• Earthquakes and Structures
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• v.26 no.6
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• pp.433-447
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• 2024

During earthquakes, regular buildings perform better than irregular buildings. In general, seismic design codes define a regular building using estimates of Storey Stiffness and Storey Strength. At present, seismic design codes do not recommend a specific method to estimate these parameters. Consequently, any method described in the literature can be applied to estimate the aforementioned parameters. Nevertheless, research has demonstrated that storey stiffness and storey strength vary depending on the estimation method employed. As a result, the same building can be regular or irregular, depending on the method employed to estimate storey stiffness and storey strength. Hence, there is a need to identify the best method to estimate storey stiffness and storey strength. For this purpose, the study presents a qualitative and quantitative evaluation of nine approaches used to determine storey stiffness. Similarly, the study compares six approaches for estimating storey strength. Subsequently, the study identifies the best method to estimate storey stiffness and storey strength using results of 350 linear time history analyses and 245 nonlinear time history analyses, respectively. Based on the comparison, it is concluded that the Fundamental Lateral Translational Mode Shape Method and Isolated Storey Method - A Particular Case are the best methods to estimate storey stiffness and storey strength of low-to-mid rise buildings, respectively.

• Nuclear Engineering and Technology
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• v.48 no.2
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• pp.419-433
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• 2016

One of the important severe accident management measures in the Light Water Reactors is water injection to the reactor core. The related phenomena are investigated by performing experiments and computer simulations. One of the most widely known is the QUENCH test-program. A number of analyses on QUENCH tests have also been performed by different computer codes for code validation and improvements. Unfortunately, any deterministic computer simulation is not free from the uncertainties. To receive the realistic calculation results, the best estimate computer codes should be used for the calculation with combination of uncertainty and sensitivity analysis of calculation results. In this article, the QUENCH-03 and QUENCH-06 experiments are modelled using ASTEC and RELAP/SCDAPSIM codes. For the uncertainty and sensitivity analysis, SUSA3.5 and SUNSET tools were used. The article demonstrates that applying the best estimate approach, it is possible to develop basic QUENCH input deck and to develop the two sets of input parameters, covering maximal and minimal ranges of uncertainties. These allow simulating different (but with the same nature) tests, receiving calculation results with the evaluated range of uncertainties.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.20 no.1
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• pp.32-38
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• 2024

The best estimate plus uncertainty methodologies for loss-of-coolant accident analyses make use of the best-estimate codes and relevant experimental databases. Inherently, best-estimate codes have various uncertainties in the model parameters, which can be quantified by the dedicated experimental database. Therefore, this study was devoted to establishing procedures for identifying the input parameters of predictive models and quantifying their uncertainty ranges. The rod bundle heat transfer experiments were employed as a representative reflood separate effect test, and the TRACE code was utilized as a best-estimate code. In accordance with the present procedure for uncertainty quantification, the integrated list of the influential input parameters and their uncertainty ranges was obtained through local sensitivity calculations and screening criteria. The validity of the procedure was confirmed by applying it to uncertainty analyses, which checks whether the measured data are within computed ranges of the variables of interest. The uncertainty quantification procedure proposed in this study is anticipated to provide comprehensive guidance for the conduct of uncertainty analyses.

• Magazine of the Korean Society of Agricultural Engineers
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• v.44 no.6
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• pp.49-60
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• 2002

This study was conducted to estimate the design flood by the determination of best fitting order of LH-moments of the annual maximum series at six and nine watersheds in Korea and Australia, respectively. Adequacy for flood flow data was confirmed by the tests of independence, homogeneity, and outliers. Gumbel (GUM), Generalized Extreme Value (GEV), Generalized Pareto (GPA), and Generalized Logistic (GLO) distributions were applied to get the best fitting frequency distribution for flood flow data. Theoretical bases of L, L1, L2, L3 and L4-moments were derived to estimate the parameters of 4 distributions. L, L1, L2, L3 and L4-moment ratio diagrams (LH-moments ratio diagram) were developed in this study. GEV distribution for the flood flow data of the applied watersheds was confirmed as the best one among others by the LH-moments ratio diagram and Kolmogorov-Smirnov test. Best fitting order of LH-moments will be derived by the confidence analysis of estimated design flood in the second report of this study.

• Proceedings of the Korean Nuclear Society Conference
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• 1997.10a
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• pp.611-616
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• 1997

The thermal-hydraulic effects of removing the RCC guide thimble plugs are evaluated for 8 Westinghouse type PWR plants in Korea as a part of feasibility study: core outlet loss coefficient, thimble bypass flow, and best estimate flow. It is resulted that the best estimate thimble bypass flow increases about by 2% and the best estimate flow increases approximately by 1.2%. The resulting DNBR penalties can be covered with the current DNBR margin. Accident analyses are also investigated that the dropped rod transient is shown to be limiting and relatively sensitive to bypass flow variation.

• Proceedings of the Korean Nuclear Society Conference
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• 1996.05b
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• pp.166-172
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• 1996

The thermal-hydraulic effects of removing the RCC guide thimble plugs are evaluated for Westinghouse type PWR plants as a part of feasibility study: core outlet loss coefficient, thimble bypass flow, and best estimate flow. It is resulted that the best estimate thimble bypass flow increases about by 2% and the best estimate flow increase approximately by 1.2%. The resulting DNBR penalties can be covered within the current DNBR margin. Accident analyses are also investigated and the dropped rod transient is shown to be limiting and relatively sensitive to bypass flow variation.

• Nuclear Engineering and Technology
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• v.55 no.7
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• pp.2670-2677
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• 2023

In the nuclear safety studies, a new trend refers to the evaluation of uncertainties as a mandatory component of best-estimate safety analysis which is a modern and technically consistent approach being known as BEPU (Best Estimate Plus Uncertainty). The major objectives of this study consist in performing a study of uncertainties/sensitivities of the major analysis results for a generic CANDU 6 Nuclear Power Plant during Station Blackout (SBO) progression to understand and characterize the sources of uncertainties and their effects on the key figure-of-merits (FOMs) predictions in severe accidents (SA). The FOMs of interest are hydrogen mass generation and event timings such as the first fuel channel failure time, beginning of the core disassembly time, core collapse time and calandria vessel failure time. The outcomes of the study, will allow an improvement of capabilities and expertise to perform uncertainty and sensitivity analysis with severe accident codes for CANDU 6 Nuclear Power Plant.

• Nuclear Engineering and Technology
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• v.46 no.4
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• pp.541-546
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• 2014

Probabilistic Safety Assessment (PSA) has been widely used to estimate the overall safety of nuclear power plants (NPP) and it provides base information for risk informed application (RIA) and risk informed regulation (RIR). For the effective and correct use of PSA in RIA/RIR related decision making, the risk estimated by a PSA model should be as realistic as possible. In this work, a best-estimate thermal-hydraulic analysis of loss-of-coolant accidents (LOCAs) for the Hanul Nuclear Units 3&4 is first carried out in a systematic way. That is, the behaviors of peak cladding temperature (PCT) were analyzed with various combinations of break sizes, the operating conditions of safety systems, and the operator's action time for aggressive secondary cooling. Thereafter, the results of the thermal-hydraulic analysis have been reflected in the improvement of the PSA model by changing both accident sequences and success criteria of the event trees for the LOCA scenarios.

• Journal of the Korean Society of Systems Engineering
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• v.19 no.2
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• pp.18-31
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• 2023

Exploring artificial intelligence and machine learning for nuclear safety has witnessed increased interest in recent years. To contribute to this area of research, a machine learning model capable of accurately predicting nuclear power plant response with minimal computational cost is proposed. To develop a robust machine learning model, the Best Estimate Plus Uncertainty (BEPU) approach was used to generate a database to train three models and select the best of the three. The BEPU analysis was performed by coupling Dakota platform with the best estimate thermal hydraulics code RELAP/SCDAPSIM/MOD 3.4. The Code Scaling Applicability and Uncertainty approach was adopted, along with Wilks' theorem to obtain a statistically representative sample that satisfies the USNRC 95/95 rule with 95% probability and 95% confidence level. The generated database was used to train three models based on Recurrent Neural Networks; specifically, Long Short-Term Memory, Gated Recurrent Unit, and a hybrid model with Long Short-Term Memory coupled to Convolutional Neural Network. In this paper, the System Engineering approach was utilized to identify requirements, stakeholders, and functional and physical architecture to develop this project and ensure success in verification and validation activities necessary to ensure the efficient development of ML meta-models capable of predicting of the nuclear power plant response.

• Genomics & Informatics
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• v.12 no.4
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• pp.254-260
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• 2014

Best linear unbiased prediction (BLUP) has been used to estimate the fixed effects and random effects of complex traits. Traditionally, genomic relationship matrix-based (GRM) and random marker-based BLUP analyses are prevalent to estimate the genetic values of complex traits. We used three methods: GRM-based prediction (G-BLUP), random marker-based prediction using an identity matrix (so-called single-nucleotide polymorphism [SNP]-BLUP), and SNP-SNP variance-covariance matrix (so-called SNP-GBLUP). We used 35,675 SNPs and R package "rrBLUP" for the BLUP analysis. The SNP-SNP relationship matrix was calculated using the GRM and Sherman-Morrison-Woodbury lemma. The SNP-GBLUP result was very similar to G-BLUP in the prediction of genetic values. However, there were many discrepancies between SNP-BLUP and the other two BLUPs. SNP-GBLUP has the merit to be able to predict genetic values through SNP effects.