RESEARCH AND OPTIMIZATION OF THE INFLUENCE OF FRACTIONAL COMPOSITION OF THE WORKING MIXTURE OF POWDERS ON THE CHARACTERISTICS OF THE SOLID MIXTURE FUEL

Николай Дмитриевич Кошевой, Алексей Леонидович Кириченко, Сергей Анатольевич Борисенко, Виктор Владимирович Муратов

Abstract


When studying the influence of the fractional composition of the working mixture of powders on the characteristics of solid mixed rocket fuel (SMRF), optimization is proposed using the jumping frog method to construct time-optimal experimental designs. It is known that the proportion of the fractional agent (FA) product in the composition of SMRF is the largest and amounts to 80 %. Consequently, the FA product has one of the greatest effects on the whole range of physicochemical properties of SMRF. Thus, the task of determining the effect of the FA product on the properties of SMRF is very relevant. The application of experimental design methods reduces the cost and time costs in the study of various technological processes, devices, and systems. Minimizing the number of transitions of factor levels in terms of the experiment, in turn, leads to a decrease in the cost (time) of its implementation. The goal of the work is the optimization of the full factorial experiment time-lapse experiment using the jumping frog method. To this end, a method is proposed for constructing a time-optimal implementation of the experiment planning matrix using the jumping frog algorithm. In the jumping frog method, a successful frog is determined by the least transition time between levels for each of the factors. After that, frog permutations are performed. The frog strives for the most successful and, if located nearby, remains in its current location. The software has been developed that implements the proposed method, which was used to conduct computational experiments to study the properties of this method when studying the influence of the fractional composition of the working mixture of powders on the characteristics of solid mixed rocket fuel. The experimental plans optimal in terms of implementation time were obtained, and also the winnings in the optimization results are given in comparison with the initial experiment time. A full factorial experiment was carried out to study the effect of the fractional composition of the working mixture of powders on the characteristics of SMRF, based on which recommendations were made regarding the effect of the fractional composition of the working mixture of powders and the content of liquid-viscous components in the composition on the properties of SMRF. Mathematical models are also constructed, the coefficients of which characterize the effect of the content of liquid-viscous components in the composition on the properties of the SMRF. The experiments confirmed the efficiency of the proposed method and the software that implements it, and also allow us to recommend it for practical use in constructing the optimal planning matrices of the experiment.

Keywords


optimization; experiment planning; the working mixture of powders; optimal plan; jumping frog method; time

References


Yakovlev, S. V., Pichugina, O. S. Properties of Combinatorial Optimization Problems Over Polyhedral-Spherical Sets. Cybernetics and Systems Analysis, 2018, vol. 54 (1), pp. 99-109. DOI: 10.1007/s10559-018-0011-6.

Yakovlev, S. Convex extensions in combinatorial optimization and their applications. Springer Optimization and Its Applications, 2017, vol. 130, pp. 567-584. DOI: 10.1007/978-3-319-68640-0_27.

Hoskins, D. S. Combinatorics and Statistical Inferecing. Applied Optimal Designs, vol. 4, 2007, pp. 147 179.

Morgan, J. P. Association Schemes: Designed Experiments, Algebra and Combinatorics. Journal of the American Statistical Association, vol. 100, no. 471, 2005, pp. 1092-1093.

Bailey, R. A., Cameron, P. G. Combinatorics of optimal designs. Surveys in Combinatorics, vol. 365, 2009, pp. 19-73.

Wu, C. F. J., Hamada, M. S. Experiments: Planning, Analysis, and Optimization. Wiley, 2015. 743 p.

Semenov, S. A. Planirovanie eksperimenta v khimii i khimicheskoy tekhnologii. Uchebno-metodicheskoe posobie [Planning an experiment in chemistry and chemical technology. Teaching aid]. Moscow, CPI, 2001. 93 p.

Akhnazarova, S. L., Kafarov, V. V. Optimizacija jeksperimenta v himii i himicheskoj tehnologii. Uchebnoe posobie dlja himiko-tehnologicheskih vuzov [Optimization of an experiment in chemistry and chemical technology: Textbook. A allowance for chemical and technological universities]. Moscow, Higher School Publ., 1978. 319 p.

Adler, Yu. P., Markova, E. V., Granovskiy, Yu. V. Planirovanie experimenta pri poiske optimalnih usloviy [Planning an experiment to find optimal conditions]. Мoscow, Science Publ., 1976. 280 p.

Karpenko, A. P. Sovremennye algoritmy poiskovoj optimizacii. Algoritmy, vdohnovlennye prirodoj. Uchebnoe posobie [Modern search engine optimization algorithms. Algorithms inspired by nature: a training manual]. Moscow, MSTU, N.E. Bauman, 2014. 446 p.

Koshevoy, N. D., Kostenko, E. M. Optimal'noe po stoimostnym i vremennym zatratam planirovanie eksperimenta: monografija [Cost-effective and time-optimal experiment design: monograph]. Poltava, Izdatel' Shevchenko R.V., 2013. 317 p.

Koshevoy, N. D., Gordienko, V. A., Sukhobrus, Ye. A. Optimization for the design of technological processes. Telecommunications and Radio Engineering, 2014, vol. 73, no. 15, pp. 1383-1386. DOI: 10.1615/TelecomRadEng. V73.i15.60.

Koshevoy, N. D., Muratov, V. V. Primenenie algoritma prygajushhih ljagushek dlja optimizacii po stoimostnym (vremennym) zatratam planov polnogo faktornogo jeksperimenta [The use of the jumping frog algorithm for optimization of the cost (time) cost of plans for a full factorial experiment]. Radioelektronni i komp'uterni sistemi – Radioelectronic and computer systems, 2018, no. 4, pp. 53-61. DOI: 10.32620/reks.2018.4.05.

Koshoviy, M. D., Muratov, V. V. Zastosuvannja algoritmu mavpjachogo poshuku dlja optimіzacії planіv povnogo faktornogo eksperimentu [Application of the monkey application algorithm for optimizing the plans of the full factor experiment]. Zbіrnik naukovih prac' Vіjs'kovogo іnstitutu Kiїvs'kogo Nacіonal'nogo unіversitetu іmenі Tarasa Shevchenka – Collection of Scientific Papers of the Military Institute Military Institute of Taras Shevchenko National University of Kyiv, 2018, no. 61, pp. 61-69.

Ugryumov, M. L., Men’shikov, V. A., Belik, V. V. Network characteristic calculation method of spatial boundary layer on bounding surface of interblade channel of turboset. Izvestiya Vysshikh Uchebnykh Zavedenij. Aviatsionnaya Tekhnika, 1992, no. 1, pp. 38-41.

Ugryumov, M. L., Afanasjevska, V. E., Tronchuk, A. A., Myenyaylov, A. V. Stochastic optimization models and method in the turbomachines system improvement problem. ASME-JSME-KSME 2011 Joint Fluids Engineering Conference, AJK, no. 1 (PARTS A, B, C, D), pp. 755–761.




DOI: https://doi.org/10.32620/aktt.2020.2.07