• Fire Science and Engineering
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• v.30 no.6
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• pp.37-42
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• 2016

The present study has been performed to examine the feasibility of a flame spread model on the design fire scenario for fire risk analysis. Thermo-Gravimetric analysis and sample burning test were conducted to obtain the material properties of a single couch covered with synthetic leather material and a series of FDS calculations applying with the measured material properties were performed for different grid sizes. The overall fire growth characteristics predicted by the fire model were quite different from the results of a real scale fire test and the initial peak value of the HRR and total released energy showed the results within a 30% discrepancy for the computational grids used in the present study. The current model has some limitations in predicting the fire growth characteristics, such as fire growth rate and the time to the maximum HRR. This study shows that the fire model may be applicable to creating the design fire scenario through continuous model improvement and detailed material properties.

• Journal of the Korea Institute of Military Science and Technology
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• v.25 no.6
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• pp.617-627
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• 2022

Military training is an essential item for the fundamental problem of war. However, there has always been a problem that many resources are consumed, causing spatial and environmental pollution. The concepts of defense modeling and simulation and CGF(Computer Generated Force) using computer technology began to appear to improve this problem. The Naval Operations, Resources Analysis Model(NORAM) developed by the Republic of Korea Navy is also a DEVS(Discrete Event Simulation)-based naval virtual force analysis model. The current NORAM is a battle experiment conducted by an operator, and parameter values such as maneuver and armament operation for individual objects for each situation are evaluated. In spite of our research conducted evolutionary, supervised, reinforcement learning, in this paper, we introduce our design of a scenario creation model based on evolutionary learning using genetic algorithms. For verification, the NORAM is loaded with our model to analyze wartime engagements. Human-level tactical scenario creation capability is secured by automatically generating enemy tactical scenarios for human-designed Blue Army tactical scenarios.

• Industrial Engineering and Management Systems
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• v.10 no.2
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• pp.140-153
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• 2011

Functional form and dysfunctional form of Kano model are considered as customer need regarding attribute of product. Both functional and dysfunctional forms are: Like, Must-be Neutral, Live-with and Dislike. The answers of customer regarding a product of functional and dysfunctional forms have been applied for selection of customer needs regarding product attribute (Kano evaluation). Filling.up and returning the Questionnaires by the individuals are essential for determining Kano evaluation. But many Questionnaires have not been returned in that case. Moreover, many possible consumers could not get opportunity to fill-up questionnaire. These uncertain or unknown consumers' opinions are also essential for product development. The choices of Kano evaluations have been outlined by: Attractive, One-dimensional, Must-be, Indifferent and Reverse. In this study, choices of evaluation of unknown customer are considered uniform cumulative vector probability (scenario 1). This study is based on the Monte Carlo simulation method, concept of probability and Kano model. This model has also been tested for its soundness and found fairly consistent including existing Kano model (scenario 2) and case survey for headlight of bicycle (scenario 3).

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.4
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• pp.217-228
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• 2020

The ROK Army must detect the enemy's location and the type of artillery weapon to respond effectively at wartime. This paper proposes a radar positioning model by applying a scenario-based robust optimization method i.e., binary integer programming. The model consists of the different types of radar, its available quantity and specification. Input data is a combination of target, weapon types and enemy position in enemy's attack scenarios. In this scenario, as the components increase by one unit, the total number increases exponentially, making it difficult to use all scenarios. Therefore, we use partial scenarios to see if they produce results similar to those of the total scenario, and then apply them to case studies. The goal of this model is to deploy an artillery locating radar that maximizes the detection probability at a given candidate site, based on the probability of all possible attack scenarios at an expected enemy artillery position. The results of various experiments including real case study show the appropriateness and practicality of our proposed model. In addition, the validity of the model is reviewed by comparing the case study results with the detection rate of the currently available radar deployment positions of Corps. We are looking forward to enhance Korea Artillery force combat capability through our research.

• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.107-117
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• 2023

It must be possible to assess how combat actions taking place in cyberspace affect the military's major mission systems and weapon systems. In order to analyze the mission impact caused by a cyber attack through cyber M&S, the target mission system and cyber warfare elements must be built as a model and a scenario for simulation must be authored. Many studies related to mission impact analysis due to cyber warfare have been conducted focusing on the United States, and existing studies have authored separate scenarios for physical battlefields and cyber battlefields. It is necessary to build a simulation environment that combines a physical battlefield model and a cyber battlefield model, and be able to integrate and author mission scenarios and cyber attack/defense scenarios. In addition, the physical battlefield and cyber battlefield are different work areas, so authoring two types of scenarios for simulation is very complicated and time-consuming. In this paper, we propose a method of using mission system information to prepare the data needed for scenario authoring in advance and using the pre-worked data to author an integrated scenario. The proposed method is being developed by reflecting it in the design of the scenario authoring tool, and an integrated scenario authoring in the field of counter-fire warfare is being performed to prove the proposed method. In the future, by using a scenario authoring tool that reflects the proposed method, it will be possible to easily author an integrated scenario for mission impact analysis in a short period of time.

• Korean Journal of Agricultural and Forest Meteorology
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• v.18 no.3
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• pp.170-178
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• 2016

It is not clear how to apply the climate scenario to assess the impact of climate change in the agricultural sector. Even if you apply the same scenario, the result can vary depending on the temporal-spatial downscaling, the post-treatment to adjust the bias of a model, and the prediction model selection (used for an impact assessment). The end user, who uses the scenario climate data, should select climate factors, a spatial extend, and a temporal range appropriate for the objectives of an analysis. It is important to draw the impact assessment results with minimum uncertainty by evaluating the suitability of the data including the reproducibility of the past climate and calculating the optimum future climate change scenario. This study introduced data processing methods for reducing the uncertainties in the process of applying the future climate change scenario to users in the agricultural sector and tried to provide basic information for appropriately using the scenario data in accordance with the study objectives.

• Korean Journal of Agricultural Science
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• v.48 no.3
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• pp.433-446
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• 2021

In this study, the future flood inundation changes under a climate change were simulated in the Tonle Sap basin in Cambodia, one of the countries with high vulnerability to climate change. For the flood inundation simulation using the rainfall-runoff-inundation (RRI) model, globally available geological data (digital elevation model [DEM]; hydrological data and maps based on Shuttle elevation derivatives [HydroSHED]; land cover: Global land cover facility-moderate resolution imaging spectroradiometer [GLCF-MODIS]), rainfall data (Asian precipitation-highly-resolved observational data integration towards evaluation [APHRODITE]), climate change scenario (HadGEM3-RA), and observational water level (Kratie, Koh Khel, Neak Luong st.) were constructed. The future runoff from the Kratie station, the upper boundary condition of the RRI model, was constructed to be predicted using the long short-term memory (LSTM) model. Based on the results predicted by the LSTM model, a total of 4 cases were selected (representative concentration pathway [RCP] 4.5: 2035, 2075; RCP 8.5: 2051, 2072) with the largest annual average runoff by period and scenario. The results of the analysis of the future flood inundation in the Tonle Sap basin were compared with the results of previous studies. Unlike in the past, when the change in the depth of inundation changed to a range of about 1 to 10 meters during the 1997 - 2005 period, it occurred in a range of about 5 to 9 meters during the future period. The results show that in the future RCP 4.5 and 8.5 scenarios, the variability of discharge is reduced compared to the past and that climate change could change the runoff patterns of the Tonle Sap basin.

• Korean Journal of Agricultural and Forest Meteorology
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• v.17 no.1
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• pp.35-44
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• 2015

Forests contain a huge amount of carbon (C) and climate change could affect forest C dynamics. This study was conducted to predict the C dynamics of Pinus densiflora and Quercus variabilis forests, which are the most dominant needleleaf and broadleaf forests in Korea, using the Korean Forest Soil Carbon (KFSC) model under the two climate change scenarios (2012-2100; Constant Temperature (CT) scenario and Representative Concentration Pathway (RCP) 8.5 scenario). To construct simulation unit, the forest land areas for those two species in the 5th National Forest Inventory (NFI) data were sorted by administrative district and stand age class. The C pools were initialized at 2012, and any disturbance was not considered during the simulation period. Although the forest C stocks of two species generally increased over time, the forest C stocks under the RCP 8.5 scenario were less than those stocks under the CT scenario. The C stocks of P. densiflora forests increased from 260.4 Tg C in 2012 to 395.3 (CT scenario) or 384.1 Tg C (RCP 8.5 scenario) in 2100. For Q. variabilis forests, the C stocks increased from 124.4 Tg C in 2012 to 219.5 (CT scenario) or 204.7 (RCP 8.5 scenario) Tg C in 2100. Compared to 5th NFI data, the initial value of C stocks in dead organic matter C pools seemed valid. Accordingly, the annual C sequestration rates of the two species over the simulation period under the RCP 8.5 scenario (65.8 and $164.2g\;C\;m^{-2}\;yr^{-1}$ for P. densiflora and Q. variabilis) were lower than those values under the CT scenario (71.1 and $193.5g\;C\;m^{-2}\;yr^{-1}$ for P. densiflora and Q. variabilis). We concluded that the C sequestration potential of P. densiflora and Q. variabilis forests could be decreased by climate change. Although there were uncertainties from parameters and model structure, this study could contribute to elucidating the C dynamics of South Korean forests in future.

• Educational Technology International
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• v.11 no.1
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• pp.171-192
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• 2010

This study was to investigate the elaborated project based learning model for scientifically gifted in the context of R & E project learning. It is important for the scientifically gifted to provide the appropriate learning environments instead of general learning model for the gifted. Although R & E project learning model is effective, the model has the limitations of managing the course for the scientifically gifted. To improve R & E learning model, the elaborated project based learning model was suggested with integration of both project based learning model and goal based scenario. The elaborated project-based learning model was comprised with 'basic learning process', 'elaboration through inquiry', and 'presentation and reflection'. To measure the satisfaction, eighty scientifically gifted students participated in the class. The result shows that learners were satisfied with the elaborated project-based learning up to 90%, and teachers were satisfied with this model up to 77%.

• The Journal of Korean Academic Society of Nursing Education
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• v.20 no.2
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• pp.212-222
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• 2014

Purpose: The purpose of this study was to evaluate the nursing students' clinical judgment skills in simulation using Tanner's Clinical Judgment Model. Method: Forty-five teams of a total 93 nursing students participated in a post-operative patient care scenario using human patient simulator. Data were collected from students' responses in scenario and guided reflective journaling according to the framework of Tanner's model which comprised noticing, interpreting, responding, and reflecting on response. Data were analyzed using descriptive statistics. Results: The students' responses of the situation were in accordance with the goals of scenario, i.e. relieving patient' pain and preventing pulmonary complications. However, most of students needed clinical cues and focused on a given clue to solve the issues. They were lack of ability to collect additional information as well as connect the relevant clues in simulated clinical situation. Conclusion: The nursing students have difficulty in what they notice, how they interpret finding, and respond appropriately to the situation. The simulation training using Tanner's model could provide faculty and nursing students with an effective teaching and learning strategy to develop the clinical judgment skills.