• Wind and Structures
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• 제18권5호
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• pp.549-566
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• 2014

In spite of progress in the numerical simulation of typhoon wind field in atmospheric boundary layer (ABL), using typhoon wind field model in conjunction with Monte Carlo simulation method can only accurately evaluate typhoon wind field over a general terrain. This method is not enough for a reliable evaluation of typhoon wind field over the actual complex terrain with surface roughness and topography variations. To predict typhoon wind field over the actual complex terrain in ABL, a hybrid numerical simulation method combined typhoon simulation used the typhoon wind field model proposed by Meng et al. (1995) and CFD simulation in which the Reynolds averaged Navier-Stokes (RANS) equations and k-${\varepsilon}$ turbulence model are used. Typhoon wind filed during typhoon Dujuan and Imbudo are simulated using the hybrid numerical simulation method, and compared with the results predicted by the typhoon wind field model and the wind field measurement data collected by Fugro Geotechnical Services (FGS) in Hong Kong at the bridge site from the field monitoring system of wind turbulence parameters (FMS-WTP) to validate the feasibility and accuracy of the hybrid numerical simulation method. The comparison demonstrates that the hybrid numerical simulation method gives more accurate prediction to typhoon wind speed and direction, because the effect of topography is taken into account in the hybrid numerical simulation method.

• Journal of Electrical Engineering and Technology
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• 제8권3호
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• pp.464-471
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• 2013

This paper proposes a hybrid searching algorithm based on parameter identification for power system load models. Hybrid searching was performed by the combination of particle swarm optimization (PSO) and a complex method, which enhances the convergence of solutions closer to minima and takes advantage of global searching with PSO. In this paper, the load model of interest is composed of a ZIP model and a third-order model for induction motors for stability analysis, and parameter sets are obtained that best-fit the output measurement data using the hybrid search. The origin of the hybrid method is to further apply the complex method as a local search for finding better solutions using the selected particles from the performed PSO procedure.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2011년도 제42회 하계학술대회
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• pp.187-188
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• 2011

This paper proposes the hybrid Complex-PSO algorithm based on the complex search method and particle swarm optimization (PSO) for unconstrained optimization. This hybridization intends to produce faster and more accurate convergence to the optimum value. These hybrid will concentrate on determining the dynamic load model parameters, the ZIP model and induction motor model parameters. Measurement-based parameter estimation, which employs measurement data to derive load model parameters, is used. The theoretical foundation of the measurement-based approach is system identification. The main objective of this paper is to demonstrate how the standard particle swarm optimization and complex method can be improved through hybridization of the two methods and the results will be compared with that of their original forms.

• 대한조선학회논문집
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• 제59권6호
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• pp.362-371
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• 2022

As considerable interests in noise emission from the ships have been increased, International Maritime Organization (IMO) standardized the Underwater Radiated Noise (URN) measurement process of commercial ships in deep seas by enacting the related ISO standard ISO 17208-1 and classification societies responded with the enactment or revision of corresponding notations. According to this trend, a new hybrid underwater sound propagation model based on underwater sound propagation theories was developed and its accuracy on analysis was verified through the result comparison with the results of other generally used models. Using the verified model, each URN propagation characteristics adjusted by the correction methods proposed in the ISO standard and class notations were analyzed and compared in two assumed URN measurement cases. The results showed that the effects of transmission loss corrections in the circumstances with less bottom reflections generally similar but they had rather large differences in the model analysis results with bottom-reflection-dominant conditions. It was concluded that the deep consideration of effective bottom-reflection-correction method should be made in future revisions of ISO standard and class notations.

• Smart Structures and Systems
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• 제14권6호
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• pp.1105-1129
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• 2014

The unscented Kalman filter (UKF) has been developed for nonlinear model parametric identification, and it assumes that the model parameters are symmetrically distributed about their mean values without any constrains. However, the parameters in many applications are confined within certain ranges to make sense physically. In this paper, a constrained unscented Kalman filter (CUKF) algorithm is proposed to improve accuracy of numerical substructure modeling in hybrid testing. During hybrid testing, the numerical models of numerical substructures which are assumed identical to the physical substructures are updated online with the CUKF approach based on the measurement data from physical substructures. The CUKF method adopts sigma points (i.e., sample points) projecting strategy, with which the positions and weights of sigma points violating constraints are modified. The effectiveness of the proposed hybrid testing method is verified by pure numerical simulation and real-time as well as slower hybrid tests with nonlinear specimens. The results show that the new method has better accuracy compared to conventional hybrid testing with fixed numerical model and hybrid testing based on model updating with UKF.

• 대한설비공학회:학술대회논문집
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• 대한설비공학회 2006년도 하계학술발표대회 논문집
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• pp.838-846
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• 2006

The purpose of this study to develop the air-conditioning system that adopts adaptive model as an indoor climate control logic for energy saving. The adaptive model using the ability of human thermal adaptation could be expected to alleviate the indoor set-point temperature compared with the past heat-balance model. Especially, in case of hybrid air-conditioning system coupled with natural ventilation and heating/cooling system, the adaptive model can be describe the thermal comfort of inhabitant who stay at hybrid system controlled buildings with accuracy. In this paper, the concept of adaptive model will be described and the results of a continuous measurement on the actual thermal experiences and behaviors of thermal adaptation for office worker will be reported.

• 한국해양공학회지
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• 제17권6호
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• pp.83-90
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• 2003

This paper presents an underwater hybrid navigation system for a semi-autonomous underwater vehicle (SAUV). The navigation system consists of an inertial measurement unit (IMU), and a Doppler velocity log (DVL), accompanied by a magnetic compass. The errors of inertial measurement units increase with time, due to the bias errors of gyros and accelerometers. A navigational system model is derived, to include the scale effect and bias errors of the DVL, of which the state equation composed of the navigation states and sensor parameters is 20. The conventional extended Kalman filter was used to propagate the error covariance, update the measurement errors, and correct the state equation when the measurements are available. Simulation was performed with the 6-d.o,f equations of motion of SAUV, using a lawn-mowing survey mode. The hybrid underwater navigation system shows good tracking performance, by updating the error covariance and correcting the system's states with the measurement errors from a DVL, a magnetic compass, and a depth sensor. The error of the estimated position still slowly drifts in the horizontal plane, about 3.5m for 500 seconds, which could be eliminated with the help of additional USBL information.

• Geomechanics and Engineering
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• 제22권1호
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• pp.81-95
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• 2020

Measurement of the unconfined compressive strength (UCS) of the rock is critical to assess the quality of the rock mass ahead of a tunnel face. In this study, extensive field studies have been conducted along 3,885 m of the new Nagasaki tunnel in Japan. To predict UCS, a hybrid model of artificial neural network (ANN) based on genetic algorithm (GA) optimization was developed. A total of 1350 datasets, including six parameters of the Measurement-While- Drilling data and the UCS were considered as input and output parameters respectively. The multiple linear regression (MLR) and the ANN were employed to develop contrast models. The results reveal that the developed GA-ANN hybrid model can predict UCS with higher performance than the ANN and MLR models. This study is of great significance for accurately and effectively evaluating the quality of rock masses in tunnel engineering.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 춘계 학술대회 학술발표 논문집
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• pp.303-306
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• 2003

In radar tracking, since the sensor measures range, azimuth and elevation angle of a target, the measurement equation is nonlinear and the extended Kalman filter (EKF) is applied to nonlinear estimation. The conventional EKF has been widely used as a nonlinear filter for radar tracking, but the considerably large measurement error due to the linearization of nonlinear function in highly nonlinear situations may deteriorate the performance of the EKF To solve this problem, a fuzzy-model-based Kalman filter (FMBKF) is proposed for radar tracking. The FMBKF uses a local model approximation based on a TS fuzzy model instead of a Jacobian matrix to linearize nonlinear measurement equation. The hybrid GA and RLS method is used to identify the premise and the consequent parameters and the rule numbers of this TS fuzzy model. In two-dimensional radar tracking problem, the proposed method is compared with the conventional EKF.

• 한국해양공학회:학술대회논문집
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• 한국해양공학회 2003년도 춘계학술대회 논문집
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• pp.149-156
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• 2003

This paper presents an underwater hybrid navigation system for a semi-autonomous underwater vehicle (SAUV). The navigation system consists of an inertial measurement unit (IMU), an ultra-short baseline (USBL) acoustic navigation sensor and a doppler velocity log (DVL) accompanying a magnetic compass. The errors of inertial measurement units increase with time due to the bias errors of gyros and accelerometers. A navigational system model is derived to include the error model of the USBL acoustic navigation sensor and the scale effect and bias errors of the DVL, of which the state equation composed of the navigation states and sensor parameters is 25 in the order. The conventional extended Kalman filter was used to propagate the error covariance, update the measurement errors and correct the state equation when the measurements are available. Simulation was performed with the 6-d.o.f. equations of motion of SAUV in a lawn-mowing survey mode. The hybrid underwater navigation system shows good tracking performance by updating the error covariance and correcting the system's states with the measurement errors from a DVL, a magnetic compass and a depth senor. The error of the estimated position still slowly drifts in horizontal plane about 3.5m for 500 seconds, which could be eliminated with the help of additional USBL information.