title: ÐÐ¿ÑÑ Ð¿ÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ð¸Ñ Ð½ÐµÐ¹ÑÐ¾ÑÐµÑÐµÐ²ÑÑ ÑÐµÑ Ð½Ð¾Ð»Ð¾Ð³Ð¸Ð¹ Ð² Ð³Ð¸Ð´ÑÐ¾Ð´Ð¸Ð½Ð°Ð¼Ð¸ÐºÐµ: Ð»Ð°Ð¼Ð¸Ð½Ð°ÑÐ½Ð¾Ðµ Ð¾Ð±ÑÐµÐºÐ°Ð½Ð¸Ðµ ÐºÑÑÐ³Ð¾Ð²Ð¾Ð³Ð¾ ÑÐ¸Ð»Ð¸Ð½Ð´ÑÐ°
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð±Ð°ÐºÐ°Ð»Ð°Ð²ÑÐ°
titleType: Subtitle
title: Experience in the application of neural network technologies in hydrodynamics: laminar flow around a circular cylinder
Creators: name: Ð£Ð³ÑÑÐ¼Ð¾Ð², ÐÐ»ÐµÐºÑÐ°Ð½Ð´Ñ
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2020
Subjects: Ð¸ÑÐºÑÑÑÑÐ²ÐµÐ½Ð½ÑÐ¹ Ð¸Ð½ÑÐµÐ»Ð»ÐµÐºÑ
Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ
ÑÐ²ÐµÑÑÐ¾ÑÐ½Ð°Ñ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½Ð°Ñ ÑÐµÑÑ
relu
cnn
openlb
keras
tensorflow
Ð»Ð°Ð¼Ð¸Ð½Ð°ÑÐ½Ð¾Ðµ Ð¾Ð±ÑÐµÐºÐ°Ð½Ð¸Ðµ
ÐºÑÑÐ³Ð¾Ð²Ð¾Ð¹ ÑÐ¸Ð»Ð¸Ð½Ð´Ñ
artificial intelligence
machine learning
artificial
neural network
convolutional neural network
laminar flow
circular cylinder

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description: The subject of the graduate qualification work is âExperience in the application of neural network technologies in hydrodynamics: laminar flow around a circular cylinderâ. The given work is devoted to studying the possibility of using neural network technology to obtain hydrodynamic characteristics. As an example, the problem of laminar flow around a circular cylinder was used. The research set the following goals: 1. The researcher prepared a review of the literature on the application of neural networks in fundamental and applied fields with an emphasis on the field of hydrodynamics. 2. Materials were prepared to describe the general principles of the use of neural networks in practice, the necessary terms were introduced, the substantiation of the main advantages and disadvantages were carried out. 3. Materials were prepared describing the applied software, as well as specialized libraries, which are intensively used in the works on the subject under discussion and are used in this work. 4. The program was developed based on neural network technologies and using the capabilities of ready-made libraries. It performs the prediction of velocity and pressure fields, as well as resistance coefficient for the selected problem. 5. The researcher prepared a description of the developed program, the models and methods laid down in it, as well as a guide to its use. 6. Based on the developed program, computational experiments were carried out for different geometries of the computational domain. The problem was solved using a convolutional neural network. This choice is due to available literature data on the issue. Development and design was carried out using Open Source libraries and the Python programming language. The results of the application of neural network technologies in the field of hydrodynamics were obtained, the basic design and development tools were mastered, the results correspond to the current level of application of neural network technologies in computational hydrodynamics.