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Bajpai, R. K.
- Long-Term Performance Assessment of Nuclear Waste and Natural Glasses in the Geological Repository: a Geochemical Modelling
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Authors
Affiliations
1 Department of Geology, University of Delhi, Delhi 110 007, IN
2 Nuclear Recycle Group, BARC, Mumbai 400 008, IN
1 Department of Geology, University of Delhi, Delhi 110 007, IN
2 Nuclear Recycle Group, BARC, Mumbai 400 008, IN
Source
Current Science, Vol 110, No 2 (2016), Pagination: 214-219Abstract
Nuclear waste loaded and natural (analogue) glasses were studied to understand neo-formed mineral species, formed in equilibrium with the physico-chemical conditions existing in the geological repository. To predict alteration-phases, dissolution equations for average vitrification system (AVS), barium borosilicate (BBS) and obsidian glass were calculated, considering glass composition, pressure, temperature and pH conditions. Progress of reaction plotted against saturation index, indicates saturation with solid phases - chamosite, chalcedony and Ca-beidellite in obsidian; greenalite and fayalite in AVS; and coffinite BBS glass. Activities and molalities of aqueous species together with the number of moles of each mineral species produced and degenerated during the progress of the reaction (as a function of time) are discussed in this communication.Keywords
Geochemical Modelling, Geological Repository, Natural Glass, Nuclear Waste.Full Text
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- Development of Artificial Neural Network-Based Model for Prediction of Temperature Field in Host Rock of a Geological Disposal Facility for Radioactive Waste
Abstract Views :239 |
PDF Views:80
Authors
Affiliations
1 Bhabha Atomic Research Centre, Mumbai 400 085, IN
1 Bhabha Atomic Research Centre, Mumbai 400 085, IN
Source
Current Science, Vol 118, No 3 (2020), Pagination: 439-443Abstract
Calculation of temperature field in a deep geological repository (DGR) after emplacement of a large number of heat emitting vitrified radioactive canisters is important and requires large computational time and hence in this study an effort has been made towards development of artificial neural network (ANN) based model that can predict the temperature quickly. The datasets required to train the ANN model were generated using an in-house developed GUI tool for simulating heat diffusion process. Various numerical studies were conducted with different configurations of the ANN model and different datasets of size 50, 100, 150, 200, to optimize the number of input data required to train the model. The results in the form of temperature values predicted by the trained ANN model have been compared with those for the same problem calculated using analytical and finite difference based methods. The trained ANN model can predict temperature values with less than 0.001% error.Keywords
Artificial Neural Network, Geological Repository, Host Rock, Radioactive Waste, Temperature Field.Full Text
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Abstract Views :158 |
PDF Views:85
Authors
Affiliations
1 Homi Bhabha National Institute, Mumbai 400 094, IN
2 Indian Institute of Technology (BHU), Varanasi 221 005, IN
3 Indian Institute of Technology Bombay, Mumbai 400 076, IN
1 Homi Bhabha National Institute, Mumbai 400 094, IN
2 Indian Institute of Technology (BHU), Varanasi 221 005, IN
3 Indian Institute of Technology Bombay, Mumbai 400 076, IN
Source
Current Science, Vol 122, No 9 (2022), Pagination: 1089-1093Abstract
High-level heat-emitting long-lived vitrified radioactive waste produced during recycling of the spent nuclear fuel is under consideration for permanent disposal in deep geological formations with appropriate thermomechanical, hydrogeological and geochemical properties. The capability of these rock formations ensuring long-term confinement and isolation of such waste from the environment is significantly controlled by their efficiency in smoothly dissipating the heat emanating from the waste. A number of rock types such as basalt, granite, clay stones, volcanic tuff, argillites, etc. are being evaluated worldwide as well as in India. In this study, a granite from Jalore and bentonite from Barmer, both from Rajasthan, India, have been evaluated for their heat dissipation capacity. The study revealed that the temperature within granite at the centre of the canister reached 55.21°C, resulting in a thermal stress of 25.50 MPa. Bentonite experienced a temperature of 67.42°C in the central part with maximum thermal stress and displacement of 1.78 MPa and 0.446 mm respectively. A displacement of 0.997 mm was recorded at the granite–bentonite interface. Thus, no significant microcrack formation or undesirable displacement was observed within the granite as well as in bentonite, suggesting their capability to isolate and confine the heat-emitting source for extended periods.Keywords
Bentonite, deep geological repository, granite, radioactive waste, thermo-mechanical analysis.Full Text
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