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Title: Quantitative estimation of the static and dynamic parameters of Jet-A-air detonation from the first principle calulations.

Abstract

No abstract prepared.

Authors:
; ; ; ; ; ; ; ; ; ; ; ; ; ; ; ;
Publication Date:
Research Org.:
Argonne National Lab. (ANL), Argonne, IL (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
982327
Report Number(s):
ANL/NE/CP-57576
TRN: US201013%%1005
DOE Contract Number:
DE-AC02-06CH11357
Resource Type:
Conference
Resource Relation:
Conference: 8th Asia-Pacific International Symposium on Combustion and Energy Utilization; Oct. 10, 2006 - Oct. 12, 2006; Sochi, Russian Federation
Country of Publication:
United States
Language:
ENGLISH
Subject:
02 PETROLEUM; 32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION; AIR; CALCULATION METHODS; COMBUSTION; DYNAMICS; JET ENGINE FUELS; MIXTURES

Citation Formats

Strelkova, M. I., Kirillov, I. A., Potapkin, B. V., Umanskiy, S. Ya., Bagaturyants, A. A., Safonov, A., Liventsov, V. V., Deminsky, M. A., Dean, T., Varatharajan, B., Tentner, A., RRC Kurchatov Inst., Kinetic Technologies Lab., N.N. Semenov Inst. of Chemical Physics, Russian Academy of Science, Moscow State Univ., and GE Global Research. Quantitative estimation of the static and dynamic parameters of Jet-A-air detonation from the first principle calulations.. United States: N. p., 2007. Web.
Strelkova, M. I., Kirillov, I. A., Potapkin, B. V., Umanskiy, S. Ya., Bagaturyants, A. A., Safonov, A., Liventsov, V. V., Deminsky, M. A., Dean, T., Varatharajan, B., Tentner, A., RRC Kurchatov Inst., Kinetic Technologies Lab., N.N. Semenov Inst. of Chemical Physics, Russian Academy of Science, Moscow State Univ., & GE Global Research. Quantitative estimation of the static and dynamic parameters of Jet-A-air detonation from the first principle calulations.. United States.
Strelkova, M. I., Kirillov, I. A., Potapkin, B. V., Umanskiy, S. Ya., Bagaturyants, A. A., Safonov, A., Liventsov, V. V., Deminsky, M. A., Dean, T., Varatharajan, B., Tentner, A., RRC Kurchatov Inst., Kinetic Technologies Lab., N.N. Semenov Inst. of Chemical Physics, Russian Academy of Science, Moscow State Univ., and GE Global Research. Mon . "Quantitative estimation of the static and dynamic parameters of Jet-A-air detonation from the first principle calulations.". United States. doi:.
@article{osti_982327,
title = {Quantitative estimation of the static and dynamic parameters of Jet-A-air detonation from the first principle calulations.},
author = {Strelkova, M. I. and Kirillov, I. A. and Potapkin, B. V. and Umanskiy, S. Ya. and Bagaturyants, A. A. and Safonov, A. and Liventsov, V. V. and Deminsky, M. A. and Dean, T. and Varatharajan, B. and Tentner, A. and RRC Kurchatov Inst. and Kinetic Technologies Lab. and N.N. Semenov Inst. of Chemical Physics and Russian Academy of Science and Moscow State Univ. and GE Global Research},
abstractNote = {No abstract prepared.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Mon Jan 01 00:00:00 EST 2007},
month = {Mon Jan 01 00:00:00 EST 2007}
}

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  • The Jet A surrogate, consisted from 72.7 wt % decane + 9.1 wt % hexane + 18.2 wt % benzene was selected. Detailed mechanism, consisted of 417 elementary reversible reactions and 71 components, for this Jet A surrogate combustion was elaborated. The capability of the 3-component Jet A surrogate to predict the ignition delay times for the Jet A fuel over wide temperature and pressure ranges and to predict the pressure, temperature, and velocity of detonation was demonstrated.
  • The authors have previously developed a knowledge-based method of factor analysis to analyze dynamic nuclear medicine image sequences. In this paper, the authors analyze dynamic PET cerebral glucose metabolism and neuroreceptor binding studies. These methods have shown the ability to reduce the dimensionality of the data, enhance the image quality of the sequence, and generate meaningful functional images and their corresponding physiological time functions. The new information produced by the factor analysis has now been used to improve the estimation of various physiological parameters. A principal component analysis (PCA) is first performed to identify statistically significant temporal variations and removemore » the uncorrelated variations (noise) due to Poisson counting statistics. The statistically significant principal components are then used to reconstruct a noise-reduced image sequence as well as provide an initial solution for the factor analysis. Prior knowledge such as the compartmental models or the requirement of positivity and simple structure can be used to constrain the analysis. These constraints are used to rotate the factors to the most physically and physiologically realistic solution. The final result is a small number of time functions (factors) representing the underlying physiological processes and their associated weighting images representing the spatial localization of these functions. Estimation of physiological parameters can then be performed using the noise-reduced image sequence generated from the statistically significant PCs and/or the final factor images and time functions. These results are compared to the parameter estimation using standard methods and the original raw image sequences. Graphical analysis was performed at the pixel level to generate comparable parametric images of the slope and intercept (influx constant and distribution volume).« less