• Nuclear Engineering and Technology
• /
• v.54 no.4
• /
• pp.1195-1205
• /
• 2022

Recent developments on spectral diffusion algorithms, i.e., algorithms which exploit the projection of the solution on the eigenfunctions of the Laplacian operator, demonstrated their effective applicability in fast transient conditions. Nevertheless, the numerical error introduced by these algorithms, together with the uncertainties associated with model parameters, may impact the reliability of the predictions on short-lived volatile fission product release from nuclear fuel. In this work, we provide an upper bound on the numerical error introduced by the presented spectral diffusion algorithm, in both constant and time-varying conditions, depending on the number of modes and on the time discretization. The definition of this upper bound allows introducing a methodology to a priori bound the numerical error on short-lived volatile fission product retention.

• Journal of the Society of Disaster Information
• /
• v.16 no.1
• /
• pp.133-143
• /
• 2020

Purpose: This study aims to derive a predictive empirical equation for PGV prediction from P-wave using earthquake records in Korea and to verify the reliability of Onsite EEW. Method: The noise of P wave is removed from the observations of 627 seismic events in Korea to derive an empirical equation with PGV on the base rock, and reliability of Onsite alarms is verified from comparing PGV's predictions and observations through simulation using the empirical equation. Result: P-waves were extracted using the Filter Picker from earthquake observation records that eliminated noises, a linear regression with PGV was used to derive a predictive empirical equation for Onsite EEW. Through the on-site warning simulation we could get a success rate of 80% within the MMI±1 error range above MMI IV or higher. Conclusion: Through this study, the design feasibility and performance of Onsite EEWS using domestic earthquake records were verified. In order to increase validity, additional medium-sized seismic observations from abroad are required, the mis-detection of P waves is controlled, and the effect of seismic amplification on the surface is required.

• KOREAN JOURNAL OF CROP SCIENCE
• /
• v.56 no.1
• /
• pp.88-93
• /
• 2011

This experiment was carried out to find suitable sample type for the more accurate prediction and non-destructive way in the application of near infrared reflectance spectroscopy (NIRS) technique for estimation the protein, total amino acids, and total isoflavone of soybean by comparing three different sample types, single seed, whole seeds, and milled seeds powder. The coefficient of determination in calibration ($R^2$) and coefficient of determination in cross-validation (1-VR) for three components analyzed using NIRS revealed that milled powder sample type yielded the highest, followed by single seed, and the whole seeds as the lowest. The coefficient of determination in calibration for single seed was moderately low($R^2$ 0.70-0.84), while the calibration equation developed with NIRS data scanned with whole seeds showed the lowest accuracy and reliability compared with other sample groups. The scatter plot for NIRS data versus the reference data of whole seeds showed the widest data cloud, in contrary with the milled powder type which showed flatter data cloud. By comparison of NIRS results for total isoflavone, total amino acids, and protein of soybean seeds with three sample types, the powder sample could be estimated for the most accurate prediction. However, based from the results, the use of single bean samples, without grinding the seeds and in consideration with NIRS application for more nondestructive and faster prediction, is proven to be a promising strategy for soybean component estimation using NIRS.

• Journal of Welding and Joining
• /
• v.17 no.1
• /
• pp.124-132
• /
• 1999

Thermal fatigue strength of the solder joints is the most critical issue for TSOP(Thin Small Outline Package) because the leads of this package are extremely short and thermal deformation cannot be absorbed by the deflection of the lead. And the TSOP body can be subject to early fatigue failures in thermal cycle environments. This paper was discussed distribution of thermal stresses at near the joint between silicon chip and die pad and investigated their reliability of solder joints of TSOP with 42 alloy clad lead frame on printed circuit board through FEM and 3 different thermal cycling tests. It has been found that the stress concentration around the encapsulated edge structure for internal crack between the silicon chip and Cu alloy die pad. And using 42 alloy clad, The reliability of TSOP body was improved. In case of using 42 alloy clad die pad(t=0.03mm). $$\sigma$_{VMmax}$ is 69Mpa. It is showed that 15% improvement of the strength in the TSOP body in comparison with using Cu alloy die pad $($\sigma$_{VMmax}$=81MPa). In solder joint of TSOP, the maximum equivalent plastic strain and Von Mises stress concentrate on the heel of solder fillet and crack was initiated in it's region and propagated through the interface between lead and solder. Finally, the modified Manson-Coffin equation and relationship of the ratio of $N_{f}$ to nest(η) and cumulative fracture probability(f) with respect to the deviations of the 50% fracture probability life $(N_{f 50%})$ were achieved.

• Journal of the Korean Institute of Gas
• /
• v.5 no.2 s.14
• /
• pp.30-35
• /
• 2001

Presently, working gas pipelines are being subjected to the influence of construction vibration. Especially on subway and road construction, gas pipelines are being influenced to construction vibration caused by use of construction equipment, passage of a large-sized vehicle and blasting. Buried gas pipelines are subjected to the influence of vibration caused by blast in the vicinity of pipeline, exposed gas pipelines are subjected to the influence of vehicle vibration. Therefore, in the study, it is developed to vibration prediction program of gas pipeline by analyzing measured construction vibration. This program is able to predict vibration of gas pipeline according to field conditions by using the results of structural finite element analysis and empirical equation by reliability analysis. And, this program contains the database of construction vibration. Additionally, this program is able to compute estimated blast vibration equation using measured blast vibration data in the field and to form graph of allowable charging gunpowder per delayed-action with the change of blast velocity. Therefore, field workers are able to predict construction vibration around gas pipeline and estimate safety of gas pipeline.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2023.05a
• /
• pp.100-103
• /
• 2023

Recently, development of maritime autonomoust surface ships and eco-friendly ships, production and evaluation research considering various marine environments is needed in the field of optimal routes as the demand for accurate and detailed real-time marine environment prediction information expands. An algorithm that can calculate the optimal route while reducing the risk of the marine environment and uncertainty in energy consumption in smart ships was developed in 2 stages. In the first stage, a profile was created by combining marine environmental information with ship location and status information within the Automatic Ship Identification System(AIS). In the second stage, a model was developed that could define the marine environment energy map using the configured profile results, A regression equation was generated by applying Random Forest among machine learning techniques to reflect about 600,000 data. The Random Forest coefficient of determination (R²) was 0.89, showing very high reliability. The Dijikstra shortest path algorithm was applied to the marine environment prediction at June 1 to 3, 2021, and to calculate the optimal safety route and express it on the map. The route calculated by the random forest regression model was streamlined, and the route was derived considering the state of the marine environment prediction information. The concept of route calculation based on real-time marine environment prediction information in this study is expected to be able to calculate a realistic and safe route that reflects the movement tendency of ships, and to be expanded to a range of economic, safety, and eco-friendliness evaluation models in the future.

• Journal of Korea Water Resources Association
• /
• v.53 no.9
• /
• pp.661-670
• /
• 2020

The water supply system has a wider installation range and various components of it than other infrastructure, making it difficult to secure stability against earthquakes. Therefore, it is necessary to develop methods for evaluating the seismic performance of water supply systems. Ground Motion Prediction Equation (GMPE) is used to evaluate the seismic performance (e.g, failure probability) for water supply facilities such as pump, water tank, and pipes. GMPE is calculated considering the independent variables such as the magnitude of the earthquake and the ground motion such as PGV (Peak Ground Velocity) and PGA (Peak Ground Acceleration). Since the large magnitude earthquake data has not accumulated much to date in Korea, this study tried to select a suitable GMPE for the domestic earthquake simulation by using the earthquake data measured in Korea. To this end, GMPE formula is calculated based on the existing domestic earthquake and presented the results. In the future, it is expected that the evaluation will be more appropriate if the determined GMPE is used when evaluating the seismic performance of domestic waterworks. Appropriate GMPE can be directly used to evaluate hydraulic seismic performance of water supply networks. In other words, it is possible to quantify the damage rate of a pipeline during an earthquake through linkage with the pipe failure probability model, and it is possible to derive more reasonable results when estimating the water outage or low-pressure area due to pipe damages. Finally, the quantifying result of the seismic performance can be used as a design criteria for preparing an optimal restoration plan and proactive seismic design of pipe networks to minimize the damage in the event of an earthquake.

• Journal of Korean Academy of Nursing
• /
• v.36 no.1
• /
• pp.37-44
• /
• 2006

Purpose: This research has been conducted in order to understand the major factors that affect self-esteem of adolescents. Methods: Data was collected by questionnaires from 1155 students at middle and high school in Seoul and Kyungkido, Korea. The Instrument tools utilized in this study were self-esteem, body-image, problematic behavior, depression, school adjustment, social support tool and thoroughly modified to verify validity and reliability. The collected data have been analyzed using SPSS 11.0 program. The variable of family harmony and counseling partner was treated as a dummy variable. Seven outliers which were bigger than 3 in absolute value were found, so after taking them off, Multiple Regression was used for further analysis. Result: The major factors that affect self-esteem of adolescents were depression, social support, body-image, problematic behavior, school adjustment, and family harmony, which explained $54.7\%$ of self-esteem. Conclusion: It has been confirmed that the regression equation model of this research may serve as a self-esteem prediction factors in adolescents.

• Journal of East-West Nursing Research
• /
• v.13 no.1
• /
• pp.40-47
• /
• 2007

Purpose: This study has been attempted in order to confirm the factors that affect the healthpromotion lifestyle of nurses. Method: Data was collected by questionnaires from 324 nurses at 5 university hospitals located in Seoul. The instrument tools utilized in this study was health-promotion lifestyle, perceived health status, perceived benefits, perceived barriers, self-efficacy, and social support, and validity and reliability of the tool have been verified with literature studies and pre-study examinations. The collected data have been analyzed using SPSS PC 12 program. Result: The factors that affect health-promotion lifestyle of nurses were perceived health status ($\beta$= .320), self-efficacy ($\beta$= .248), social support ($\beta$= .139), perceived benefits ($\beta$= .207), and age ($\beta$= .089), that altogether explained 41.1%. Conclusion: It has been confirmed that th regression equation model of this research may serve as a health- promotion lifestyle prediction factors in nurses.

• Proceedings of the Korean Society of Agricultural Engineers Conference
• /
• 2001.10a
• /
• pp.156-161
• /
• 2001

Currently, agricultural facilities are evaluated using either basic inspections or detailed analysis. However, conventional analyses as well as methods based on fuzzy logic and rule of thumb have not been very successful in providing a clear relationship between rating and real state of agricultural facilities, because they can't provide exactly acceptable reliability of degraded structures with manager or supervisor. Therefore, in this stage, we must define probabilistic variables for representing degradation of structures being given damages during a survival time. This paper describes the application of neural network system in developing the relation between subjective ratings and parameters of agricultural reservoir as well as that between subjective and analytical ratings. It is shown that neural networks can be trained and used successfully in estimating a rating based on several parameters. The specific application problem for agricultural reservoir in the rural area of Korea is presented and database is constructed to maintain training data set, the information of inspection and facilities. This study showed that a successful training of a neural network could be useful, especially if the input data set for target problem contains parameters with a diverse combination of inter-correlation coefficients. And the networks had a prediction rating of about $^{\ast}^{\ast}^{\ast}%$. The neural network system is expected to show high performance fairly in estimate than statistical method to use equation that is consisted of very lowly interrelated variables.