Modeling of dilution jet flowfields

The present paper will compare temperature field measurements from selected cases in these investigations with distributions calculated with an empirical model based on assumed vertical profile similarity and superposition and with a 3-D elliptic code using a standard K-E turbulence model. The results will show the capability (or lack thereof) of the models to predict the effects of the principle flow and geometric variables

On modeling dilution jet flowfields

This paper compares temperature field measurements from selected experiments on a single row, and opposed rows, of jets injected into a ducted crossflow with profiles calculated using an empirical model based on assumed vertical profile similarity and superposition, and distributions calculated with a 3-D elliptic code using a standard K-E turbulence model. The empirical model predictions are very good within the range of the generating experiments, and the numerical model resultings, although exhibiting too little mixing, correctly describe the effects of the principal flow and geometric variables

Qualitative System Identification from Imperfect Data

Experience in the physical sciences suggests that the only realistic means of understanding complex systems is through the use of mathematical models. Typically, this has come to mean the identification of quantitative models expressed as differential equations. Quantitative modelling works best when the structure of the model (i.e., the form of the equations) is known; and the primary concern is one of estimating the values of the parameters in the model. For complex biological systems, the model-structure is rarely known and the modeler has to deal with both model-identification and parameter-estimation. In this paper we are concerned with providing automated assistance to the first of these problems. Specifically, we examine the identification by machine of the structural relationships between experimentally observed variables. These relationship will be expressed in the form of qualitative abstractions of a quantitative model. Such qualitative models may not only provide clues to the precise quantitative model, but also assist in understanding the essence of that model. Our position in this paper is that background knowledge incorporating system modelling principles can be used to constrain effectively the set of good qualitative models. Utilising the model-identification framework provided by Inductive Logic Programming (ILP) we present empirical support for this position using a series of increasingly complex artificial datasets. The results are obtained with qualitative and quantitative data subject to varying amounts of noise and different degrees of sparsity. The results also point to the presence of a set of qualitative states, which we term kernel subsets, that may be necessary for a qualitative model-learner to learn correct models. We demonstrate scalability of the method to biological system modelling by identification of the glycolysis metabolic pathway from data

The Mass-Loss Return From Evolved Stars to The Large Magellanic Cloud VI: Luminosities and Mass-Loss Rates on Population Scales

We present results from the first application of the Grid of Red Supergiant and Asymptotic Giant Branch ModelS (GRAMS) model grid to the entire evolved stellar population of the Large Magellanic Cloud (LMC). GRAMS is a pre-computed grid of 80,843 radiative transfer (RT) models of evolved stars and circumstellar dust shells composed of either silicate or carbonaceous dust. We fit GRAMS models to ~30,000 Asymptotic Giant Branch (AGB) and Red Supergiant (RSG) stars in the LMC, using 12 bands of photometry from the optical to the mid-infrared. Our published dataset consists of thousands of evolved stars with individually determined evolutionary parameters such as luminosity and mass-loss rate. The GRAMS grid has a greater than 80% accuracy rate discriminating between Oxygen- and Carbon-rich chemistry. The global dust injection rate to the interstellar medium (ISM) of the LMC from RSGs and AGB stars is on the order of 1.5x10^(-5) solar masses/yr, equivalent to a total mass injection rate (including the gas) into the ISM of ~5x10^(-3) solar masses/yr. Carbon stars inject two and a half times as much dust into the ISM as do O-rich AGB stars, but the same amount of mass. We determine a bolometric correction factor for C-rich AGB stars in the K band as a function of J - K color, BC(K) = -0.40(J-K)^2 + 1.83(J-K) + 1.29. We determine several IR color proxies for the dust mass-loss rate (MLR) from C-rich AGB stars, such as log (MLR) = (-18.90)/((K-[8.0])+3.37)-5.93. We find that a larger fraction of AGB stars exhibiting the `long-secondary period' phenomenon are O-rich than stars dominated by radial pulsations, and AGB stars without detectable mass-loss do not appear on either the first-overtone or fundamental-mode pulsation sequences.Comment: 19 pages, 19 figure

Experiments in dilution jet mixing

Experimental results are given on the mixing of a single row of jets with an isothermal mainstream in a straight duct, to include flow and geometric variations typical of combustion chambers in gas turbine engines. The principal conclusions reached from these experiments were: at constant momentum ratio, variations in density ratio have only a second-order effect on the profiles; a first-order approximation to the mixing of jets with a variable temperature mainstream can be obtained by superimposing the jets-in-an isothermal-crossflow and mainstream profiles; flow area convergence, especially injection-wall convergence, significantly improves the mixing; for opposed rows of jets, with the orifice centerlines in-line, the optimum ratio of orifice spacing to duct height is one half of the optimum value for single side injection at the same momentum ratio; and for opposed rows of jets, with the orifice centerlines staggered, the optimum ratio of orifice spacing to duct height is twice the optimum value for single side injection at the same momentum ratio

Method of complex paths and general covariance of Hawking radiation

We apply the technique of complex paths to obtain Hawking radiation in different coordinate representations of the Schwarzschild space-time. The coordinate representations we consider do not possess a singularity at the horizon unlike the standard Schwarzschild coordinate. However, the event horizon manifests itself as a singularity in the expression for the semi-classical action. This singularity is regularized by using the method of complex paths and we find that Hawking radiation is recovered in these coordinates indicating the covariance of Hawking radiation. This also shows that there is no correspondence between the particles detected by the model detector and the particle spectrum obtained by the quantum field theoretic analysis -- a result known in other contexts as well.Comment: 9 pages, uses MPLA Style file, Accepted for publication in Mod. Phys. Letts.

Bubbling route to strange nonchaotic attractor in a nonlinear series LCR circuit with a nonsinusoidal force

We identify a novel route to the birth of a strange nonchaotic attractor (SNA) in a quasiperiodically forced electronic circuit with a nonsinusoidal (square wave) force as one of the quasiperiodic forces through numerical and experimental studies. We find that bubbles appear in the strands of the quasiperiodic attractor due to the instability induced by the additional square wave type force. The bubbles then enlarge and get increasingly wrinkled as a function of the control parameter. Finally, the bubbles get extremely wrinkled (while the remaining parts of the strands of the torus remain largely unaffected) resulting in the birth of the SNA which we term as the \emph{bubbling route to SNA}. We characterize and confirm this birth from both experimental and numerical data by maximal Lyapunov exponents and their variance, Poincar\'e maps, Fourier amplitude spectra and spectral distribution function. We also strongly confirm the birth of SNA via the bubbling route by the distribution of the finite-time Lyapunov exponents.Comment: 11 pages. 11 figures, Accepted for publication in Phys. Rev.

Tribological properties of sintered polycrystalline and single crystal silicon carbide

Tribological studies and X-ray photoelectron spectroscopy analyses were conducted with sintered polycrystalline and single crystal silicon carbide surfaces in sliding contact with iron at various temperatures to 1500 C in a vacuum of 30 nPa. The results indicate that there is a significant temperature influence on both the friction properties and the surface chemistry of silicon carbide. The main contaminants on the as received sintered polycrystalline silicon carbide surfaces are adsorbed carbon, oxygen, graphite, and silicon dioxide. The surface revealed a low coefficient of friction. This is due to the presence of the graphite on the surface. At temperatures of 400 to 600 C graphite and copious amount of silicon dioxide were observed on the polycrystalline silicon carbide surface in addition to silicon carbide. At 800 C, the amount of the silicon dioxide decreased rapidly and the silicon carbide type silicon and carbon peaks were at a maximum intensity in the XPS spectra. The coefficients of friction were high in the temperature range 400 to 800 C. Small amounts of carbon and oxygen contaminants were observed on the as received single crystal silicon carbide surface below 250 C. Silicon carbide type silicon and carbon peaks were seen on the silicon carbide in addition to very small amount of graphite and silicon dioxide at temperatures of 450 to 800 C