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13 pages, 3079 KiB

Open AccessArticle

Comparative Theoretical Analysis of Halden Reactor Creep Tests on M5 Cladding Material

by Vincenzo Romanello

Appl. Sci. 2025, 15(3), 1040; https://doi.org/10.3390/app15031040 - 21 Jan 2025

Viewed by 754

This study provides a comparative analysis of two creep tests performed on M5 cladding material at the Halden reactor under different stress conditions in the IFA-617 and IFA-663 test rigs. The objective was to evaluate the creep behavior of the M5 cladding material, a crucial component in nuclear reactors, under both compressive and tensile stress environments. The data generated from these experiments were analyzed to assess the diameter changes in the cladding over time, considering factors such as stress, temperature, and neutron flux. The results revealed a significant difference in creep rates between the two tests, with IFA-663 showing a considerably higher rate. This disparity is attributed to the combined effects of creep and corrosion/crud deposition phenomena, which were more pronounced under tensile stress conditions. A model was developed to account for these factors, providing a better understanding of the M5 cladding behavior in different operational environments. These findings contribute to improving the predictive capabilities of the TRANSURANUS code for simulating M5 cladding creep, highlighting the need for further post-irradiation examinations to refine the understanding of corrosion and crud deposition effects. Full article

(This article belongs to the Section Applied Physics General)

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18 pages, 27653 KiB

Open AccessArticle

Toward Deep Decontamination of Intermediate-Level-Activity Spent Ion-Exchange Resins Containing Poorly Soluble Inorganic Deposits

by Marina Palamarchuk, Maxim Chervonetskiy, Natalya Polkanova and Svetlana Bratskaya

Sustainability 2023, 15(5), 3990; https://doi.org/10.3390/su15053990 - 22 Feb 2023

Cited by 2 | Viewed by 2514

Abstract

Spent ion-exchange resins (SIERs) generated yearly in large volumes in nuclear power plants (NPPs) require particular predisposal handling and treatment with the primary objectives of waste volume reduction and lowering the disposal class. Deep decontamination of the SIERs using solution chemistry is a promising approach to reduce the amount of intermediate-level radioactive waste (ILW) and, thus, SIER disposal costs. However, the entrapment of nonexchangeable radionuclides in poorly soluble inorganic deposits on SIERs significantly complicates the implementation of this approach. In this work, the elemental and radiochemical compositions of inorganic deposits in an intermediate-level-activity SIER sample with an activity of 310 kBq/g have been analyzed, and a feasibility study of SIER decontamination using solution chemistry has been conducted. The suggested approach included the magnetic separation of crud, removal of cesium radionuclides using alkaline solutions in the presence of magnetic resorcinol-formaldehyde resin, removal of cobalt radionuclides using acidic EDTA-containing solutions, and hydrothermal oxidation of EDTA-containing liquid wastes with immobilization of radionuclides in poorly soluble oxides. The decontamination factors for ¹³⁷Cs, ⁶⁰Co, and ⁹⁴Nb radionuclides were 3.9 × 10³, 7.6 × 10², and 1.3 × 10², respectively, whereas the activity of the decontaminated SIER was 17 Bq/g, which allows us to classify it as very low-level waste. Full article

(This article belongs to the Special Issue Nuclear Waste Management and Sustainability)

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19 pages, 1295 KiB

Open AccessArticle

A Novel Method for Controlling Crud Deposition in Nuclear Reactors Using Optimization Algorithms and Deep Neural Network Based Surrogate Models

by Brian Andersen, Jason Hou, Andrew Godfrey and Dave Kropaczek

Eng 2022, 3(4), 504-522; https://doi.org/10.3390/eng3040036 - 23 Nov 2022

Cited by 4 | Viewed by 2430

Abstract

This work presents the use of a high-fidelity neural network surrogate model within a Modular Optimization Framework for treatment of crud deposition as a constraint within light-water reactor core loading pattern optimization. The neural network was utilized for the treatment of crud constraints within the context of an advanced genetic algorithm applied to the core design problem. This proof-of-concept study shows that loading pattern optimization aided by a neural network surrogate model can optimize the manner in which crud distributes within a nuclear reactor without impacting operational parameters such as enrichment or cycle length. Several analysis methods were investigated. Analysis found that the surrogate model and genetic algorithm successfully minimized the deviation from a uniform crud distribution against a population of solutions from a reference optimization in which the crud distribution was not optimized. Strong evidence is presented that shows boron deposition in crud can be optimized through the loading pattern. This proof-of-concept study shows that the methods employed provide a powerful tool for mitigating the effects of crud deposition in nuclear reactors. Full article

(This article belongs to the Special Issue Feature Papers in Eng 2022)

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