Abstract
Deterministic Safety Analysis and Probabilistic Safety Assessment (PSA) analyses are used concurrently to assess the Nuclear Power Plant (NPP) safety. The conventional deterministic analysis is conservative. The best estimate plus uncertainty analysis is increasingly being used for deterministic calculation in NPPs. The PSA methodology aims to be as realistic as possible while integrating information about accident phenomena, plant design, operating practices, component reliability and human behaviour. The peak clad temperature (PCT) distribution provides an insight into the confidence in safety margin for an initiating event. The paper deals with the concept of calculating the peak clad temperature with 95 percent confidence and 95 percent probability (PCT{sub 95/95}) in small break loss of coolant accident (SBLOCA) and methodologies for assessing safety margin. Five input parameters mainly, nominal power level, decay power, fuel clad gap conductivity, fuel thermal conductivity and discharge coefficient, were selected. A Uniform probability density function was assigned to the uncertain parameters and these uncertainties are propagated using Latin Hypercube Sampling (LHS) technique. The sampled data for 5 parameters were randomly mixed by LHS to obtain 25 input sets. A non-core damage accident sequence was selected from the SBLOCA event tree of a typical VVER study to estimate the
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Nagrale, D. B.;
Prasad, M.;
Rao, R. S.;
Gaikwad, A.J., E-mail: avinashg@aerb.gov.in
[1]
- Nuclear Safety Analysis Division, Atomic Energy Regulatory Board, Mumbai (India)
Citation Formats
Nagrale, D. B., Prasad, M., Rao, R. S., and Gaikwad, A.J., E-mail: avinashg@aerb.gov.in.
Methodology for the Assessment of Confidence in Safety Margin for Small Break Loss of Coolant Accident Sequences.
IAEA: N. p.,
2014.
Web.
Nagrale, D. B., Prasad, M., Rao, R. S., & Gaikwad, A.J., E-mail: avinashg@aerb.gov.in.
Methodology for the Assessment of Confidence in Safety Margin for Small Break Loss of Coolant Accident Sequences.
IAEA.
Nagrale, D. B., Prasad, M., Rao, R. S., and Gaikwad, A.J., E-mail: avinashg@aerb.gov.in.
2014.
"Methodology for the Assessment of Confidence in Safety Margin for Small Break Loss of Coolant Accident Sequences."
IAEA.
@misc{etde_22318545,
title = {Methodology for the Assessment of Confidence in Safety Margin for Small Break Loss of Coolant Accident Sequences}
author = {Nagrale, D. B., Prasad, M., Rao, R. S., and Gaikwad, A.J., E-mail: avinashg@aerb.gov.in}
abstractNote = {Deterministic Safety Analysis and Probabilistic Safety Assessment (PSA) analyses are used concurrently to assess the Nuclear Power Plant (NPP) safety. The conventional deterministic analysis is conservative. The best estimate plus uncertainty analysis is increasingly being used for deterministic calculation in NPPs. The PSA methodology aims to be as realistic as possible while integrating information about accident phenomena, plant design, operating practices, component reliability and human behaviour. The peak clad temperature (PCT) distribution provides an insight into the confidence in safety margin for an initiating event. The paper deals with the concept of calculating the peak clad temperature with 95 percent confidence and 95 percent probability (PCT{sub 95/95}) in small break loss of coolant accident (SBLOCA) and methodologies for assessing safety margin. Five input parameters mainly, nominal power level, decay power, fuel clad gap conductivity, fuel thermal conductivity and discharge coefficient, were selected. A Uniform probability density function was assigned to the uncertain parameters and these uncertainties are propagated using Latin Hypercube Sampling (LHS) technique. The sampled data for 5 parameters were randomly mixed by LHS to obtain 25 input sets. A non-core damage accident sequence was selected from the SBLOCA event tree of a typical VVER study to estimate the PCTs and safety margin. A Kolmogorov– Smirnov goodness-of-fit test was carried out for PCTs. The smallest value of safety margin would indicate the robustness of the system with 95% confidence and 95% probability. Regression analysis was also carried out using 1000 sample size for the estimating PCTs. Mean, variance and finally safety margin were analysed. (author)}
place = {IAEA}
year = {2014}
month = {Oct}
}
title = {Methodology for the Assessment of Confidence in Safety Margin for Small Break Loss of Coolant Accident Sequences}
author = {Nagrale, D. B., Prasad, M., Rao, R. S., and Gaikwad, A.J., E-mail: avinashg@aerb.gov.in}
abstractNote = {Deterministic Safety Analysis and Probabilistic Safety Assessment (PSA) analyses are used concurrently to assess the Nuclear Power Plant (NPP) safety. The conventional deterministic analysis is conservative. The best estimate plus uncertainty analysis is increasingly being used for deterministic calculation in NPPs. The PSA methodology aims to be as realistic as possible while integrating information about accident phenomena, plant design, operating practices, component reliability and human behaviour. The peak clad temperature (PCT) distribution provides an insight into the confidence in safety margin for an initiating event. The paper deals with the concept of calculating the peak clad temperature with 95 percent confidence and 95 percent probability (PCT{sub 95/95}) in small break loss of coolant accident (SBLOCA) and methodologies for assessing safety margin. Five input parameters mainly, nominal power level, decay power, fuel clad gap conductivity, fuel thermal conductivity and discharge coefficient, were selected. A Uniform probability density function was assigned to the uncertain parameters and these uncertainties are propagated using Latin Hypercube Sampling (LHS) technique. The sampled data for 5 parameters were randomly mixed by LHS to obtain 25 input sets. A non-core damage accident sequence was selected from the SBLOCA event tree of a typical VVER study to estimate the PCTs and safety margin. A Kolmogorov– Smirnov goodness-of-fit test was carried out for PCTs. The smallest value of safety margin would indicate the robustness of the system with 95% confidence and 95% probability. Regression analysis was also carried out using 1000 sample size for the estimating PCTs. Mean, variance and finally safety margin were analysed. (author)}
place = {IAEA}
year = {2014}
month = {Oct}
}