• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2009.04a
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• pp.151-156
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• 2009

Forward modelling of ground penetrating radar (GPR) data is implemented using a new finite element ray tracing technique. The method is different from conventional ray tracing techniques in that the radar cross section of buried targets, the effective area of the receiving antenna, and the attenuation along the raypath are computed. The forward models are used to understand radar signatures measured across various ground structures which are important in detecting engineering hazards at construction sites, void spaces beneath simulated road beds, as well as a learning tool to avoid pitfalls in radargram interpretation. Forward modelling of radar data also can be used in predicting possible structures present at cultural property sites.

• Journal of Power Electronics
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• v.9 no.6
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• pp.854-865
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• 2009

Super-lift dc-dc converters are a series of advanced step-up dc-dc topologies that provide high voltage transfer gains by super-lift techniques. This paper presents a developed graphical modelling method for super-lift converters and gives a thorough analysis with a consideration of the effects caused by parasitic parameters and diodes' forward voltage drop. The general guidelines for constructing and deriving graphical models are provided for system analysis. By applying it to examples, the proposed method shows the advantages of high convenience and feasibility. Both the circuit simulation and experimental results are given to support the theoretical analysis.

• Computers and Concrete
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• v.8 no.5
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• pp.541-561
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• 2011

The Finite Element Method (FEM) was employed to demonstrate that accurate simulations of seismically repaired and retrofitted reinforced concrete shear walls can be achieved provided a good analysis program with comprehensive models for material and structural behaviour is used. Furthermore, the analysis tool should have the capability to retain residual damage experienced by the original structure and carry it forward in the repaired and retrofitted structure. The focus herein is to provide quick, simple, but reliable modelling procedures for repair and retrofitting strategies such as concrete replacement, addition of diagonal reinforcing bars, bolting of external steel plates, and bonding of external steel plates and fibre reinforced polymer sheets, thus illustrating versatility in the modelling. Slender, squat, and slender-squat shear walls were investigated. The modelling utilized simple rectangular membrane elements for the concrete, truss bar elements for the steel and FRP retrofitting materials, and bond-link elements for the bonding interface between steel or FRP to concrete. The analyses satisfactorily simulated seismic behaviour, including lateral load capacity, displacement capacity, energy dissipation, hysteretic response, and failure mode.

• Journal of Advanced Marine Engineering and Technology
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• v.20 no.3
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• pp.286-286
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• 1996

A neural predictive tracking system for the control of structure-unknown dynamic system is presented. The control system comprises a neural network modelling mechanism for the the forward and inverse dynamics of a plant to be controlled, a feedforward controller, feedback controller, and an error prediction mechanism. The feedforward controller, a neural network model of the inverse dynamics, generates feedforward control signal to the plant. The feedback control signal is produced by the error prediction mechanism. The error predictor adopts the neural network models of the forward and inverse dynamics. Simulation results are presented to demonstrate the applicability of the proposed scheme to predictive tracking control problems.

• Journal of Advanced Marine Engineering and Technology
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• v.20 no.3
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• pp.154-161
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• 1996

A neural predictive tracking system for the control of structure-unknown dynamic system is presented. The control system comprises a neural network modelling mechanism for the the forward and inverse dynamics of a plant to be controlled, a feedforward controller, feedback controller, and an error prediction mechanism. The feedforward controller, a neural network model of the inverse dynamics, generates feedforward control signal to the plant. The feedback control signal is produced by the error prediction mechanism. The error predictor adopts the neural network models of the forward and inverse dynamics. Simulation results are presented to demonstrate the applicability of the proposed scheme to predictive tracking control problems.

• Korean Chemical Engineering Research
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• v.61 no.2
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• pp.328-339
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• 2023

Methanol steam reforming (MSR) is a promising method for hydrogen supplying as a critical step in hydrogen fuel cell commercialization in mobile applications. Modelling and understanding of the reactor behavior is an attractive research field to develop an efficient reformer. Three-layer feed-forward artificial neural network (ANN) and Box-Behnken design (BBD) were used to modelling of MSR process using the Cu-SiO₂ aerogel catalyst. Furthermore, impacts of the basic operational variables and their mutual interactions were studied. The results showed that the most affecting parameters were the reaction temperature (56%) and its quadratic term (20.5%). In addition, it was also found that the interaction between temperature and Steam/Methanol ratio is important on the MSR performance. These models precisely predict MSR performance and have great agreement with experimental results. However, on the basis of statistical criteria the ANN technique showed the greater modelling ability as compared with statistical BBD approach.

• Journal of Advanced Marine Engineering and Technology
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• v.32 no.8
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• pp.1303-1308
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• 2008

Keeping cooling water temperature higher within the allowable range helps marine engines to run in more efficient condition especially when the engine load is low. Temperature control of jacket cooling water in outlet side of main engine has been more widely adopted to ships these days for the purpose to reduce fuel consumption rate. But If the temperature sensor for the control loop is placed at the outlet of engine, it brings more difficulties in attaining stable and desirable properties due to dead times included in pipe length and engine itself comparing to the case where the measuring point is at the inlet side of main engine. In relation with this problem, Feed-forward control could be one of realistic solutions as it reveals good properties and requires less cost for system configuration. This study suggests a forward control system which leads to improved temperature control performances to disturbance signals which could arise from variation of engine load or weather condition. Two dead times in the modelling were described, considering pipe length between the actuator and the engine as well as the thermal process inside the engine. The results of analysis were shown by simulations to confirm responses under different conditions.

• Journal of Electrical Engineering and Technology
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• v.12 no.6
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• pp.2219-2226
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• 2017

This paper deals with artificial neural network approach for automatic detection of severity level of stator winding fault in induction motor. The problem is faced through modelling and simulation of induction motor with inter coil shorting in stator winding. The sum of the absolute values of difference in the peak values of phase currents from each half cycle has been chosen as the main input to the classifier. Sample values from workspace of Simulink model, which are verified with experiment setup practically, have been imported to neural network architecture. Consideration of a single input extracted from time domain simplifies and advances the fault detection technique. The output of the feed forward back propagation neural network classifies the short circuit fault level of the stator winding.

• International Journal of Automotive Technology
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• v.7 no.4
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• pp.459-468
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• 2006

The objective of this paper is the development of the forward-looking dynamic simulation model of a hybrid electric vehicle(HEV) for a fuel economy study. The specification of the vehicle is determined based on two factors, engine peak power to curb weight ratio and specific engine power. The steady state efficiency models of the powertrain components are explained in detail. These include a spark ignition direct injection(SIDI) engine, an integrated starter alternator(ISA), and an infinitely variable transmission(IVT). The paper describes the integration of these models into a forward facing dynamic simulation diagram using the AMESim environment. Appropriate vehicle and driver models have been added and described. The controller was designed in Simulink and was combined with the physical powertrain model by the co-simulation interface. Finally, the simulation results of the HEV are compared with those of a baseline vehicle in order to demonstrate the fuel economy potential. Results for the vehicle speed error and the fuel economy over standard driving cycles are illustrated.

• Journal of Electrical Engineering and Technology
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• v.11 no.2
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• pp.265-273
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• 2016

A water wall system is one of the most important components of a boiler in a thermal power plant, and it is a nonlinear Multi-Input and Multi-Output (MIMO) system, with 6 inputs and 3 outputs. Three models are developed and comp for the controller design, including a linear model, a multilayer feed-forward neural network (MFNN) model and an Echo State Network (ESN) model. First, the linear model is developed by linearizing a given nonlinear model and is analyzed as a function of the operating point. Second, the MFNN and the ESN are developed by using training data from the nonlinear model. The three models are validated using Matlab with nonlinear input-output data that was not used during training.