Cargando…

The development of prediction model on irradiation embitterment for low Cu RPV steels

The development of prediction model on irradiation embitterment (PMIE) of reactor pressure vessel (RPV) is an important method for nuclear reactor long term operation. Based on the physical mechanism of RPV irradiation embrittlement, a preliminary model is determined and the critical threshold of Cu...

Descripción completa

Detalles Bibliográficos
Autores principales: Xu, Chaoliang, Liu, Xiangbing, Li, Yuanfei, Jia, Wenqing, Quan, Qiwei, Qian, Wangjie, Yin, Jian, Jin, Xiao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10220401/
https://www.ncbi.nlm.nih.gov/pubmed/37251475
http://dx.doi.org/10.1016/j.heliyon.2023.e16581
_version_ 1785049211816902656
author Xu, Chaoliang
Liu, Xiangbing
Li, Yuanfei
Jia, Wenqing
Quan, Qiwei
Qian, Wangjie
Yin, Jian
Jin, Xiao
author_facet Xu, Chaoliang
Liu, Xiangbing
Li, Yuanfei
Jia, Wenqing
Quan, Qiwei
Qian, Wangjie
Yin, Jian
Jin, Xiao
author_sort Xu, Chaoliang
collection PubMed
description The development of prediction model on irradiation embitterment (PMIE) of reactor pressure vessel (RPV) is an important method for nuclear reactor long term operation. Based on the physical mechanism of RPV irradiation embrittlement, a preliminary model is determined and the critical threshold of Cu content of 0.072% is obtained according to this preliminary model. Then a prediction model named PMIE-2020 for low Cu RPV steels is developed. At last the residual, standard deviation and predicted values and test values distribution analysis are given. Simultaneously, a comparison between PMIE-2020 and other prediction model and irradiation data is provided. Results indicate that the predicted results of PMIE-2020 has no tendency with influence factors such as neutron fluence, flux, irradiation temperature, chemical elements Cu, P, Mn, Ni, Si. The residual standard deviation is 10.76 °C, which is lower than present prediction model. The distribution between predicted values of PMIE-2020 and test values are located the area near the 45° line. These results prove that the PMIE-2020 have high accuracy on irradiation embrittlement prediction.
format Online
Article
Text
id pubmed-10220401
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Elsevier
record_format MEDLINE/PubMed
spelling pubmed-102204012023-05-28 The development of prediction model on irradiation embitterment for low Cu RPV steels Xu, Chaoliang Liu, Xiangbing Li, Yuanfei Jia, Wenqing Quan, Qiwei Qian, Wangjie Yin, Jian Jin, Xiao Heliyon Research Article The development of prediction model on irradiation embitterment (PMIE) of reactor pressure vessel (RPV) is an important method for nuclear reactor long term operation. Based on the physical mechanism of RPV irradiation embrittlement, a preliminary model is determined and the critical threshold of Cu content of 0.072% is obtained according to this preliminary model. Then a prediction model named PMIE-2020 for low Cu RPV steels is developed. At last the residual, standard deviation and predicted values and test values distribution analysis are given. Simultaneously, a comparison between PMIE-2020 and other prediction model and irradiation data is provided. Results indicate that the predicted results of PMIE-2020 has no tendency with influence factors such as neutron fluence, flux, irradiation temperature, chemical elements Cu, P, Mn, Ni, Si. The residual standard deviation is 10.76 °C, which is lower than present prediction model. The distribution between predicted values of PMIE-2020 and test values are located the area near the 45° line. These results prove that the PMIE-2020 have high accuracy on irradiation embrittlement prediction. Elsevier 2023-05-23 /pmc/articles/PMC10220401/ /pubmed/37251475 http://dx.doi.org/10.1016/j.heliyon.2023.e16581 Text en © 2023 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Research Article
Xu, Chaoliang
Liu, Xiangbing
Li, Yuanfei
Jia, Wenqing
Quan, Qiwei
Qian, Wangjie
Yin, Jian
Jin, Xiao
The development of prediction model on irradiation embitterment for low Cu RPV steels
title The development of prediction model on irradiation embitterment for low Cu RPV steels
title_full The development of prediction model on irradiation embitterment for low Cu RPV steels
title_fullStr The development of prediction model on irradiation embitterment for low Cu RPV steels
title_full_unstemmed The development of prediction model on irradiation embitterment for low Cu RPV steels
title_short The development of prediction model on irradiation embitterment for low Cu RPV steels
title_sort development of prediction model on irradiation embitterment for low cu rpv steels
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10220401/
https://www.ncbi.nlm.nih.gov/pubmed/37251475
http://dx.doi.org/10.1016/j.heliyon.2023.e16581
work_keys_str_mv AT xuchaoliang thedevelopmentofpredictionmodelonirradiationembittermentforlowcurpvsteels
AT liuxiangbing thedevelopmentofpredictionmodelonirradiationembittermentforlowcurpvsteels
AT liyuanfei thedevelopmentofpredictionmodelonirradiationembittermentforlowcurpvsteels
AT jiawenqing thedevelopmentofpredictionmodelonirradiationembittermentforlowcurpvsteels
AT quanqiwei thedevelopmentofpredictionmodelonirradiationembittermentforlowcurpvsteels
AT qianwangjie thedevelopmentofpredictionmodelonirradiationembittermentforlowcurpvsteels
AT yinjian thedevelopmentofpredictionmodelonirradiationembittermentforlowcurpvsteels
AT jinxiao thedevelopmentofpredictionmodelonirradiationembittermentforlowcurpvsteels
AT xuchaoliang developmentofpredictionmodelonirradiationembittermentforlowcurpvsteels
AT liuxiangbing developmentofpredictionmodelonirradiationembittermentforlowcurpvsteels
AT liyuanfei developmentofpredictionmodelonirradiationembittermentforlowcurpvsteels
AT jiawenqing developmentofpredictionmodelonirradiationembittermentforlowcurpvsteels
AT quanqiwei developmentofpredictionmodelonirradiationembittermentforlowcurpvsteels
AT qianwangjie developmentofpredictionmodelonirradiationembittermentforlowcurpvsteels
AT yinjian developmentofpredictionmodelonirradiationembittermentforlowcurpvsteels
AT jinxiao developmentofpredictionmodelonirradiationembittermentforlowcurpvsteels