• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2017.05a
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• pp.258-265
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• 2017

At the early stage of the development of high speed propulsion systems, the designers suffer from the lack of both the quantity and the quality of test data. In that situation, the associated uncertainties could not be modeled as probabilistic distribution since probabilistic modelling requires large amount of data. In this paper, instead, the information provided by experts based on their experience and engineering knowledge was used to model uncertainty using the evidence theory. In designing the DCR(Dual Combustion Ramjet) engine, the combustion efficiencies, not well understood and little data existing, are assumed to have been provided by experts. And the uncertainties are quantified by Evidence theory. The quantified uncertainties are incorporated into the optimization. The design variables, area of inlet and area of combustor exit, have been found while satisfying reliability margins of thrust and thermal choking. The results show a reasonable design of the engine under the uncertain circumstances.

• Nuclear Engineering and Technology
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• v.40 no.3
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• pp.199-212
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• 2008

A small-break loss of coolant accident (SB-LOCA) test with a break size equivalent to a 3-inch cold leg break of the APR1400 was carried out as the first transient integral effect test using the ATLAS (Advanced Thermal-hydraulic Test Loop for Accident Simulation). This was the first integral effect test to investigate the integral performance of the test facility and to verify its simulation capability for one of the design-basis accidents. Reasonably good thermal hydraulic data was obtained so that an integral performance of the fluid sub-systems was identified and control performance of the ATLAS was confirmed under real thermal hydraulic conditions. Based on the measured data, a post-test calculation was carried out using the best-estimate thermal hydraulic safety analysis code, MARS 3.1, and the similarity between the expected and actual data was investigated. On the whole, the post-test calculation reasonably predicts the major thermal hydraulic parameters measured during the SB-LOCA test. The obtained data will be used to enhance the simulation capability of the ATLAS and to improve an input model of the ATLAS for simulation of other target scenarios.

• Animal cells and systems
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• v.16 no.4
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• pp.329-336
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• 2012

This study evaluated ecological health, using various biomarkers and bioindicators, of pale chub (Zacco platypus) as a sentinel species, in Daejeon Stream, South Korea, during AprilMay 2011. The biomarkers and bioindicators were compared among three sites of control: Reference ($C_z$), transition ($T_z$), and the urban zones ($U_z$); and the 7-Ethoxyresorufin-O-deethylase (EROD) activity, DNA damage, acetylcholinesterase (AChE) activity, and vitellogenin (VTG) concentrations were more significantly increased in the $U_z$ than in the $C_z$. Also, physiological markers such as condition factor, liver somatic index, visceral somatic index, and gonad somatic index were significantly increased in the $U_z$ than in the $C_z$. For the health assessments, three categorized parameters of blood chemistry, molecular biomarkers, and physiological bioindicators were standardized and calculated as a star-plot, representing values of Integrated Health Response (IHR). Values of IHR had more significant (P<0.05) increases in the $U_z$ than any other zones, indicating an impairment of ecological health by organic matter, nutrients (N, P), and toxic chemicals. This study is based on low levels of biological organization approach of molecular and physiological biomarkers and bioindicators, so further study of high-levels of biological organization approach such as community and population is required for overall range of health assessments. The approach of IHR values, however, may be useful in providing early warning of future impacts on ecological health.

• International Journal of Highway Engineering
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• v.2 no.2
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• pp.139-148
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• 2000

Currently existing Accelerated Pavement Testing (APT) systems developed in several countries have been employed mainly to test the performance of asphalt pavement. Meanwhile, the length of concrete pavement is similar to that of asphalt pavement in expressways of Korea. and is expected to increase due to its durability and compatibility to our weather condition. To meet the society's demand of having our own APT system which can examine the long-term performance of concrete pavement, a contract study to develop Korea Accelerated Loading and Environment Simulator (KALES) for concrete pavement has been performed for 3 years from 1997 through 1999. Through the project, a detailed design was Peformed for the KALES system in which the entire structure of KALES, loading mechanism, wandering mechanism, suspension system, driving system were proposed. Also in advance to design a full-scale KALES system, a sample scale model was manufactured and tested for operating motion and force distribution. It is evident that the proposed prototype KALES system will provide higher degree of traffic simulation and durable operation, based on the satisfactory fatigue analysis.

• Journal of Korea Water Resources Association
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• v.41 no.10
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• pp.1059-1065
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• 2008

Rainfall data is the most basic input data to analyze the hydrological phenomena and can be missing due to various reasons. In this research, a neural network based model to estimate missing rainfall data as approximate values was developed for 12 rainfall stations in the Soyang river basin to improve existing methods. This approach using neural network has shown to be useful in many applications to deal with complicated natural phenomena and displayed better results compared to the popular offline estimating methods, such as RDS(Reciprocal Distance Squared) method and AMM(Arithmetic Mean Method). Additionally, we proposed automated data reconciliation systems composed of a neural network learning processer to be capable of real-time reconciliation to transmit reliable hydrological data online.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.9
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• pp.1492-1512
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• 2011

Due to multiple hops, mobility and time-varying channel, supporting delay sensitive real-time traffic in wireless local area network-based (WLAN) mesh networks is a challenging task. In particular for real-time traffic subject to medium access control (MAC) layer control overhead, such as preamble, carrier sense waiting time and the random backoff period, the performance of real-time flows will be degraded greatly. In order to support real-time traffic, an efficient adaptive packet scheduling (APS) scheme is proposed, which aims to improve the system performance by guaranteeing inter-class, intra-class service differentiation and adaptively adjusting the packet length. APS classifies incoming packets by the IEEE 802.11e access class and then queued into a suitable buffer queue. APS employs strict priority service discipline for resource allocation among different service classes to achieve inter-class fairness. By estimating the received signal to interference plus noise ratio (SINR) per bit and current link condition, APS is able to calculate the optimized packet length with bi-dimensional markov MAC model to improve system performance. To achieve the fairness of intra-class, APS also takes maximum tolerable packet delay, transmission requests, and average allocation transmission into consideration to allocate transmission opportunity to the corresponding traffic. Detailed simulation results and comparison with IEEE 802.11e enhanced distributed channel access (EDCA) scheme show that the proposed APS scheme is able to effectively provide inter-class and intra-class differentiate services and improve QoS for real-time traffic in terms of throughput, end-to-end delay, packet loss rate and fairness.

• Journal of the Korea Society for Simulation
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• v.24 no.3
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• pp.9-16
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• 2015

This research focuses on analysis of the flight trajectory characteristics of SLBM (Submarine Launched Ballistic Missile) of North Korea. Recently, North Korea tested launching of SLBM which is threatening international security. Also it is known that North Korea had possessed the technologies about SLBM since they disassembled submarines out of commission of the former Soviet Union. If the development of the SLBM of North Korea is completed, it should be affected as asymmetric threat to South Korea. Therefore, for active respondence to these threat, it is essential to analyze the SLBM systematically. In this point of view, this work made a SLBM flight model and simulated. In addition, we controled flight trajectories according to adjusting loft angle and described their characteristics. The sea-based ballistic missile defense system is required for an effective response to the flight trajectory of the SLBM from mid-course to terminal phase.

• Smart Structures and Systems
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• v.19 no.1
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• pp.105-113
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• 2017

A microstructure-dependent dynamic model for silicon nanobeams with axial motion is developed by considering the effects of nonlocal elasticity and surface energy. The nanobeam is considered to subject to both transverse and longitudinal loads arising from nanostructural surface effect and all positive directions of physical quantities are defined clearly prior to modeling so as to clarify the confusions of sign in governing equations of previous work. The nonlocal and surface effects are taken into consideration in the dynamic behaviors of silicon nanobeams with axial motion including circular natural frequency, vibration mode, transverse displacement and critical speed. Various supporting conditions are presented to investigate the circular frequencies by a numerical method and the effects of many variables such as nonlocal nanoscale, axial velocity and external loads on non-dimensional circular frequencies are addressed. It is found that both nonlocal and surface effects play remarkable roles on the dynamics of nanobeams with axial motion and cause the frequencies and critical speed to decrease compared with the classical continuum results. The comparisons of the non-dimensional calculation values by present and previous studies validate the correctness of the present work. Additionally, numerical examples for silicon nanobeams with axial motion are addressed to show the nonlocal and surface effects on circular frequencies intuitively. Results obtained in this paper are helpful for the design and optimization of nanobeam-like microstructures based sensors and oscillators at nanoscale with desired dynamic mechanical properties.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.5
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• pp.47-52
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• 2021

Recently, demand for artificial intelligence solutions for production process management has been increasing in the manufacturing industry. However, through the application of AI solutions in the manufacturing industry, there are limitations to legacy smart factory solutions such as POP and MES.Therefore, in order to overcome this, this paper aims to improve production management efficiency by applying guidance, an artificial intelligence concept, to image recognition systems. In the system flow, As_is To be separated and actual work flow was applied, and the process was improved for overall productivity efficiency. The pre-processing plan for AI guidance learning was established and the relevant AI model was designed, developed, and simulated, resulting in a 97% recognition rate.

• Nuclear Engineering and Technology
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• v.51 no.3
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• pp.807-817
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• 2019

Airborne Gamma Ray Spectrometry (AGRS) with its important applications such as gathering radiation information of ground surface, geochemistry measuring of the abundance of Potassium, Thorium and Uranium in outer earth layer, environmental and nuclear site surveillance has a key role in the field of nuclear science and human life. The Broyden-Fletcher-Goldfarb-Shanno (BFGS), with its advanced numerical unconstrained nonlinear optimization in collaboration with Artificial Neural Networks (ANNs) provides a noteworthy opportunity for modern AGRS. In this study a new AGRS system empowered by ANN-BFGS has been proposed and evaluated on available empirical AGRS data. To that effect different architectures of adaptive ANN-BFGS were implemented for a sort of published experimental AGRS outputs. The selected approach among of various training methods, with its low iteration cost and nondiagonal scaling allocation is a new powerful algorithm for AGRS data due to its inherent stochastic properties. Experiments were performed by different architectures and trainings, the selected scheme achieved the smallest number of epochs, the minimum Mean Square Error (MSE) and the maximum performance in compare with different types of optimization strategies and algorithms. The proposed method is capable to be implemented on a cost effective and minimum electronic equipment to present its real-time process, which will let it to be used on board a light Unmanned Aerial Vehicle (UAV). The advanced adaptation properties and models of neural network, the training of stochastic process and its implementation on DSP outstands an affordable, reliable and low cost AGRS design. The main outcome of the study shows this method increases the quality of curvature information of AGRS data while cost of the algorithm is reduced in each iteration so the proposed ANN-BFGS is a trustworthy appropriate model for Gamma-ray data reconstruction and analysis based on advanced novel artificial intelligence systems.