title: ÐÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ð¸Ðµ Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ ÑÐºÑÐ¿ÑÐµÑÑÐ¸Ð¸ Ð³ÐµÐ½Ð¾Ð² Ð¸ Ð¼ÐµÑÐ¾Ð´Ð° Ð½Ð°Ð³ÑÐµÑÑÑ ÐºÐ°Ð½Ð°Ð»Ð¾Ð² Ð´Ð»Ñ Ð¿Ð¾ÑÑÑÐ¾ÐµÐ½Ð¸Ñ ÐºÐ¾ÑÑÐµÐ»ÑÑÐ¸Ð¹ ÑÐµÐ¼Ð¿ÐµÑÐ°ÑÑÑÑ ÑÐµÐ¿Ð»Ð¾Ð½Ð¾ÑÐ¸ÑÐµÐ»Ñ ÑÐµÐ°ÐºÑÐ¾ÑÐ° ÐÐÐ­Ð -1000 Ð¿ÑÐ¸ ÑÑÐ°ÑÐ¸Ð¾Ð½Ð°ÑÐ½ÑÑ ÑÐµÐ¶Ð¸Ð¼Ð°Ñ ÑÐ°Ð±Ð¾ÑÑ
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð¼Ð°Ð³Ð¸ÑÑÑÐ°
titleType: Subtitle
title: Application of gene expression programming and single-heated channel approach in developing a correlation for coolant temperature of VVER 1000 reactor in steady-state
Creators: name: Ð¨Ð°ÑÐ¸Ð½Ð³ÑÐ·, ÐÐ¶ÐµÐ¼
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: 2022
Subjects: Ð¯Ð´ÐµÑÐ½ÑÐµ ÑÐµÐ°ÐºÑÐ¾ÑÑ Ð²Ð¾Ð´Ð¾-Ð²Ð¾Ð´ÑÐ½ÑÐµ
ÐÑÐºÑÑÑÑÐ²ÐµÐ½Ð½ÑÐ¹ Ð¸Ð½ÑÐµÐ»Ð»ÐµÐºÑ
Ð¼ÐµÑÐ¾Ð´ Ð¾Ð´Ð¸Ð½Ð¾ÑÐ½Ð¾Ð³Ð¾ ÐºÐ°Ð½Ð°Ð»Ð°
Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ðµ ÑÐºÑÐ¿ÑÐµÑÑÐ¸Ð¸ Ð³ÐµÐ½Ð¾Ð²
Ð¿ÑÐ¾Ð³Ð½Ð¾Ð·Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ðµ ÑÐµÐ¼Ð¿ÐµÑÐ°ÑÑÑÑ ÑÐµÐ¿Ð»Ð¾Ð½Ð¾ÑÐ¸ÑÐµÐ»Ñ
single channel method
gene expression programming
coolant temperature prediction

description: Ð¢ÐµÐ¼Ð¿ÐµÑÐ°ÑÑÑÐ° ÑÐµÐ¿Ð»Ð¾Ð½Ð¾ÑÐ¸ÑÐµÐ»Ñ Ð² ÑÐ´ÐµÑÐ½Ð¾Ð¼ ÑÐµÐ°ÐºÑÐ¾ÑÐµ ÑÐ²Ð»ÑÐµÑÑÑ ÐºÑÐ¸ÑÐ¸ÑÐµÑÐºÐ¸Ð¼ ÑÐ°ÐºÑÐ¾ÑÐ¾Ð¼ Ð´Ð»Ñ Ð¾Ð±ÐµÑÐ¿ÐµÑÐµÐ½Ð¸Ñ Ð±ÐµÐ·Ð¾Ð¿Ð°ÑÐ½Ð¾Ð¹ Ð¸ ÑÑÑÐµÐºÑÐ¸Ð²Ð½Ð¾Ð¹ ÑÐ°Ð±Ð¾ÑÑ ÑÐµÐ°ÐºÑÐ¾ÑÐ°. Ð¢Ð¾ÑÐ½ÑÐµ ÐºÐ¾ÑÑÐµÐ»ÑÑÐ¸Ð¸, Ð¿ÑÐµÐ´ÑÐºÐ°Ð·ÑÐ²Ð°ÑÑÐ¸Ðµ ÑÐµÐ¼Ð¿ÐµÑÐ°ÑÑÑÑ ÑÐµÐ¿Ð»Ð¾Ð½Ð¾ÑÐ¸ÑÐµÐ»Ñ, Ð½ÐµÐ¾Ð±ÑÐ¾Ð´Ð¸Ð¼Ñ Ð´Ð»Ñ Ð¿ÑÐµÐ´Ð¾ÑÐ²ÑÐ°ÑÐµÐ½Ð¸Ñ Ð¿ÐµÑÐµÐ³ÑÐµÐ²Ð° ÑÐ¾Ð¿Ð»Ð¸Ð²Ð°, Ð¾Ð¿ÑÐ¸Ð¼Ð¸Ð·Ð°ÑÐ¸Ð¸ ÑÐ°Ð±Ð¾ÑÑ ÑÐµÐ°ÐºÑÐ¾ÑÐ° Ð¸ Ð¾Ð±ÐµÑÐ¿ÐµÑÐµÐ½Ð¸Ñ Ð±ÐµÐ·Ð¾Ð¿Ð°ÑÐ½Ð¾ÑÑÐ¸. ÐÐ»Ñ ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐºÐ¸ ÑÐ°ÐºÐ¸Ñ ÐºÐ¾ÑÑÐµÐ»ÑÑÐ¸Ð¹ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·ÑÑÑÑÑ Ð¼ÐµÑÐ¾Ð´Ð¸ÐºÐ¸ Ð¸ÑÐºÑÑÑÑÐ²ÐµÐ½Ð½Ð¾Ð³Ð¾ Ð¸Ð½ÑÐµÐ»Ð»ÐµÐºÑÐ° (ÐÐ). Ð¦ÐµÐ»ÑÑ Ð´Ð°Ð½Ð½Ð¾Ð³Ð¾ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ ÑÐ²Ð»ÑÐµÑÑÑ ÑÐ¾Ð·Ð´Ð°Ð½Ð¸Ðµ ÐºÐ¾ÑÑÐµÐ»ÑÑÐ¸Ð¸ Ñ Ð¿Ð¾Ð¼Ð¾ÑÑÑ Ð¼ÐµÑÐ¾Ð´Ð¾Ð² Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ð³Ð¾ Ð¾Ð±ÑÑÐµÐ½Ð¸Ñ, Ð¿Ð¾Ð·Ð²Ð¾Ð»ÑÑÑÐµÐ¹ Ð¿ÑÐ¾Ð³Ð½Ð¾Ð·Ð¸ÑÐ¾Ð²Ð°ÑÑ ÑÐµÐ¼Ð¿ÐµÑÐ°ÑÑÑÑ ÑÐµÐ¿Ð»Ð¾Ð½Ð¾ÑÐ¸ÑÐµÐ»Ñ Ð² ÑÐ´ÐµÑÐ½ÑÑ ÑÐµÐ°ÐºÑÐ¾ÑÐ°Ñ. Ð§Ð¸ÑÐ»ÐµÐ½Ð½Ð¾Ðµ Ð¼Ð¾Ð´ÐµÐ»Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ðµ ÑÐ´ÐµÑÐ½Ð¾Ð³Ð¾ ÑÐµÐ°ÐºÑÐ¾ÑÐ° ÐÐÐ­Ð -1000 Ð±ÑÐ»Ð¾ Ð¿ÑÐ¾Ð²ÐµÐ´ÐµÐ½Ð¾ Ñ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸ÐµÐ¼ Ð¿Ð¾Ð´ÑÐ¾Ð´Ð° Ñ Ð¾Ð´Ð½Ð¸Ð¼ Ð½Ð°Ð³ÑÐµÑÑÐ¼ ÐºÐ°Ð½Ð°Ð»Ð¾Ð¼ Ð´Ð»Ñ ÑÐ¾Ð·Ð´Ð°Ð½Ð¸Ñ Ð²ÑÐµÐ¾Ð±ÑÐµÐ¼Ð»ÑÑÐµÐ³Ð¾ Ð½Ð°Ð±Ð¾ÑÐ° Ð´Ð°Ð½Ð½ÑÑ Ð² Ð¿ÑÑÐ¼Ð¾Ð¼ Ð½Ð°Ð¿ÑÐ°Ð²Ð»ÐµÐ½Ð¸Ð¸. ÐÐ°Ð±Ð¾Ñ Ð´Ð°Ð½Ð½ÑÑ ÑÐ¾ÑÑÐ¾ÑÐ» Ð¸Ð· Ð±ÐµÐ·ÑÐ°Ð·Ð¼ÐµÑÐ½ÑÑ Ð¿Ð°ÑÐ°Ð¼ÐµÑÑÐ¾Ð² ÑÑÑÐ°Ð½Ð¾Ð²Ð¸Ð²ÑÐµÐ³Ð¾ÑÑ ÑÐµÐ¶Ð¸Ð¼Ð°, ÑÐ°ÐºÐ¸Ñ ÐºÐ°Ðº Ð¼Ð°ÑÑÐ¾Ð²ÑÐ¹ Ð¿Ð¾ÑÐ¾Ðº Ð½Ð° Ð²ÑÐ¾Ð´Ðµ, Ð´Ð°Ð²Ð»ÐµÐ½Ð¸Ðµ Ð½Ð° Ð²ÑÑÐ¾Ð´Ðµ, ÑÐµÐ¼Ð¿ÐµÑÐ°ÑÑÑÐ° Ð½Ð° Ð²ÑÐ¾Ð´Ðµ Ð¸ ÐºÐ¾ÑÑÑÐ¸ÑÐ¸ÐµÐ½Ñ Ð¼Ð¾ÑÐ½Ð¾ÑÑÐ¸ Ð°ÐºÑÐ¸Ð²Ð½Ð¾Ð¹ Ð·Ð¾Ð½Ñ. ÐÐ»Ð³Ð¾ÑÐ¸ÑÐ¼ Gene Expression Programming (GEP) Ð±ÑÐ» Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½ Ð´Ð»Ñ Ð¿Ð¾ÑÑÑÐ¾ÐµÐ½Ð¸Ñ ÐºÐ¾ÑÑÐµÐ»ÑÑÐ¸Ð¸ Ð´Ð»Ñ ÑÐµÐ¼Ð¿ÐµÑÐ°ÑÑÑÑ ÑÐµÐ¿Ð»Ð¾Ð½Ð¾ÑÐ¸ÑÐµÐ»Ñ Ð½Ð° ÑÐ°Ð·Ð½ÑÑ Ð¾ÑÐµÐ²ÑÑ ÑÑÐ¾Ð²Ð½ÑÑ. Ð¡ÑÐµÐ´Ð½ÑÑ ÐºÐ²Ð°Ð´ÑÐ°ÑÐ¸ÑÐ½Ð°Ñ Ð¾ÑÐ¸Ð±ÐºÐ° (MSE) Ð¸ ÐºÐ¾ÑÑÑÐ¸ÑÐ¸ÐµÐ½Ñ Ð´ÐµÑÐµÑÐ¼Ð¸Ð½Ð°ÑÐ¸Ð¸ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð»Ð¸ÑÑ Ð´Ð»Ñ ÐºÐ¾Ð»Ð¸ÑÐµÑÑÐ²ÐµÐ½Ð½Ð¾Ð¹ Ð¾ÑÐµÐ½ÐºÐ¸ Ð¿Ð¾Ð³ÑÐµÑÐ½Ð¾ÑÑÐ¸ ÐºÐ°Ð¶Ð´Ð¾Ð³Ð¾ Ð¿Ð¾Ð´ÑÐ¾Ð´Ð°. Ð ÐµÐ·ÑÐ»ÑÑÐ°ÑÑ Ð¿Ð¾ÐºÐ°Ð·Ð°Ð»Ð¸, ÑÑÐ¾ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼ GEP Ð¿ÑÐ¾Ð´ÐµÐ¼Ð¾Ð½ÑÑÑÐ¸ÑÐ¾Ð²Ð°Ð» Ð¸ÑÐºÐ»ÑÑÐ¸ÑÐµÐ»ÑÐ½Ð¾ Ð²ÑÑÐ¾ÐºÑÑ ÑÐ¾ÑÐ½Ð¾ÑÑÑ Ð¿ÑÐ¾Ð³Ð½Ð¾Ð·Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ (MSE &lt; 10-5), ÑÑÐ¾ ÑÐ²Ð¸Ð´ÐµÑÐµÐ»ÑÑÑÐ²ÑÐµÑ Ð¾ ÐµÐ³Ð¾ ÑÑÑÐµÐºÑÐ¸Ð²Ð½Ð¾ÑÑÐ¸ Ð² ÑÐ¾Ð·Ð´Ð°Ð½Ð¸Ð¸ ÐºÐ¾ÑÑÐµÐ»ÑÑÐ¸Ð¹ Ñ Ð²ÑÑÐ¾ÐºÐ¾Ð¹ ÑÐ¾ÑÐ½Ð¾ÑÑÑÑ Ð´Ð»Ñ Ð¾ÑÑÐ»ÐµÐ¶Ð¸Ð²Ð°Ð½Ð¸Ñ ÑÐµÐ¼Ð¿ÐµÑÐ°ÑÑÑÑ Ð¾ÑÐ»Ð°Ð¶Ð´Ð°ÑÑÐµÐ¹ Ð¶Ð¸Ð´ÐºÐ¾ÑÑÐ¸ Ð² Ð½Ð¾ÑÐ¼Ð°Ð»ÑÐ½Ð¾Ð¼ ÑÐµÐ¶Ð¸Ð¼Ðµ ÑÐ°Ð±Ð¾ÑÑ.
description: The coolant temperature in a nuclear reactor is a critical factor in ensuring the safe and efficient operation of the reactor. Accurate correlations that predict coolant temperature are necessary to prevent fuel overheating, optimize reactor performance, and ensure safety. Artificial intelligence (AI) methodologies have been used to develop such correlations. The objective of this study is to generate a correlation through the application of machine learning techniques that enable the prediction of coolant water in nuclear reactors. A numerical simulation of a VVER-1000 nuclear reactor was conducted using a single-heated channel approach to generate a comprehensive dataset in a forward direction. The dataset consisted of nondimensional steady-state parameters, such as inlet mass flux, outlet pressure, inlet temperature, and power ratio of the core. The Gene Expression Programming (GEP) algorithm was then used to develop a correlation for the temperature of the coolant at different axial levels. The Mean Square Error (MSE) and coefficient of determination were used to quantify the error of each approach. Results showed that the GEP algorithm exhibited exceptionally high prediction accuracy (MSE &lt; 10-5), indicating its efficacy in generating correlations with high accuracy to track coolant temperature in normal operation.