• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.31 no.3
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• pp.95-100
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• 2003

Electronic equipment used in satellites are demanding extremely high reliability, so they should be designed to have immunity for some critical faults by using redundancy component. Generally, Communication satellites are assigned to meet the 15 years mission lifetime, of the analysis about faults must be performed to electronic equipments of satellite. This paper is a summary of the fault tolerance design research of command processor, the improvement of reliability and trade-off study of fault tolerance design result. The reliability prediction value of the satellite component used in this research was taken from Koreasat 3 and Kompsat 1. It is important to perform many trade-off studies for fault tolerance design, especially to choose the most proper fault tolerance method for the specified fault scenario.

• Journal of the Korean Society of Hazard Mitigation
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• v.8 no.3
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• pp.77-86
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• 2008

A database program is constructed by collecting all information related to shallow foundations such as measured load-settlement data, foundation shapes and sizes, properties of soils under the foundation and various measured data obtained from field investigation methods including CPT, PMT and SPT etc.. Based on the database program, a special program module is developed for performing statistical analyses of reliability and accuracy of predicting equations used for calculation of settlement of the shallow foundations. Special interests are focused not only on the settlement, but also on the settlement to width ratio (s/B). Results of the reliability and accuracy analyses on five available settlement equations are provided. Conclusions based on the provided results can be confirmed by extending number of related reliable data about the shallow foundations and can be adapted as guidelines for design of the shallow foundations.

• IEMEK Journal of Embedded Systems and Applications
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• v.13 no.3
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• pp.143-149
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• 2018

It has become ever harder to design reliable circuits with each nanometer technology node; under normal operation conditions, a transistor device can be affected by various aging effects resulting in performance degradation and eventually design failure. The reliability (aging) effect has traditionally been the area of process engineers. However, in the future, even the smallest of variations can slow down a transistor's switching speed, and an aging device may not perform adequately at a very low voltage. Therefore, circuit designers need to consider these reliability effects in the early stages of design to make sure there are enough margins for circuits to function correctly over their entire lifetime. However, such an approach excessively increases the size and power dissipation of a system. As the impact of reliability, new techniques in designing aging-resilient circuits are necessary to reduce the impact of the aging stresses on performance, power, and yield or to predict the failure of a system. Therefore, in this paper, a novel low power on-chip self-tuning circuit considering the aging effects has been proposed.

• Structural Engineering and Mechanics
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• v.29 no.1
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• pp.17-35
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• 2008

Neglecting the real joint behaviour in frame analysis may result in unrealistic predictions of the response and reliability of steel frames. The reliability of the prediction of main joint properties according to the component method (Eurocode 3-Part 1.8) still remains open to further investigation. The first step toward the solution is to compare the theoretical expressions given in EN 1993-1-8 and the experimental results. With that goal in mind six nominally the same, but really different specimens of welded beam-to-column joints subjected to static load were tested. The specimens present a combination of nominally identical structural elements produced in different European mills. This paper provides these tests, as well as their detailed evaulation and interpretation. All three joint structural properties (rotational stiffness, moment resistance and rotation capacity) have been considered. Four models for determining the plastic resistance out of experimental Mj-${\phi}$ curves have been applied. The results that have been discussed in detail, point to the fact that EN 1993-1-8 underestimates the real structural properties of the tested type of joint, as well as to the conclusion that detailed research of this problem needs to be conducted using the probabilistic reliability methods.

• Journal of Mechanical Science and Technology
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• v.19 no.6
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• pp.1280-1289
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• 2005

This paper presents the effects of corrosion environments of failure pressure model for buried pipelines on failure prediction by using a failure probability. The FORM (first order reliability method) is used in order to estimate the failure probability in the buried pipelines with corrosion defects. The effects of varying distribution types of random variables such as normal, lognormal and Weibull distributions on the failure probability of buried pipelines are systematically investigated. It is found that the failure probability for the MB31G model is larger than that for the B31G model. And the failure probability is estimated as the largest for the Weibull distribution and the smallest for the normal distribution. The effect of data scattering in corrosion environments on failure probability is also investigated and it is recognized that the scattering of wall thickness and yield strength of pipeline affects the failure probability significantly. The normalized margin is defined and estimated. Furthermore, the normalized margin is used to predict the failure probability using the fitting lines between failure probability and normalized margin.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.2
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• pp.14-22
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• 2021

A plan for the development of reliability-based ROK amphibious assault vehicles is proposed. By analyzing the development case of the U.S. EFV, considerations for the successful development of the next-generation Korea Forces amphibious assault vehicle are presented. If the vehicle reliability can be improved to the level of the fourth highest priority electric unit for power units, suspensions, decelerators, and body groups, which have the highest priority among fault frequency items, a system level MTBF of 36.4%↑ can be achieved, and the operational availability can be increased by 3.5%↑. The next-generation amphibious assault vehicles must fulfill certain operating and performance requirements, the underlying systems must be built, and sequencing of the hybrid engine and the modular concept should be considered. Along with big-data- and machine-learning-based failure prediction, machine maintenance based on augmented reality/virtual reality and remote maintenance should be used to improve the ability to maintain combat readiness and reduce lifecycle costs.

• Environmental Analysis Health and Toxicology
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• v.30 no.sup
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• pp.7.1-7.10
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• 2015

Objectives For successful adoption of legislation controlling registration and assessment of chemical substances, it is important to obtain sufficient toxicological experimental evidence and other related information. It is also essential to obtain a sufficient number of predicted risk and toxicity results. Particularly, methods used in predicting toxicities of chemical substances during acquisition of required data, ultimately become an economic method for future dealings with new substances. Although the need for such methods is gradually increasing, the-required information about reliability and applicability range has not been systematically provided. Methods There are various representative environmental and human toxicity models based on quantitative structure-activity relationships (QSAR). Here, we secured the 10 representative QSAR-based prediction models and its information that can make predictions about substances that are expected to be regulated. We used models that predict and confirm usability of the information expected to be collected and submitted according to the legislation. After collecting and evaluating each predictive model and relevant data, we prepared methods quantifying the scientific validity and reliability, which are essential conditions for using predictive models. Results We calculated predicted values for the models. Furthermore, we deduced and compared adequacies of the models using the Alternative non-testing method assessed for Registration, Evaluation, Authorization, and Restriction of Chemicals Substances scoring system, and deduced the applicability domains for each model. Additionally, we calculated and compared inclusion rates of substances expected to be regulated, to confirm the applicability. Conclusions We evaluated and compared the data, adequacy, and applicability of our selected QSAR-based toxicity prediction models, and included them in a database. Based on this data, we aimed to construct a system that can be used with predicted toxicity results. Furthermore, by presenting the suitability of individual predicted results, we aimed to provide a foundation that could be used in actual assessments and regulations.

• International Journal of Highway Engineering
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• v.13 no.1
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• pp.69-77
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• 2011

This study is to suggest a methodology to overcome the uncertainty and lack of reliability of data. The fuzzy reasoning model and the neural network model were developed in order to overcome the potential lack of reliability which may occur during the process of data collection. According to the result of comparison with the Poisson regression model, the suggested models showed better performance in the accuracy of the accident frequency prediction. It means that the more accurate accident frequency prediction model can be developed by the process of the uncertainty of raw data and the adjustment of errors in data by learning. Among the suggested models, the performance of the neural network model was better than that of the fuzzy reasoning model. The suggested models can evaluate the safety of signalized intersections in operation and/or planning, and ultimately contribute the reduction of accidents.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.4
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• pp.14-25
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• 2018

In recent years, it has become technically easier to explain factors related with traffic accidents in the Big Data era. Therefore, it is necessary to apply the latest analysis techniques to analyze the traffic accident data and to seek for new findings. The purpose of this study is to compare the predictive performance of the negative binomial regression model and the deep learning method developed in this study to predict the frequency of traffic accidents in expressways. As a result, the MOEs of the deep learning model are somewhat superior to those of the negative binomial regression model in terms of prediction performance. However, using a deep learning model could increase the predictive reliability. However, it is easy to add other independent variables when using deep learning, and it can be expected to increase the predictive reliability even if the model structure is changed.

• Journal of the Korea institute for structural maintenance and inspection
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• v.20 no.1
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• pp.48-55
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• 2016

The assessment and prediction of service life of a structure are usually under uncertainty so that rational probabilistic concepts and methods have to be applied. Based on these rational assessment and prediction, optimum maintenance strategies to minimize the life-cycle cost and/or maximize the structural safety can be established. The service life assessment and prediction considering maintenance actions generally includes effects of maintenance types and times of the structural components on the service life extensions of structural system. Existing researches on the service life management have revealed the appropriate system modeling considering the correlation among the components is required for system reliability analysis and probabilistic service life estimation. However, the study on correlation among the maintenance actions is still required. This paper deals with such a study for more effective and efficient service life management. In this paper, both the preventive and essential maintenances are considered for the extended service life estimation and management.