• Proceedings of the Korean Institute of Building Construction Conference
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• 2013.11a
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• pp.139-140
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• 2013

Ground source heat pump systems can achieve the energy saving of building and reduce CO₂ emission by utilizing stable ground temperature. However, they have many barriers such as high cost of installation, incompletion of design tool, lack of recognition as heating and cooling systems. In order to solve the problems, the building integrated geothermal system (BIGS) developed by several researches which use building foundation as a heat exchanger. In order to establish the optimum design tool of BIGS with the horizontal heat exchanger, the prediction method of ground heat exchange rate developed with numerical simulation model. In this study, the economic analysis for BIGS was conducted based on simulation results and the optimal design method was suggested. As a result, it was found that the case of 32 A, piping space 0.3 m, piping deep 0.5 m and flow rate 9.52 L/min was the best case as 50.1 W/m2 of heat exchange rate. In this case the initial cost was reduced to 115 million won.

• Geomechanics and Engineering
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• v.33 no.3
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• pp.261-269
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• 2023

In this study, the compressive strength of cement stabilized soil was predicted using the electrical resistivity measurement. The effects of the water to cement (w/c) ratio and recovered Carbon Black (rCB) contents were examined. A series of electrical resistivity and compressive strength tests were conducted on two types of stabilized soil after 28 days of curing. Multiple nonlinear regression (MNLR) analysis was used to evaluate the relationship between the compressive strength and the electrical resistivity in terms of the rCB, C_u (uniformity coefficient), and w/c ratio. The results showed that the w/c ratio and C_u have a strong influence on the compressive strength and electrical resistivity of the cement stabilized soil compared to the rCB content. The use of a small amount of rCB led to a decrease in the void space in the specimen and was attributed to the increase strength and decrease electrical resistivity. A high w/c ratio also induced a low electrical resistivity and compressive strength, whereas 3% rCB in the cemented soil provided the optimum strength for all w/c ratios. Finally, a prediction equation for the compressive strength using the electrical resistivity measurement was suggested based on its reliability, time effectiveness, non-destructiveness, and cost-effectiveness.

• Nuclear Engineering and Technology
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• v.56 no.8
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• pp.2999-3029
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• 2024

To improve the predictive capability of a nuclear thermal hydraulic safety analysis code by developing a better constitutive equation for individual phenomenon has been the general research direction until now. This paper proposes a new method to directly use complex experimental data obtained from integral effect test (IET) to improve constitutive models holistically and simultaneously. The method relies on the sensitivity of a simulation result of IET data to the multiple constitutive equations utilized during the simulation, and the sensitivity of individual model determines the direction of modification for the constitutive model. To develop a robust and generalized method, a clustering algorithm using an artificial neural network, sample space size determination using non-parametric statistics, and sampling method of Latin hypercube sampling are used in a combined manner. The value of the proposed methodology is demonstrated by applying the method to the ATLAS DSP-05 IET experiment. A sensitivity of each observation parameter to the constitutive models is analyzed. The new methodology suggested in the study can be used to improve the code prediction results of complex IET data by identifying the direction for constitutive equations to be modified.

• Journal of Korean Society for Quality Management
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• v.39 no.3
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• pp.400-411
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• 2011

Process variables are factors in an experiment that are not mixture components but could affect the blending properties of the mixture ingredients. For example, the effectiveness of an etching solution which is measured as an etch rate is not only a function of the proportions of the three acids that are combined to form the mixture, but also depends on the temperature of the solution and the agitation rate. Efficient designs for the mixture components-process variables experiments depend on the mixture components-process variables model which is called a combined model. We often use the product model between the canonical polynomial model for the mixture and process variables model as a combined model. In this paper we propose three starting models for the mixture components-process variables experiments. One of the starting model we are considering is the model which includes product terms up to cubic order interactions between mixture effects and the linear & pure quadratic effect of the process variables from the product model. In this paper, we propose a method for finding robust designs and practical designs with respect to D-, G-, and I-optimality for the various starting combined models and then, we find practically efficient and robust designs for estimating the regression coefficients for those models. We find the prediction capability of those recommended designs in the case of three components and three process variables to be good by checking FDS(Fraction of Design Space) plots.

• KIISE Transactions on Computing Practices
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• v.24 no.3
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• pp.138-144
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• 2018

A video is a vivid medium similar to human's visual-linguistic experiences, since it can inculcate a sequence of situations, actions or dialogues that can be told as a story. In this study, we propose story learning/regeneration frameworks from videos with successive event order supervision for contextual coherence. The supervision induces each episode to have a form of trajectory in the latent space, which constructs a composite representation of ordering and semantics. In this study, we incorporated the use of kids videos as a training data. Some of the advantages associated with the kids videos include omnibus style, simple/explicit storyline in short, chronological narrative order, and relatively limited number of characters and spatial environments. We build the encoder-decoder structure with successive event order embedding, and train bi-directional LSTMs as sequence models considering multi-step sequence prediction. Using a series of approximately 200 episodes of kids videos named 'Pororo the Little Penguin', we give empirical results for story regeneration tasks and SEOE. In addition, each episode shows a trajectory-like shape on the latent space of the model, which gives the geometric information for the sequence models.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.39 no.9
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• pp.839-847
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• 2011

This paper proposes a new guidance law for increasing the lethality of munitions. The well known PNG (Proportional Navigation Guidance) is inadequate for the munitions because of some weaknesses. Even if the munition does not have the impact point error, the acceleration command is non zero because the line-of-sight changes at all times in flight. Therefore, we use a difference between a target and an impact point. This proposed guidance law is similar to PNG in the form, but this guidance law concentrates a correction rate of flight path angle instead of the LOS (Line of Sight) rate. The correction of flight path angle is defined as the amount of impact point error. This impact point error can be calculated by neural networks rapidly. Finally, we show that the simulation results prove the suitability of this law.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.3
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• pp.232-239
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• 2009

The prediction of the separation trajectories of external stores carried by military aircraft is an important task in the area of aircraft design having the objective to define the operational, release envelopes. This paper presents the results obtained for safe store separation from a fighter aircraft by experimental methods in the subsonic wind tunnel. The problems associated with separation of external stores can be studied by the use of several wind-tunnel test techniques. Attention is given the two most useful techniques: 1) dynamically scaled drop-model testing, 2) grid testing. A description of each method is given and data obtained are shown to validate the similarity within acceptable limits.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.2 no.3
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• pp.53-60
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• 2009

The vision-based driver fatigue detection is one of the most prospective commercial applications of facial expression recognition technology. The facial feature tracking is the primary technique issue in it. Current facial tracking technology faces three challenges: (1) detection failure of some or all of features due to a variety of lighting conditions and head motions; (2) multiple and non-rigid object tracking; and (3) features occlusion when the head is in oblique angles. In this paper, we propose a new active approach. First, the active IR sensor is used to robustly detect pupils under variable lighting conditions. The detected pupils are then used to predict the head motion. Furthermore, face movement is assumed to be locally smooth so that a facial feature can be tracked with a Kalman filter. The simultaneous use of the pupil constraint and the Kalman filtering greatly increases the prediction accuracy for each feature position. Feature detection is accomplished in the Gabor space with respect to the vicinity of predicted location. Local graphs consisting of identified features are extracted and used to capture the spatial relationship among detected features. Finally, a graph-based reliability propagation is proposed to tackle the occlusion problem and verify the tracking results. The experimental results show validity of our active approach to real-life facial tracking under variable lighting conditions, head orientations, and facial expressions.

• The Korean Journal of Applied Statistics
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• v.29 no.4
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• pp.581-594
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• 2016

We introduce innovations state space exponential smoothing models (ISS-ESM) that can analyze time series with multiple seasonal patterns. Especially, in order to control complex structure existing in the multiple patterns, the model equations use a matrix consisting of seasonal updating parameters. It enables us to group the seasonal parameters according to their similarity. Because of the grouped parameters, we can accomplish the principle of parsimony. Further, the ISS-ESM can potentially accommodate any number of multiple seasonal patterns. The models are applied to predict electricity demand in Korea that is observed on hourly basis, and we compare their performance with that of the traditional exponential smoothing methods. It is observed that the ISS-ESM are superior to the traditional methods in terms of the prediction and the interpretability of seasonal patterns.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.11
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• pp.763-770
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• 2022

In an environment where multiple drones are operated, collisions can occur when path points overlap, and collision avoidance in preparation for this is essential. When multiple drones perform multiple tasks, it is not appropriate to use a method to generate a collision-avoiding path in the path planning phase because the path of the drone is complex and there are too many collision prediction points. In this paper, we generate a path through a commonly used path generation algorithm and propose a collision avoidance method using speed profile optimization from that path segment. The safe distance between drones was considered at the expected point of collision between paths of drones, and it was designed to assign a speed profile to the path segment. The optimization problem was defined by setting the distance between drones as variables in the flight time equation. We constructed the constraints through linearize and convexification, and compared the computation time of SQP and convex optimization method in multiple drone operating environments. Finally, we confirmed whether the results of performing convex optimization in the 20 drone operating environments were suitable for the multiple drone operating system proposed in this study.