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International Journal of Energetic Materials and Chemical Propulsion

Выходит 6 номеров в год

ISSN Печать: 2150-766X

ISSN Онлайн: 2150-7678

The Impact Factor measures the average number of citations received in a particular year by papers published in the journal during the two preceding years. 2017 Journal Citation Reports (Clarivate Analytics, 2018) IF: 0.7 To calculate the five year Impact Factor, citations are counted in 2017 to the previous five years and divided by the source items published in the previous five years. 2017 Journal Citation Reports (Clarivate Analytics, 2018) 5-Year IF: 0.7 The Immediacy Index is the average number of times an article is cited in the year it is published. The journal Immediacy Index indicates how quickly articles in a journal are cited. Immediacy Index: 0.1 The Eigenfactor score, developed by Jevin West and Carl Bergstrom at the University of Washington, is a rating of the total importance of a scientific journal. Journals are rated according to the number of incoming citations, with citations from highly ranked journals weighted to make a larger contribution to the eigenfactor than those from poorly ranked journals. Eigenfactor: 0.00016 The Journal Citation Indicator (JCI) is a single measurement of the field-normalized citation impact of journals in the Web of Science Core Collection across disciplines. The key words here are that the metric is normalized and cross-disciplinary. JCI: 0.18 SJR: 0.313 SNIP: 0.6 CiteScore™:: 1.6 H-Index: 16

Indexed in

APPLICATION OF ARTIFICIAL NEURAL NETWORKS FOR SOLUTION OF SCIENTIFIC AND APPLIED PROBLEMS FOR COMBUSTION OF ENERGETIC MATERIALS

Том 6, Выпуск 6, 2007, pp. 665-679
DOI: 10.1615/IntJEnergeticMaterialsChemProp.v6.i6.10
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Краткое описание

A goal of the paper is a presentation of possibilities of artificial neural networks (ANN) technologies for combustion modeling, experimental investigation, and diagnostics. A short introduction to ANN technologies and their applicability to scientific problems is included. For the first time, the use of sigmoid function for obtaining analytical solutions of combustion wave propagation differential equations has been suggested. Methods for the development of new computational models of combustion, as well as possible applications of ANN are discussed in this paper. A goal of the models is to solve the hard tasks involved with the experimental investigation of propellant combustion. An example of ANN being used for an investigation of deflagration-to-detonation transition (model of pulse detonation engine) under various experimental conditions is presented. It is shown that ANN can make up for gaps in experimental data. New ways for solving inverse problems of optics and their direct tasks by means of ANN are presented also. It is shown that ANN can be used for many optical and non-optical methods of combustion diagnostics as well as for testing and controlling combustion processes when the usual approaches cannot be used. Possibilities for the use of the only value of a function of signal distribution in a plane of the registration in order to determine full distribution of local characteristics in an object, as well as its integral characteristics, are shown.

ЦИТИРОВАНО В
  1. Rybkina A., Hodson S., Gvishiani A., Kabat P., Krasnoperov R., Samokhina O., Firsova E.~, CODATA and global challenges in data-driven science, Russian Journal of Earth Sciences, 18, 4, 2018. Crossref

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