• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.21-29
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• 1994

This paper presents a method to accommodate failures that affect aircraft dynamical characteristics, especially control surface jams on a large transport aircraft. The approach is to use the slow effectors, such as the stabilators or engines, in the feedforward manner. The simulation results indicate the performance of the RFCS. In some cases of control surface jam, the aircraft cannot recover without using the stabilators. Although the inputs to the slow effectors are determined using the nominal parameters, the effects of parameter change can be compensated by adjusting the control parameters for the fast surfaces. In the case of rudder jam, if the remaining control surfaces and the differential thrust cancel the moments produced by the stuck rudder, using the engine control improves time responses and reduces deflection angles of the control surfaces. If not, however, the aircraft starts a large rolling motion following a yawing motion. In that case, the stabilators should be used to damp the induced rolliig motion, instead of trying to directly cancel the moments caused by the stuck rudder. Unfortunately, the proposed control law for the stabilators does not give such inputs, because it does not take into account the dynamical effects which stuck surfaces have on the aircraft motions. However, we have shown through simulation that the aircraft can be recovered by giving the stabilators the control inputs that counteract the induced rolling moment. Besides, the method has also been shown through simulation to be effective in maintaining control during a situation similar to an actual accident. Finally let us mention a problem with the RFCS. As stated above, we have not established a method to select a trim point which call be reached as easily as possible using the remaining control effectors. In fact, recovery performance considerably depends on the trim states. As pointed out in Ref. 11, finding the best trim point for impaired aircraft will be one of the most difficult questions in RFCS design.

• Journal of Welding and Joining
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• v.24 no.5
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• pp.62-66
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• 2006

Panel line is an important process occupying the largest work amount in shipbuilding. In this research product simulation has been carried out to establish the optimal production scheduling. For this purpose a web-based panel line simulator was developed using an object modeling technology and C# language. The balance of work-load and increase in the productivity by the improvement of production facilities and process are the key factors for a good scheduling. In this study SPRT(Shortest Remaining Process Time) rule was applied for the work-load balancing and a good result achieved. To increase the productivity in the stiffener welding stage which is a bottleneck; process, more welding heads and higher welding speed were tested using the developed simulator. The simulation results showed that either more welding head or higher welding speed decreased the total work time. Use of both, however, deteriorated the productivity because of the bottleneck in the following stage. This result points out that the improvement of production facilities and/or process should be evaluated with their influences on the leading and following processing stage.

• Journal of the Korean GEO-environmental Society
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• v.24 no.12
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• pp.47-52
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• 2023

In order to efficiently maintain heat pipes operated by district heating operators, the facility history and damage history data built by the operator are used to identify key independent variables that are related to the occurrence of damage. Afterwards, the correlation with the frequency of damage was analyzed, and a basic model for estimating the frequency of damage was derived. Considering the correlation with the estimation model based on the use time currently being used by domestic and foreign district heating operators, a simple regression analysis basic model was presented as the independent variable with the highest correlation between continuous variables such as the use time, pipe diameter, burial depth, and insulation level of monitoring system, and the frequency of damage. The remaining independent variables were reflected as factors that modify and supplement the basic model. As a result of the analysis, as in previous research cases, it was confirmed that the analysis model between use time and frequency of damage had the highest correlation between the two variables and could be used as a basic model. Pipe diameter, burial depth, and insulation level of monitoring system information have also been confirmed to have a correlation with the frequency of damage, so they can be used as factors to supplement the basic model.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.4
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• pp.470-476
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• 2019

The pattern locking technique applied to smart phones is a locking technique that many people use conveniently. However, the safety of pattern locking techniques is very low compared with other techniques. The pattern locking technique is vulnerable to a shoulder surfing attack, which is based on the user's input and can be interpreted by looking at the movement of the shoulder, and the smudge attack is also vulnerable due to fingerprint drag marks remaining on the mobile phone pad. Therefore, in this paper, we want to add a new security method to check the pressed time by using a thread in the pattern locking scheme to secure the vulnerability. It is divided into short, middle, and long click according to the pressing time at each point. When dragging using the technique, security performance enhances $3^n$ tiems. Therefore, even if dragging in the same 'ㄱ' manner, it becomes a completely different pattern depending on the pressing time at each point.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.97-97
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• 2020

Flooding in urban areas is caused by heavy rains for a short period of time and drains within 1 to 2 hours. It is also characterized by a small flooding area. In addition, flooding is often caused by various and complex causes such as land use, basin slope, pipe, street inlet, drainage pumping station, making it difficult to predict flooding. Therefore, this study analyzes the effect of each basin characteristic on the occurrence of flooding in urban areas by correlating various basin characteristics, whether or not flooding occurred, and rainfall(Limit Rainfall), and intends to use the data for urban flood prediction. As a result of analyzing the relationship between the imperviousness and the urban slope, pipe, threshold rainfall and limit rainfall, the pipe showed a correlation coefficient of 0.32, and the remaining factors showed low correlation. However, the multiple correlation analysis showed the correlation coefficient about 0.81 - 0.96 depending on the combination, indicating that the correlation was relatively high. In the future, I will further analyze various urban characteristics data, such as area by land use, average watershed elevation, river and coastal proximity, and further analyze the relationship between flooding occurrence and urban characteristics. The relationship between the urban characteristics, the occurrence of flooding and the limiting rainfall amount suggested in this study is expected to be used as basic data for the study to predict urban flooding in the future.

• Journal of the Korean Operations Research and Management Science Society
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• v.42 no.2
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• pp.1-17
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• 2017

Based on increased popularity and use of social network services as a marketing tool, social commerce became an emerging trend in e-commerce platforms. Social commerce involves sellers offering potential consumers the products and services at a lower price in a limited time period. Through comparison of the performances of domestic social commerce websites, we found that the buying environment such as price, number of available products, and the remaining time period for sale has a significant difference influencing on the purchase decisions of consumers. This study aims to analyze the interaction effects and preference levels of four characteristics (price, discount rate, number of purchases and purchase time) by conducting choice-based conjoint analysis. Survey experiment was performed using a sample of 146 undergraduate and graduate students. The results showed that consumers importantly consider purchase time, discount rate, price, number of purchases in the order of their preference. Also, discount effect is more significant on purchase decisions than price effect and consumers distinguish less the differences among the buying environment characteristics in the closing days of purchase period. Customer segmentation using the preference levels of characteristics indicates that the preference levels have different effects in the purchase utility of each segment. The proposed customer segmentation and differences in feature utilities are expected to be valuable in forming future sales promotion strategies in social commerce.

• Wind and Structures
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• v.36 no.6
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• pp.367-377
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• 2023

This study proposes a few-shot learning model for extrapolating the wind pressure of scaled experiments to full-scale measurements. The proposed ML model can use scaled experimental data and a few full-scale tests to accurately predict the remaining full-scale data points (for new specimens). This model focuses on extrapolating the prediction to different scales while existing approaches are not capable of accurately extrapolating from scaled data to full-scale data in the wind engineering domain. Also, the scaling issue observed in wind tunnel tests can be partially resolved via the proposed approach. The proposed model obtained a low mean-squared error and a high coefficient of determination for the mean and standard deviation wind pressure coefficients of the full-scale dataset. A parametric study is carried out to investigate the influence of the number of selected shots. This technique is the first of its kind as it is the first time an ML model has been used in the wind engineering field to deal with extrapolation in wind performance prediction. With the advantages of the few-shot learning model, physical wind tunnel experiments can be reduced to a great extent. The few-shot learning model yields a robust, efficient, and accurate alternative to extrapolating the prediction performance of structures from various model scales to full-scale.

• Structural Engineering and Mechanics
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• v.60 no.4
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• pp.655-665
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• 2016

This paper aims to develop models to accurately predict the behavior of fresh concrete exposed to vibration using artificial neural networks (ANNs) model and regression model (RM). For this purpose, behavior of a full scale precast concrete mold was investigated experimentally and numerically. Experiment was performed under vibration with the use of a computer-based data acquisition system. Transducers were used to measure time-dependent lateral displacements at some points on mold while both mold is empty and full of fresh concrete. Modeling of empty and full mold was made using both ANNs and RM. For the modeling of ANNs: Experimental data were divided randomly into two parts. One of them was used for training of the ANNs and the remaining part was used for testing the ANNs. For the modeling of RM: Sinusoidal regression model equation was determined and the predicted data was compared with measured data. Finally, both models were compared with each other. The comparisons of both models show that the measured and testing results are compatible. Regression analysis is a traditional method that can be used for modeling with simple methods. However, this study also showed that ANN modeling can be used as an alternative method for behavior of fresh concrete exposed to vibration in precast concrete structures.

• Journal of architectural history
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• v.33 no.1
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• pp.45-60
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• 2024

This study aims to examine the cutting traces remaining on the bracket tie beams of Sungnyemun gate, identifying the tools employed during the late Goryeo to early Joseon periods by specific processes, and deliberating on the timber shaping techniques utilized in advanced architectural construction during the late Goryeo to early Joseon eras. Through the research, it was confirmed that in the production of Sungnyemun Gate's bracket tie beams during the 14th to 15th centuries, both the timber splitting and ripsawing methods were used in conjunction. Moreover, the wood finishing process revealed the use of a plane. It can be inferred that the characteristics of the plane used during that time were not significantly different from those observed in the later period of the Joseon dynasty. The ripsawing and plane finishing techniques were evident in various parts of the bracket tie beams of Sungnyemun gate across the reigns of king Taejo and Sejong, indicating that the techniques involving ripsaw and plane were already prevalent in the late Goryeo period. Consequently, it can be inferred that the ripsawing and plane finishing techniques might have been applied in the construction of prominent government buildings in Hanyang(Seoul), including Gyeongbokgung Palace, and in the residences of royalty and nobility after the establishment of the Joseon dynasty.

• Nuclear Engineering and Technology
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• v.56 no.4
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• pp.1472-1479
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• 2024

Cyber-Physical Energy Systems (CPESs) integrate cyber and hardware components to ensure a reliable and safe physical power production and supply. Renewable Energy Sources (RESs) add uncertainty to energy demand that can be dealt with flexible operation (e.g., load-following) of CPES; at the same time, scenarios that could result in severe consequences due to both component stochastic failures and aging of the cyber system of CPES (commonly overlooked) must be accounted for Operation & Maintenance (O&M) planning. In this paper, we make use of Deep Reinforcement Learning (DRL) to search for the optimal O&M strategy that, not only considers the actual system hardware components health conditions and their Remaining Useful Life (RUL), but also the possible accident scenarios caused by the failures and the aging of the hardware and the cyber components, respectively. The novelty of the work lies in embedding the cyber aging model into the CPES model of production planning and failure process; this model is used to help the RL agent, trained with Proximal Policy Optimization (PPO) and Imitation Learning (IL), finding the proper rejuvenation timing for the cyber system accounting for the uncertainty of the cyber system aging process. An application is provided, with regards to the Advanced Lead-cooled Fast Reactor European Demonstrator (ALFRED).