• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 2005년도 추계 학술발표회 제17권2호
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• pp.229-232
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• 2005

More than effectively judging the existence of voids behind concrete tunnel linings or under concrete pavements, this research aims to develop the analysis algorithm of radar capable of estimation of the shape of specific voids. To detect or estimate void shapes in non-reinforced concrete, the simulation analysis model of transmission and reflection wave of electromagnetic radar is used. This radar simulation model is carried out with various void shapes. As the results, a proposed method in this study has a possibility of detecting or estimating void shapes with good accuracy.

• 전기학회논문지
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• 제59권3호
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• pp.492-498
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• 2010

Since it is almost impossible to train the dispatchers with real power system, the dispatcher training simulator(DTS) is used for the training. Among various components of the DTS, the power system model(PSM) emulates the dynamic behavior of the power system to calculate the frequency and voltage. The frequency is calculated from various parameters such as mechanical power of power plants, load, inertia, and the damping of the power system. In the PSM, the power plants are modeled as differential equations, so the mechanical power of the power plants are calculated by the numerical methods. Conventionally, the fixed step-size algorithm has been used in the PSM, however it has some drawbacks. This paper develops the prototype PSM using the Matlab, and analyzes the problems of the fixed step-size algorithm by comparing the results with those of PSCAD simulation. In order to overcome the limitations, this paper proposes a modified frequency calculation method using the adaptive step-size algorithm. From the simulation using the proposed method, it is verified that the accuracy of frequency calculation increases substantially while the simulation time is not greatly increased.

• 로봇학회논문지
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• 제15권3호
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• pp.233-239
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• 2020

The aims of this paper is to develop a modular agricultural robot and its autonomous driving algorithm that can be used in field farming. Actually, it is difficult to develop a controller for autonomous agricultural robot that transforming their dynamic characteristics by installation of machine modules. So we develop for the model based control algorithm of rotary machine connected to agricultural robot. Autonomous control algorithm of agricultural robot consists of the path control, velocity control, orientation control. To verify the developed algorithm, we used to analytical techniques that have the advantage of reducing development time and risks. The model is formulated based on the multibody dynamics methods for high accuracy. Their model parameters get from the design parameter and real constructed data. Then we developed the co-simulation that is combined between the multibody dynamics model and control model using the ADAMS and Matlab simulink programs. Using the developed model, we carried out various dynamics simulation in the several rotation speed of blades.

• 한국HCI학회:학술대회논문집
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• 한국HCI학회 2007년도 학술대회 3부
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• pp.326-333
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• 2007

To simulate solid dynamics,a we must com-pute the mass, the center of mass, and the products of inertia about the axes of the body of interest. These mass property computations must be continuously re-peated for certain simulations with rigid bodies or as the shape of the body changes. We introduce a GPU-friendly algorithm to approximate the mass properties for an arbitrarily shaped body. Our algorithm converts the necessary volume integrals into surface integrals on a projected plane. It then maps the plane into a frame-buffer in order to perform the surface integrals rapidly on the GPU. To deal with non-convex shapes, we use a depth-peeling algorithm. Our approach is image-based; hence, it is not restricted by the mathematical or geometric representation of the body, which means that it can efficiently compute the mass properties of any object that can be rendered on the graphics hardware. We compare the speed and accuracy of our algorithm with an analytic algorithm, and demonstrate it in a hydrostatic buoyancy simulation for real-time applications, such as interactive games.

• 한국공간구조학회논문집
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• 제22권2호
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• pp.39-46
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• 2022

Recently, machine learning is widely used to solve optimization problems in various engineering fields. In this study, machine learning is applied to development of a control algorithm for a smart control device for reduction of seismic responses. For this purpose, Deep Q-network (DQN) out of reinforcement learning algorithms was employed to develop control algorithm. A single degree of freedom (SDOF) structure with a smart tuned mass damper (TMD) was used as an example structure. A smart TMD system was composed of MR (magnetorheological) damper instead of passive damper. Reward design of reinforcement learning mainly affects the control performance of the smart TMD. Various hyper-parameters were investigated to optimize the control performance of DQN-based control algorithm. Usually, decrease of the time step for numerical simulation is desirable to increase the accuracy of simulation results. However, the numerical simulation results presented that decrease of the time step for reward calculation might decrease the control performance of DQN-based control algorithm. Therefore, a proper time step for reward calculation should be selected in a DQN training process.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권8호
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• pp.3889-3903
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• 2017

Fast and accurate localization of randomly deployed nodes is required by many applications in wireless sensor networks (WSNs). However, mobile nodes localization in WSNs is more difficult than static nodes localization since the nodes mobility brings more data. In this paper, we propose a Range-based Monte Carlo Box (RMCB) algorithm, which builds upon the Monte Carlo Localization Boxed (MCB) algorithm to improve the localization accuracy. This algorithm utilizes Received Signal Strength Indication (RSSI) ranging technique to build a sample box and adds a preset error coefficient in sampling and filtering phase to increase the success rate of sampling and accuracy of valid samples. Moreover, simplified Particle Swarm Optimization (sPSO) algorithm is introduced to generate new samples and avoid constantly repeated sampling and filtering process. Simulation results denote that our proposed RMCB algorithm can reduce the location error by 24%, 14% and 14% on average compared to MCB, Range-based Monte Carlo Localization (RMCL) and RSSI Motion Prediction MCB (RMMCB) algorithm respectively and are suitable for high precision required positioning scenes.

• 정보처리학회논문지C
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• 제18C권1호
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• pp.15-22
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• 2011

일반적으로 센서 네트워크는 라우팅 트리를 구축한 후에 시간 동기화를 수행한다. 이로 인하여 시간 동기화가 늦어지고 교환하는 패킷이 증가하여 에너지를 많이 소모하는 문제를 유발한다. 본 논문에서는 한 번의 플러딩 과정으로 라우팅 트리를 구축하고 이와 동시에 시간 동기화를 수행하는 TSRA (Time Synchronization Routing Algorithm) 알고리즘을 제안한다. 라우팅 패킷에 패킷 수신 시간과 패킷 전송시간을 추가하여 두 노드간 시간 차이를 구하고, 시간 차이를 전송함으로써 노드들 간의 시간 동기화를 구현한다. 시뮬레이션에 의하여 제안하는 알고리즘은 기존의 동기화 알고리즘인 TPSN과 동등한 수준의 정확도를 보이면서 동기화 속도 및 에너지 소모 면에서 우수하다는 것을 입증하였다.

• 한국수자원학회논문집
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• 제42권3호
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• pp.247-257
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• 2009

본 연구에서는 다방향 흐름 분배 알고리듬과 실시간 보정 알고리듬을 개발하여 분포형 강우-유출 모형에 적용하였다. 개발된 알고리듬의 적용과 분포형 모형 적용상의 약점인 계산시간 개선을 위해 비교적 간단한 수문과정 지배 방정식들을 이용하여 분포형 강우-유출 모형을 작성하였다. DEM(Digital Elevation Model)를 이용하여 공간해상도 변화에 따른 지형정보와 흐름정보의 변동성을 파악하였다. 모의수행 전처리 과정으로 가용한 고해상도 DEM 자료를 사용하여 공간해상도 변화에 따른 흐름정보의 손실을 최소화하고 상세흐름정보를 저해상도 흐름정보에 반영시키는 다방향 흐름분배 알고리듬을 개발하였다. 또한 실시간으로 유역상태량을 보정하는 실시간 보정 알고리듬을 개발하다. 개발된 모형은 저해상도 모의에서 유출 과정의 실제적 거동 정보를 유지할 수 있다. 그러므로 예측 정확도 향상 및 계산시간의 개선이 기대된다.

• Journal of Electrical Engineering and Technology
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• 제8권3호
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• pp.572-580
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• 2013

Power metering and monitoring system is a basic element of Smart Grid technology. This paper proposes a new Non-Intrusive Load Monitoring (NILM) method for a residential buildings sector using the measured total active power consumption. Home electrical appliances are classified by ON/OFF state models, Multi-state models, and Composite models according to their operational characteristics observed by experiments. In order to disaggregate the operation and the power consumption of each model, an algorithm which includes a switching function, a truth table matrix, and a matching process is presented. Typical profiles of each appliances and disaggregation results are shown and classified. To improve the accuracy, a Time Lagging (TL) algorithm and a Permanent-On model (PO) algorithm are additionally proposed. The method is validated as comparing the simulation results to the experimental ones with high accuracy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권8호
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• pp.3630-3656
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• 2018

Degree distribution can provide basic information for structural characteristics and internal relationship in social network. It is a critical procedure for social network topology analysis. In this paper, based on the mean-field theory, we study a special type of social network with exponential distribution of time intervals. First of all, in order to improve the accuracy of analysis, we propose a spreading coefficient algorithm based on intimate relationship, which determines the number of the joined members through the intimacy among members. Then, simulation show that the degree distribution of follows the power-law distribution and has small-world characteristics. Finally, we compare the performance of our algorithm with the existing algorithms, and find that our algorithm improves the accuracy of degree distribution as well as reducing the time complexity significantly, which can complete 29.04% higher precision and 40.94% lower implementation time.