• Korean Journal of Veterinary Research
• /
• v.45 no.2
• /
• pp.223-231
• /
• 2005

A quantitative risk assessment tool was used to provide estimates of the probability that foot-and-mouth (FMD) virus-contaminated, smuggled animal products are fed to susceptible swine in Korea. Sensitivity analyses were conducted to attempt to distinguish between parameter uncertainty and variability, using different assumptions on the effect of cooking at home, the effect of the fresh meat, and the effect of heat treatment at garbage processing facility. The median risk estimate was about 20.1% with a mean value of 27.4%. In a scenario regarding all beef and pork were considered as fresh meat the estimated median risk was 3.4%. The risk was greatly dependent on the survival parameters of the FMD virus during the cooking or heat treatment at garbage processing facility. Uncertainty about the proportion of garbage that is likely contaminated with FMD had a major positive influence on the risk, whereas conversion rate representing the size of a load had a major negative effect. This model was very useful in assessing the risk explored. However, the model also requires enhancements, such as the availability of more accurate data to verify the various assumptions considered such as FMD prevalence in a specific country, proportion of garbage which is recycled as feed, proportion of food discarded as garbage. Other factors including the effect of selection of animals for slaughter, ante- and post-mortem inspection, the domestic distribution of the smuggled products, and susceptible animals other than pigs, are need to be taken into account in the future model development.

• The KIPS Transactions:PartD
• /
• v.11D no.3
• /
• pp.649-658
• /
• 2004

An object-oriented system is organized by a set of interacting objects and the system behavior is represented by the cooperating interaction bet ween objects. The characteristics of object-oriented software. such as inheritance and polymorphism, increase the difficulty of the object-oriented software testing. At running time of a program, one call from a member function can bind to other member functions because of the dynamic characteristics such as concurrence, dynamic binding and interaction. Therefore, there need the research about considering the characteristics of object-oriented software and concurrently testing the interaction between objects. In this paper, we propose the techniques as follows. First, we construct a flattened state chart diagram by considering the inheritance and polymorphism. Next, we model the system with CPN(Colored Petri Net) that usually is applying the system modeling and simulation. Last, we propose a test case generation techniques for testing the interaction between objects in object-oriented software by applying a Design/CPN tool.

• Steel and Composite Structures
• /
• v.10 no.3
• /
• pp.207-222
• /
• 2010

Fire incident in buildings is common, so the fire safety design of the framed structure is imperative, especially for the unprotected or partly protected bare steel frames. However, software for structural fire analysis is not widely available. As a result, the performance-based structural fire design is urged on the basis of using user-friendly and conventional nonlinear computer analysis programs so that engineers do not need to acquire new structural analysis software for structural fire analysis and design. The tool is desired to have the capacity of simulating the different fire scenarios and associated detrimental effects efficiently, which includes second-order P-D and P-d effects and material yielding. Also the nonlinear behaviour of large-scale structure becomes complicated when under fire, and thus its simulation relies on an efficient and effective numerical analysis to cope with intricate nonlinear effects due to fire. To this end, the present fire study utilizes a second-order elastic/plastic analysis software NIDA to predict structural behaviour of bare steel framed structures at elevated temperatures. This fire study considers thermal expansion and material degradation due to heating. Degradation of material strength with increasing temperature is included by a set of temperature-stress-strain curves according to BS5950 Part 8 mainly, which implicitly allows for creep deformation. This finite element stiffness formulation of beam-column elements is derived from the fifth-order PEP element which facilitates the computer modeling by one member per element. The Newton-Raphson method is used in the nonlinear solution procedure in order to trace the nonlinear equilibrium path at specified elevated temperatures. Several numerical and experimental verifications of framed structures are presented and compared against solutions in literature. The proposed method permits engineers to adopt the performance-based structural fire analysis and design using typical second-order nonlinear structural analysis software.

• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.15 no.2
• /
• pp.51-56
• /
• 2016

High brittleness is a characteristic of glass, and in many cases it is broken during the process of machining due to processing problems, such as scratches, chipping, and notches. Machining defects occur due to the vibration of the equipment. Therefore, design techniques are needed that can control the vibration generated in the equipment to increase the strength of tempered glass. The natural frequency of the machine tool via vibration analysis (computer simulation) must be accurately understood to improve the design to ensure the stability of the machine. To accurately understand the natural frequency, 3D modeling, which is the same as actual apparatus, was used and a constraint condition was also applied that was the same as that of the actual apparatus. The maximum speeds of ultrasonic and high frequency, which are 15,000 rpm and 60,000 rpm, respectively, are considerably faster than those of typical machine tools. Therefore, an improved design is needed so that the natural frequency is formed at a lower region and the natural frequency does not increase through general design reinforcement. By restructuring the top frame of the glass processing, the natural frequency was not formed in the operating speed area with the improved design. The lower-order natural frequency is dominant for the effects that the natural frequency has on the vibration. Therefore, the design improvement in which the lower-order natural frequency is not formed in the operating speed area is an optimum design improvement. It is possible to effectively control the vibrations by avoiding resonance with simple design improvements.

• Journal of the Korean Magnetics Society
• /
• v.21 no.2
• /
• pp.61-66
• /
• 2011

The miniaturization of electrostatic precipitator is becoming a key element to the success of the efficient electrostatic precipitator due to the limited space allowed to install electrostatic precipitator in subway tunnel. Nowadays, a research on electrostatic precipitator in urban railroad equipment technology is under an active study. Finite element method has been used one of the most popular techniques, but it consumes a lot of time especially in computation iterations. Accordingly, the lumped parameter analysis can be an alternative tool to FEM because of its computation iteration capability with fair accuracy. In this paper, lumped parameter model and the simulation results are presented. In addition, the result of lumped parameter analysis is compared with those obtained from finite element analysis for verification.

• The Journal of Information Systems
• /
• v.17 no.3
• /
• pp.205-233
• /
• 2008

This study suggests the dynamic value chain model, that will be able to not only show changing processes to organization's significant capital by integrating an individual, implicit, and explicit knowledge which affect organizational decision making, but also distinguish the key driver for raising organizational competitive power because it makes possible to analyze sensitivity of performance along with decision making alternatives and policy changes from dynamic view by connecting knowledge management capability, knowledge management activity, and relations with organizational performance with specific strategic map. Recently, a lot of organizations show interest in measuring and evaluating their performance synthetically. In organizations taking knowledge management, they introduce effective value chain model like a dynamic balanced scorecard (DBSC), and therefore they can reflect their knowledge management condition as well as show their changes by checking performance of established vision and strategy periodically. Furthermore, they can ask for their inner members' understanding and participation by communicating with and inspiring their members with awareness that members are one of their group, present a base of benchmarking, and offer significant information for later decision making. The BSC has been a successful framework for measuring an organization's performance in various perspectives through translating an organization's vision and strategy into an interrelated set of key performance indicators and specific actions. The BSC, while having significant strengths over traditional performance measurement methods, however, has its own limitations, due to its static nature, such as overlooking two-way causation between performance indicators and neglecting the impact of delayed feedback flowing from the adoption of new strategies or policy changes. To overcome these limitations, this study employs SD, a methodology for understanding complex systems where dynamic feedback among the interrelated system components significantly impact on the system outcomes. The SD simulation model in the form of DBSC would serve as a useful strategic teaming tool for facilitating an organization's communication process through various scenario analyses as well as predicting the dynamic behavior pattern of their key performance measures over a future time frame. For the demonstration purpose, this study applied the DBSC model to Prototype of Korea manufacturing and service firm.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.22 no.12
• /
• pp.2744-2754
• /
• 1997

Recently, the Multi-Layer Restoration(MLR) algorithm was proposed by British Telecom(BT) to restore the network failures in Digital Cross-connect System(DCS) mesh survival network[1, 2]. This algorithm has multi restoration stage which is composed of the pre-planned and dynamic restoration. This algorithm is effective its ability in link or node failures. This reason is that it does not restore in the pre-planned rstoration stage but in dynamic restoration stage. In this paper, we propose the MLR with pre-planned Multi-Chooser(PMC) and successive restoration ratio algorithm. This proposed algorithm has a excellent performance for restortion time and ratio, spare channel availability and fast restoration from multiple link failure or node failure. This paper proposed the modeling and restoration algorithm, and analyzed the performance of the algorithm by simulation using OPNET(OPtimized Network Engineering Tools).

• Journal of the Korean Society of Systems Engineering
• /
• v.16 no.2
• /
• pp.97-109
• /
• 2020

On March 11, 2011, an earthquake followed by a tsunami caused an extended station blackout (SBO) at the Fukushima Dai-ichi NPP Units. The accident was initiated by a total loss of both onsite and offsite electrical power resulting in the loss of the ultimate heat sink for several days, and a consequent core melt in some units where proper mitigation strategies could not be implemented in a timely fashion. To enhance the plant's coping capability, the Diverse and Flexible Strategies (FLEX) were proposed to append the Emergency Operation Procedures (EOPs) by relying on portable equipment as an additional line of defense. To assess the success window of FLEX strategies, all sources of uncertainties need to be considered, using a physics-based model or system code. This necessitates conducting a large number of simulations to reflect all potential variations in initial, boundary, and design conditions as well as thermophysical properties, empirical models, and scenario uncertainties. Alternatively, data-driven models may provide a fast tool to predict the success window of FLEX strategies given the underlying uncertainties. This paper explores the applicability of Artificial Intelligence (AI) to identify the success window of FLEX strategy for extended SBO. The developed model can be trained and validated using data produced by the lumped parameter thermal-hydraulic code, MARS-KS, as best estimate system code loosely coupled with Dakota for uncertainty quantification. A Systems Engineering (SE) approach is used to plan and manage the process of using AI to predict the success window of FLEX strategies under extended SBO conditions.

• Journal of the Korean Society of Systems Engineering
• /
• v.16 no.2
• /
• pp.27-37
• /
• 2020

The Fukushima Daiichi accident in 2011 revealed some vulnerabilities of existing Nuclear Power Plants (NPPs) under extended Station Blackout (SBO) accident conditions. One of the key Severe Accident Management (SAM) strategies developed post Fukushima accident is the In-Vessel Retention (IVR) Strategy which aims to retain the structural integrity of the Reactor Pressure Vessel (RPV). RELAP/SCDAPSIM/MOD3.4 is selected to predict the thermal-hydraulic response of APR1400 undergoing an extended SBO. To assess the effectiveness of the IVR strategy, it is essential to quantify the underlying uncertainties. In this work, both the epistemic and aleatory uncertainties are considered to identify the success window of the IVR strategy. A set of in-vessel relevant phenomena were identified based on Phenomena Identification and Ranking Tables (PIRT) developed for severe accidents and propagated through the thermal-hydraulic model using Wilk's sampling method. For this work, a Systems Engineering (SE) approach is applied to facilitate the development process of assessing the reliability and robustness of the APR1400 IVR strategy. Specifically, the Kossiakoff SE method is used to identify the requirements, functions and physical architecture, and to develop a design verification and validation plan. Using the SE approach provides a systematic tool to successfully achieve the research goal by linking each requirement to a verification or validation test with predefined success criteria at each stage of the model development. The developed model identified the conditions necessary for successful implementation of the IVR strategy which maintains the vessel integrity and prevents a melt-through.

• Geomechanics and Engineering
• /
• v.33 no.2
• /
• pp.133-140
• /
• 2023

Soil erosion can cause scouring and failures of underwater structures, therefore, various soil improvement techniques are used to increase the soil erosion resistance. The microbially induced calcium carbonate precipitation (MICP) method is proposed to increase the erosion resistance, however, there are only limited experimental and numerical studies on the use of MICP treatment for improvement of surface erosion resistance. Therefore, this study investigates the improvement in surface erosion resistance of sands by MICP through laboratory experiments and numerical modeling. The surface erosion behaviors of coarse sands with various calcium carbonate contents were first investigated via the erosion function apparatus (EFA). The test results showed that MICP treatment increased the overall erosion resistance, and the contribution of the precipitated calcium carbonate to the erosion resistance and critical shear stress was quantified in relation to the calcium carbonate contents. Further, these surface erosion processes occurring in the EFA test were simulated through the coupled computational fluid dynamics (CFD) and discrete element method (DEM) with the cohesion bonding model to reflect the mineral precipitation effect. The simulation results were compared with the experimental results, and the developed CFD-DEM model with the cohesion bonding model well predicted the critical shear stress of MICP-treated sand. This work demonstrates that the MICP treatment is effective in improving soil erosion resistance, and the coupled CFD-DEM with a bonding model is a useful and promising tool to analyze the soil erosion behavior for MICP-treated sand at a particle scale.