E
Evgenia Kuleshova
Researcher at Kurchatov Institute
Publications - 89
Citations - 873
Evgenia Kuleshova is an academic researcher from Kurchatov Institute. The author has contributed to research in topics: Embrittlement & Reactor pressure vessel. The author has an hindex of 14, co-authored 79 publications receiving 725 citations. Previous affiliations of Evgenia Kuleshova include National Research Nuclear University MEPhI.
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Assessment of relative contributions from different mechanisms to radiation embrittlement of reactor pressure vessel steels
TL;DR: In this paper, the authors analyzed the relative contributions from the following mechanisms: radiation-induced hardening, inter- and intragranular segregation of impurities at precipitate/matrix interfaces.
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Intergranular and intragranular phosphorus segregation in Russian pressure vessel steels due to neutron irradiation
TL;DR: In this article, it has been established that irradiation induces both intergranular as well as intragranular phosphorus segregation in Russian reactor pressure vessel steels and that brittle and ductile fracture surfaces of Charpy specimens appear as a result of inter-granular and intraggranular segregation, respectively.
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Comparison of microstructural features of radiation embrittlement of VVER-440 and VVER-1000 reactor pressure vessel steels
TL;DR: In this article, microstructural features in the radiation embrittlement of VVER-1000 steels compared to VVER 440 RPV steels are compared. And the authors show that there are changes in the contributions of different radiation embrittlement mechanisms for VVER 1000 steel.
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Thermal ageing mechanisms of VVER-1000 reactor pressure vessel steels
TL;DR: In this paper, a complex of microstructural studies (TEM and SEM) and a comparative analysis of the results of these studies with the data of mechanical tests of temperature sets of VVER-1000 RPV surveillance specimens with exposure times up to ∼200,000h were conducted.
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Atom Probe Tomography Interlaboratory Study on Clustering Analysis in Experimental Data Using the Maximum Separation Distance Approach
Yan Dong,Auriane Etienne,Alex Frolov,S.V. Fedotova,Katsuhiko Fujii,Koji Fukuya,Constantinos Hatzoglou,Evgenia Kuleshova,Kristina Lindgren,Andrew J. London,Anabelle Lopez,Sergio Lozano-Perez,Yuichi Miyahara,Yasuyoshi Nagai,Kenji Nishida,Bertrand Radiguet,Daniel K. Schreiber,Naoki Soneda,Mattias Thuvander,Takeshi Toyama,Jing Wang,Faiza Sefta,Peter Chou,Emmanuelle A. Marquis +23 more
TL;DR: The use of the commonly used maximum separation distance and local concentration thresholding methods for solute clustering quantification is investigated to bring clarity to the range of applicability; identify existing and/or needed modifications; and interpretation of past published data.