Development of Mathematical Models for Long-Term Prediction of Corrosion Behaviour of Carbon Steel Overpacks for Radioactive Waste Disposal

1996 ◽  
Vol 465 ◽  
Author(s):  
A. R. Hoch ◽  
A. Honda ◽  
F. M. Porter ◽  
S. M. Sharland ◽  
N. Taniguchi
Keyword(s):  
Carbon Steel ◽  
Radioactive Waste ◽  
Mathematical Models ◽  
Waste Disposal ◽  
Corrosion Behaviour ◽  
Radioactive Waste Disposal ◽  
Cathodic Reaction ◽  
Term Prediction ◽  
Long Term Prediction

ABSTRACTMathematical models to enable long-term prediction of the corrosion behaviour of carbon steel overpacks for radioactive waste have been developed. An existing model of the growth of pits, implemented in the CAMLE software, has been extended and used to investigate the sensitivity of the predictions to input parameters, including cathodic reaction kinetics and the relative position of the anode and cathode. Predictions have also been made of the aeration period of the repository, during which localised corrosion is possible.

Impact of microbial activity on the radioactive waste disposal: long term prediction of biocorrosion processes

2014 ◽  
Vol 97 ◽  
pp. 162-168 ◽  
Author(s):  
Marie Libert ◽  
Marta Kerber Schütz ◽  
Loïc Esnault ◽  
Damien Féron ◽  
Olivier Bildstein
Keyword(s):  
Radioactive Waste ◽  
Microbial Activity ◽  
Waste Disposal ◽  
Radioactive Waste Disposal ◽  
Term Prediction ◽  
Long Term Prediction

Long-term prediction on atmospheric corrosion data series of carbon steel in China based on NGBM(1,1) model and genetic algorithm

2019 ◽  
Vol 66 (4) ◽  
pp. 403-411 ◽  
Author(s):  
Yuanjie Zhi ◽  
Dongmei Fu ◽  
Tao Yang ◽  
Dawei Zhang ◽  
Xiaogang Li ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Carbon Steel ◽  
Atmospheric Corrosion ◽  
Data Series ◽  
Data Sets ◽  
Content Type ◽  
Term Prediction ◽  
Long Term Prediction ◽  
Corrosion Data

PurposeThis study aims to achieve long-term prediction on a specific monotonic data series of atmospheric corrosion rate vs time.Design/methodology/approachThis paper presents a new method, used to the collected corrosion data of carbon steel provided by the China Gateway to Corrosion and Protection, that combines non-linear gray Bernoulli model (NGBM(1,1) with genetic algorithm to attain the purpose of this study.FindingsResults of the experiments showed that the present study’s method is more accurate than other algorithms. In particular, the mean absolute percentage error (MAPE) and the root mean square error (RMSE) of the proposed method in data sets are 9.15 per cent and 1.23 µm/a, respectively. Furthermore, this study illustrates that model parameter can be used to evaluate the similarity of curve tendency between two carbon steel data sets.Originality/valueCorrosion data are part of a typical small-sample data set, and these also belong to a gray system because corrosion has a clear outcome and an uncertainly occurrence mechanism. In this work, a new gray forecast model was proposed to achieve the goal of long-term prediction of carbon steel in China.

scholarly journals Source Term Development For Tritium at the Sheffield Disposal Site

1984 ◽  
Vol 44 ◽  
Author(s):  
D. R. Mackenzie ◽  
R. E. Barletta ◽  
J. F. Smalley ◽  
C. R. Kempf ◽  
R. E. Davis
Keyword(s):  
Radioactive Waste ◽  
Waste Disposal ◽  
Source Term ◽  
Fuel Cycle ◽  
Radioactive Waste Disposal ◽  
Disposal Site ◽  
Waste Disposal Site ◽  
Groundwater Samples ◽  
Low Level Radioactive Waste

AbstractThe Sheffield low-level radioactive waste disposal site, which ceased operation in 1978, has been the focus of modeling efforts by the NRC for the purpose of predicting long-term site behavior. To provide the NRC with information required for its modeling effort, a study to define the source term for tritium in eight trenches at the Sheffield site has been undertaken. Tritium is of special interest since significant concentrations of the isotope have been found in groundwater samples taken at the site and at locations outside the original site boundary. Previous estimates of tritium site inventory at Sheffield are in wide disagreement. In this study, the tritium inventory in the eight trenches was estimated by reviewing the radioactive shipping records (RSRs) for waste buried in these trenches. It has been found that the tritium shipped for burial at the site was probably higher than previously estimated. In the eight trenches surveyed, which amount to roughly one half the total volume and activity buried at Sheffield, approximately 2350 Ci of tritium from non-fuel cycle sources were identified.

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