Оптимизация элементов конструкции с помощью генетического алгоритма в существующих программных продуктах
2016
Abstract. Purpose. More than half a century, there is an evolutionary mechanism optimization, more than 20 years, many CAE systems exist and develop. Over the years, accumulating experience to optimize certain elements using genetic algorithm. Majo r companies have developed platform to simplify calculations engineer. Of course, a couple of years did not achieve all of these results, but use existing mechanisms and to create on their basis of better software, not this thing in our area. In this reg ard, the purpose of this article: To investigate the possible mechanisms of optimization from third-party systems, and the use of these mechanisms in the developed software product. Also, before the author raises a number of other tasks, such as combining the mechanisms of several software components and use the results to provide a report on all related. Methodology. The main contents of the study are to examine the possibilities of ANSYS system and platform, the ability to integrate with third -party applications and bidirectional transmission parameters. The author cites one of the considered task solutions. This article describes how to step through the implementation of the system of ANSYS optimization design element. the possible transfer options are also describ ed as of the developed software product, and with ANSYS Workrench platform. The developed model of integration between the two systems is implemented in software product "Selection of cross-sections". Findings. Element for design optimization in ANSYS system was carried out. The findings are to compare the results of optimization of the developed product. That will contribute to further improvement of the overall system. The developed model of integration between the two systems has shown the efficienc y of the ligaments. The data is updated in both systems, without any long-term processes. The very construction of the geometric model takes a long time, but in the future all graphical representations will be made automatically. Originality. Adding software already implemented mechanisms to increase the value of this product. The author considers the implementation of several systems gene tic algorithm will give a more detailed picture of the optimized element. Not learning something new, and adding new capabilities developed by the application, this product will no longer meet the requirement to address kind of tasks that are currently easily solved. And thereby the application will not be necessary. Practical value. The article describes the construction of a model to optimize the design element of the third-party application to ANSYS system. The considered systems integration will help in the future to implement a bunch of other software products, and thereby improving the design programs and learning more and more opportunities for optimization using a genetic algorithm.
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