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Использование генетического алгоритма для оптимизации параметров системы с ускоряемой присоединенной камерой

Использование генетического алгоритма для оптимизации параметров системы с ускоряемой присоединенной камерой

Abstract

На основе модели газопороховой смеси определена баллистика установки с присоединенной камерой. В виду сложности математической модели, описывающей систему в процессе выстрела, решение может быть получено лишь с использованием численных методов. Для оптимизации параметров предлагается использовать метод покоординатного спуска и генетический алгоритм. В статье приводятся постановка задачи оптимизации и результаты ее решения, полученные с помощью различных методов. Результаты оптимизации, полученные с использованием генетического алгоритма, сравниваются с результатами, полученными ранее, с использованием метода покоординатного спуска. Применение генетического алгоритма даёт значительно лучшие результаты. В соответствии с проведенными расчетами показано, что оптимизация параметров приведенной схемы позволит повысить скорости метаемого элемента, для рассматриваемой системы, до 26% при неизменном максимальном давлении на дно канала пусковой трубы по сравнению с классической схемой.

Based on the model of gas-powder mixture defined ballistics unit with camera attached. Due to the complexity of the mathematical model that describes the system in the process of firing, the solution can be obtained only by using numerical methods. To optimize the use proposed method of descent and genetic algorithm. The paper presents the formulation of the optimization problem and its solution results obtained using different methods. Optimization results obtained using the genetic algorithm are compared with results previously obtained using the method of descent. Application of genetic algorithm produces significantly better results. According to calculations show that the optimization of the parameters above scheme will increase the projectile velocity element for the system, up to 26% at constant maximum pressure on the bottom of the channel launch tube as compared with the classical scheme.

Keywords

ГЕНЕТИЧЕСКИЙ АЛГОРИТМ, МЕТОДЫ ОПТИМИЗАЦИИ, НЕЛИНЕЙНЫЕ ОГРАНИЧЕНИЯ, СПК

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
gold