• Journal of Korean Society of Coastal and Ocean Engineers
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• v.19 no.1
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• pp.81-96
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• 2007

Nonlinear shoaling characteristics over surf zone are numerically investigated based on spatially averaged NavierStokes equation. We also test the validity of gradient model for turbulent stresses due to wave breaking using the data acquainted during SUPERTANK LABORATORY DATA COLLECTION PROJECT(Krauss et al., 1992). It turns out that the characteristics length scale of breaking induced current is not negligible, which firmly stands against ever popular gradient model, ${\kappa}-{\varepsilon}$ model, but favors Large Eddy Simulation with finer grid. Based on these observations, we model the residual stress of spatially averaged NavierStokes equation after Lagrangian Dynamic Smagorinsky(Meneveau et al., 1996). We numerically integrate newly proposed wave equations using SPH with Gaussian kernel function. Severely deformed water surface profile, free falling water particle, queuing splash after landing of water particle on the free surface and wave finger due to structured vortex on rear side of wave crest(Narayanaswamy and Dalrymple, 2002) are successfully duplicated in the numerical simulation of wave propagation over uniform slope beach, which so far have been regarded very difficult features to mimic in the computational fluid mechanics.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.11b
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• pp.369-374
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• 2002

This paper presents theoretical analysis of the NRRO(non-repeatable run-out) for a ball bearing with geometric imperfection. The 3DOF dynamic analysis of a ball bearing using the Newton-Raphson method is performed to calculate the displacement of shaft center. Frequency and magnitude characteristics of radial and axial vibrations are investigated. The ball form errors of the ball, the inner race, and the outer race in a HDD spindle ball bearing are precisely measured. NRRO of a ball bearing is analyzed by using the measured waviness data. It is concluded that dominant components of radial vibrations are ${\Large}f_c\;and\;2{\Larg}f_b{\pm}{\Large}f_c$, and dominant component of axial vibrations is $2{\Large}f_b$. These are generated by the size error and the second waviness of the balls.

• Journal of Advanced Marine Engineering and Technology
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• v.28 no.3
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• pp.423-433
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• 2004

A large eddy simulation (LES) is performed for turbulent flow in a combustion device. The combustion device is simplified as a cylindrical chamber with sudden expansion. A flame holder is attached inside a cylindrical chamber in order to promote turbulent mixing and to accommodate flame stability. The turbulent sub-grid scale models are applied and validated. Emphasis is placed on the evaluation of turbulent model for the LES of complex geometry. The simulation code is constructed by using a general coordinate system based on the physical contravariant velocity components. The calculated Reynolds number is 5000 based on the bulk velocity and the diameter of inlet pipe. The predicted turbulent statistics are evaluated by comparing with the LDV measurement data. The Smagorinsky model coefficients are estimated and the utility of dynamic SGS models are confirmed in the LES of complex geometry.

• 제어로봇시스템학회:학술대회논문집
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• 1998.10a
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• pp.250-253
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• 1998

This paper presents a multi-modal neural network composed of a preprocessing module and a multi-layer neural network module in order to enhance the nonlinear characteristics of neural network. The former module is based on spectral method using Chebyschev polynomials and transforms input data into spectra. The latter module identifies the system using the spectra generated by the preprocessing module. The omnibus numerical experiments show that the method is applicable to many a nonlinear dynamic system in the real world, and that preprocessing using Chebyschev polynomials reduces the number of neurons required for the multi-layer neural network.

• Journal of Korea Multimedia Society
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• v.8 no.7
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• pp.924-942
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• 2005

Recently, large-scale directories have been developed for LINUX cluster file systems to store and retrieve huge amount of data. One of them, GFS directory, has attracted much attention because it is based on extendible hashing, one of dynamic hashing techniques, to support fast access to files. One distinctive feature of the GFS directory is the flat structure where all the leaf nodes are located at the same level of the tree. Hut one disadvantage of the mode structure is that the height of the mode tree has to be increased to make the tree flat after a byte is inserted to a full tree which cannot accommodate it. Thus, one byte addition makes the height of the whole mode tree grow, and each data block of the new tree needs one more link access than the old one. Another dynamic hashing technique which can be used for directories is linear hashing and a couple of researches have shown that it can get better performance at file access times than extendible hashing. [n this research, we have designed and implemented an extendible hashing directory and a linear hashing directory for large-scale LINUX cluster file systems and have compared performance between them. We have used the semi-flat structure which is known to have better access performance than the flat structure. According to the results of the performance evaluation, the linear hashing directory has shown slightly better performance at file inserts and accesses in most cases, whereas the extendible hashing directory is somewhat better at space utilization.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.2
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• pp.122-129
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• 2014

Effective information gathering and retrieval of the most relevant web documents on the topic of interest is difficult due to the large amount of information that exists in various formats. Current information gathering and retrieval techniques are unable to exploit semantic knowledge within documents in the "big data" environment; therefore, they cannot provide precise answers to specific questions. Existing commercial big data analytic platforms are restricted to a single data type; moreover, different big data analytic platforms are effective at processing different data types. Therefore, the development of a common big data platform that is suitable for efficiently processing various data types is needed. Furthermore, users often possess more than one intelligent device. It is therefore important to find an efficient preference profile construction approach to record the user context and personalized applications. In this way, user needs can be tailored according to the user's dynamic interests by tracking all devices owned by the user.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.384-387
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• 2003

Most of the real world phenomena change over time. The ability to represent and to reason geographic data becomes crucial. A large amount of non-standard applications are dealing with data characterized by spatial, temporal and/or uncertainty features. Non-standard data like spatial and temporal data have an inner complex structure requiring sophisticated data representation, and their operations necessitate sophisticated and efficient algorithms. Current GIS technology is inefficient to model and to handle complex geographic phenomena, which involve space, time and uncertainty dimensions. This paper concentrates on developing a fuzzy spatio-temporal data model based on fuzzy set theory and relational data models. Fuzzy spatio-temporal operators are also provided to support dynamic query.

• International Journal of Contents
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• v.16 no.4
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• pp.16-25
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• 2020

The size of observation data in astronomy has been increasing exponentially with the advents of wide-field optical telescopes. This means the needs of changes to the way used for large-scale astronomy data analysis. The complexity of analysis tools and the lack of extensibility of computing environments, however, lead to the difficulty and inefficiency of dealing with the huge observation data. To address this problem, this paper proposes a workflow execution system for analyzing large-scale astronomy data efficiently. The proposed system is composed of two parts: 1) a workflow execution manager and its RESTful endpoints that can automate and control data analysis tasks based on workflow templates and 2) an elastic resource manager as an underlying mechanism that can dynamically add/remove virtualized computing resources (i.e., virtual machines) according to the analysis requests. To realize our workflow execution system, we implement it on a testbed using OpenStack IaaS (Infrastructure as a Service) toolkit and HTCondor workload manager. We also exhaustively perform a broad range of experiments with different resource allocation patterns, system loads, etc. to show the effectiveness of the proposed system. The results show that the resource allocation mechanism works properly according to the number of queued and running tasks, resulting in improving resource utilization, and the workflow execution manager can handle more than 1,000 concurrent requests within a second with reasonable average response times. We finally describe a case study of data reduction system as an example application of our workflow execution system.

• Smart Structures and Systems
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• v.13 no.6
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• pp.993-1014
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• 2014

In civil engineering, revolving structures (RS) are a unique structural form applied in innovative architecture design. Such structures are able to revolve around themselves or along a certain track. However, few studies are dedicated to safety design or health monitoring of RS. In this paper, a wireless dynamic sensing system is developed for RS, and field tests toward a large revolving auditorium are conducted accordingly. At first, a wheel-rail problem is proposed: The internal force redistributes in RS, which is due to wheel-rail irregularity. Then the development of the sensing system for RS is presented. It includes system architecture, network organization, vibrating wire sensor (VWS) nodes and online remote control. To keep the sensor network identifiable during revolving, the addresses of sensor nodes are reassigned dynamically when RS position changes. At last, the system is mounted on a huge outdoor revolving auditorium. Considering the influence of the proposed problem, the RS of the auditorium has been designed conservatively. Two field tests are conducted via the sensing system. In the first test, 2000 people are invited to act as the live load. During the revolving process, data is collected from RS in three different load cases. The other test is the online monitoring for the auditorium during the official performances. In the end, the field-testing result verifies the existence of the wheel-rail problem. The result also indicates the dynamic sensing system is applicable and durable even while RS is rotating.

• KIISE Transactions on Computing Practices
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• v.23 no.12
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• pp.660-669
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• 2017

In order to improve user accessibility and interactivity, system scalability, service speed, and a non-standard internet web environment, we developed a Web-based geovisualization system of oceanographic information using HTML5 and dynamic particles. In particular, oceanographic and meteorological data generated from a satellite remote sensing and radar measurement and a 3-dimensioanl numerical model, has the characteristics of a heterogeneous large-capacity multi-dimensional continuous spatial and temporal variability, based on geographic information. Considering those attributes, we applied dynamic particles represent the spatial and temporal variations of vector type oceanographic data. HTML5, WebGL, Canvas, D3, and Leaflet map libraries were also applied to handle various multimedia data, graphics, map services, and location-based service as well as to implement multidimensional spatial and statistical analyses such as a UV chart.