optical selection rules, etc.) of the bound excitons in a biased bilayer graphene is markedly different from that of a two-dimensional hydrogen atom because of the pseudospin physics

Identifying emergent dynamical structures in network models

The identification of emergent structures in dynamical systems is a major challenge in complex systems science. In particular, the formation of intermediate-level dynamical structures is of particular interest for what concerns biological as well as artificial network models. In this work, we present a new technique aimed at identifying clusters of nodes in a network that behave in a coherent and coordinated way and that loosely interact with the remainder of the system. This method is based on an extension of a measure introduced for detecting clusters in biological neural networks. Even if our results are still preliminary, we have evidence for showing that our approach is able to identify these \u201cemerging things\u201d in some artificial network models and that it is way more powerful than usual measures based on statistical correlation. This method will make it possible to identify mesolevel dynamical structures in network models in general, from biological to social network

Experimental review of oxygen content at mixing layer in cone calorimeter

This work aims to elucidate whether the hypothesis of zero oxygen at the mixture layer when flame takes place is assumable for every kind of material. For that purpose, we investigated the oxygen concentration there by cone calorimeter tests. A modified holder was developed in order to collect oxygen in this mixture layer. In addition, thermogravimetric tests were carried out so as to relate the possible effects of the presence of oxygen in the atmosphere where the pyrolysis process takes place, since the cone calorimeter does not allow to control the oxygen level of the atmosphere during the experiment. The reaction rates and per cent of residue in the cone calorimetric tests were measured and compared with the results from thermogravimetric tests. Six products were analysed which can be classified in three main groups: lignocellulosic, thermoplastic polymers and thermoset polymers. Cone calorimetric results showed that for some of the materials analysed (PET, Nylon and PUR foam) the oxygen level at mixture layer decreased until values close to zero. The comparison of reaction rates between cone calorimetric and thermogravimetric tests revealed the char layer created in cone calorimetric tests over the exposed face for brushed fir, Nylon and PET established an important heat barrier that modifies the thermal behaviour of these materials.Authors would like to thank to the Spanish Ministry of Economy and Competitiveness for the PYRODESIGN Project grant, Ref.: BIA2012-37890, financed jointly by FEDER funds

Pyrolysis of medium-density fiberboard: optimized search for kinetics scheme and parameters via a genetic algorithm driven by Kissinger's method

The pyrolysis kinetics of charring materials plays an important role in understanding material combustions especially for construction materials with complex degradation chemistry. Thermogravimetric analysis (TGA) is frequently used to study the heterogeneous kinetics of solid fuels; however, there is no agreed method to determine the pyrolysis scheme and kinetic parameters for charring polymers with multiple components and competing reaction pathways. This study develops a new technique to estimate the possible numbers of species and sub-reactions in pyrolysis by analyzing the second derivatives of thermogravimetry (DDTG) curves. The pyrolysis of a medium-density fiberboard (MDF) in nitrogen is studied in detail, and the DDTG curves are used to locate the temperature of the peak mass-loss rate for each sub-reaction. Then, on the basis of the TG data under multiple heating rates, Kissinger’s method is used to quickly find the possible range of values of the kinetic parameters (<i>A</i> and <i>E</i>). These ranges are used to accelerate the optimization of the inverse problem using a genetic algorithm (GA) for the kinetic and stoichiometric parameters. The proposed method and kinetic scheme found are shown to match the experimental data and are able to predict accurately results at different heating rates better than Kissinger’s method. Moreover, the search method (K–K method) is highly efficient, faster than the regular GA search alone. Modeling results show that, as the TG data available increase, the interdependence among kinetic parameters becomes weak and the accuracy of the first-order model declines. Furthermore, conducting TG experiment under multiple heating rates is found to be crucial in obtaining good kinetic parameters