• Nuclear Engineering and Technology
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• v.54 no.11
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• pp.4049-4061
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• 2022

TRISO-coated particle fuel is widely used in high temperature gas cooled reactors and other advanced reactors. The performance of coated fuel particle is one of the fundamental bases of reactor safety. The failure probability of coated fuel particle should be evaluated and determined through suitable fuel performance models and methods during normal and accident condition. In order to better facilitate the design of coated particle fuel, a new TRISO fuel performance code named FRAT (Fission product Release Analysis Tool) was developed. FRAT is designed to calculate internal gas pressure, mechanical stress and failure probability of a coated fuel particle. In this paper, FRAT was introduced and benchmarked against IAEA CRP-6 benchmark cases for coated particle failure analysis. FRAT's results agree well with benchmark values, showing the correctness and satisfactory applicability. This work helps to provide a foundation for the credible application of FRAT.

• Journal of the Korea Safety Management & Science
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• v.9 no.6
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• pp.31-38
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• 2007

The construction industry by its nature retains higher level of danger where the smallest of error may lead to a major catastrophe endangering many workers and public safety as well as provoke social criticism. With the aid of quantitative statistical data on safety-related calamity analyzed till this day, this paper handled in depth the analysis of diseases other than the accidents, and selected new variable indexes that influence the indirect sections of calamity that are mostly concealed and incorporated them in a new model. For the factor selection of new calamity evaluation model, FRAT(Frequency, Recency, Amount, Type of merchandise/service)technique of customer-related management in marketing was applied, and as for the significance of each factor in the weight selection of variables. Consequently, considering the graveness of the FRAT itself through safety management experts, the related researches must be expanded.

• Journal of Digital Contents Society
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• v.14 no.4
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• pp.419-428
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• 2013

Real-time accessibility and agility are required in u-commerce under ubiquitous computing environment. Most of the existing recommendation techniques adopt the method of evaluation based on personal profile, which has been identified with difficulties in accurately analyzing the customers' level of interest and tendencies, as well as the problems of cost, consequently leaving customers unsatisfied. Researches have been conducted to improve the accuracy of information such as the level of interest and tendencies of the customers. However, the problem lies not in the preconstructed database, but in generating new and diverse profiles that are used for the evaluation of the existing data. Also it is difficult to use the unique recommendation method with hierarchy of each customer who has various characteristics in the existing recommendation techniques. Accordingly, this dissertation used the implicit method without onerous question and answer to the users based on the data from purchasing, unlike the other evaluation techniques. We applied FRAT technique which can analyze the tendency of the various personalization and the exact customer.

• Journal of Digital Contents Society
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• v.15 no.6
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• pp.711-719
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• 2014

Along with the advent of ubiquitous computing environment, it is becoming a part of our common life style that the demands for enjoying the wireless internet using intelligent portable device such as smart phone and iPad, are increasing anytime or anyplace without any restriction of time and place. The recommending service becomes a very important technology which can find exact information to present users, then is easy for customers to reduce their searching effort to find out the items with high purchasability in e-commerce. Traditional mining association rule ignores the difference among the transactions. In order to do that, it is considered the importance of type of merchandise or service and then, we suggest a new recommending service using mining sequential pattern based on weight to reflect frequently changing trends of purchase pattern as time goes by and as often as customers need different merchandises on e-commerce being extremely diverse. To verify improved better performance of proposing system than the previous systems, we carry out the experiments in the same dataset collected in a cosmetic internet shopping mall.