• Korean Journal of Ecology and Environment
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• v.46 no.1
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• pp.1-9
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• 2013

Algal blooms in potable water supplies are becoming an increasingly prevalent and serious water quality problem around the world. In addition to precipitating taste and odor problems, blooms damage the environment, and some classes like cyanobacteria (blue-green algae) release toxins that can threaten human health, even causing death. There is a recognized need in the water industry for models that can accurately forecast in real-time algal bloom events for planning and mitigation purposes. In this study, using data for an interconnected system of rivers and reservoirs operated by a New Jersey water utility, various ANN models, including both discrete prediction and classification models, were developed and tested for forecasting counts of three different algal classes for one-week and two-weeks ahead periods. Predictor model inputs included physical, meteorological, chemical, and biological variables, and two different temporal schemes for processing inputs relative to the prediction event were used. Despite relatively limited historical data, the discrete prediction ANN models generally performed well during validation, achieving relatively high correlation coefficients, and often predicting the formation and dissipation of high algae count periods. The ANN classification models also performed well, with average classification percentages averaging 94 percent accuracy. Despite relatively limited data events, this study demonstrates that with adequate data collection, both in terms of the number of historical events and availability of important predictor variables, ANNs can provide accurate real-time forecasts of algal population counts, as well as foster increased understanding of important cause and effect relationships, which can be used to both improve monitoring programs and forecasting efforts.

• Proceedings of the KSME Conference
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• 2002.08a
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• pp.561-564
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• 2002

For the reduction of fuel consumption of high speed, the aerodynamic drag must be reduced. In early vehicle design process, it is very important to have information about aerodynamic characteristics of design models. In this phase CFD methods are usually used to predict the aerodynamic forces. But commercial programs using turbulence models cannot give a good agreement with experimental result and have also problems with convergence. PowerFLOW employs a new technology called DIGITAL PHYSICS, which provides a different approach to simulating fluids. DIGITAL PHYSICS uses a lattice-based approach (extended from lattice-gas and lattice-Boltzmann methods) where time, space and velocity are discrete. This discrete system represents the Wavier-Stokes continuum behavior without the numerical instability Issues of traditional CFD solvers, such as convergence. In this paper, aerodynamic performance of vehicles are simulated using PowerFLOW by Exa and results are compared with experimental wind tunnel data.

• Proceedings of the Korea Society for Simulation Conference
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• 1996.05a
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• pp.15-15
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• 1996

A shop floor control system (SFCS) is the central part of a CIM system used to control the activities of several pieces of manufacturing equipment (e.g., NC machines, robots, conveyors, AGVs, AS/RS). The SFCS receives orders and related process plans, and then performs selecting a specific process routing, allocating resources, scheduling the workpieces, downloading the processing instructions (e.g., RS-274 instructions for NC machines, VAL II programs for robot), monitoring the progress of activities, detecting and recovering from errors, and preparing reports on the status of the manufacturing system. Simulation has been utilized in discovering control policies used for resolving shop floor be control problems such as resource contentions, part dispatching, deadlock. The simulation model must be designed to respond to real-time data coming from a shop floor. However, to rapidly build a realtime simulation model of SFCS cannot be easily accomplished. This talk is to address an automatic program generator of discrete event simulation model for shop floor control from process plans and resource models. The program generator is capable of constructing complete discrete simulation models for multi-product and multi-stage flexible manufacturing systems.

• Journal of Power Electronics
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• v.12 no.5
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• pp.715-722
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• 2012

New discrete time domain models for the peak current controlled (PCC) power LED drivers in continuous conduction mode include for the first time the effects of the time delay in the pulse-width-modulator. Realistic amounts of time delay are found to have significant effects on the average output LED current and on the critical inductor value at the boundary between the two conduction modes. Especially, the time delay can provide an accurate LED current for the PCC buck converter with a wide input voltage. The models can also predict the critical inductor value at the mode boundary as functions of the input voltage and the time delay. The overshoot of the peak inductor current due to the time delay results in the increase of the average output current and the reduction of the critical inductor value at the mode boundary in all converters. Experimental results are presented for the PCC buck LED driver with constant-frequency controller.

• Proceedings of the Korea Society for Simulation Conference
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• 2002.05a
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• pp.253-258
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• 2002

This paper proposes a methodology for development of protocol models. The methodology attempts to employ two modeling environments in models development, NS2 and DEVSim++, which will interoperate during simulation. NS2 is a widely used network simulator in protocol research, which employs an informal modeling approach. Within the approach time and state information of protocol models are not explicitly described, thus being hard to validate model. On the other hand the DEVS formalism is a mathematical framework for modeling a discrete event system in a hierarchical, modular manner. In DEVS, model's time and state information is described explicitly, By using DEVS formalism, models can easily be validated and errors in the modeling stage can be reduced. However, the DEVS simulator, DEVSim++, supports a small amount of models library which are required to build simulation models of general communication network. Although NS2 employs an informal modeling approach and models validation is difficult, it supports abundant models library validated by experimental users. Thus, combination of DEVS models and NS2 models may be an effective solution for network modeling. Such combination requires interoperation between DEVSim++ simulator and NS2 simulator. This paper develops an environment for such interoperation. Correctness and effectiveness of the implemented interoperation environment have been validated by simulation of UDP and TCP models.

• 한국전산유체공학회:학술대회논문집
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• 2000.05a
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• pp.66-72
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• 2000

Aerodynamic sensitivity analysis is performed for the Navier-Stokes equations coupled with two-equation turbulence models using a discrete adjoint method and a direct differentiation method respectively. Like the mean flow equations, the turbulence model equations are also hand-differentiated to accurately calculate the sensitivity derivatives of flow quantities with respect to design variables in turbulent viscous flows. Both the direct differentiation code and the adjoint variable code adopt the same time integration scheme with the flow solver to efficiently solve the differentiated equations. The sensitivity codes are then compared with the flow solver in terms of solution accuracy, computing time and computer memory requirements. The sensitivity derivatives obtained from the sensitivity codes with different turbulence models are compared with each other. Using two-equation turbulence models, it is observed that a usual assumption of constant turbulent eddy viscosity in adjoint methods may lead to seriously inaccurate results in highly turbulent flows.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1896-1900
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• 2003

In this paper, a new type of output feedback control, called a receding horizon finite memory control (RHFMC), is proposed for stochastic discrete-time state space systems. Constraints such as linearity and finite memory structure with respect to an input and an output, and unbiasedness from the optimal state feedback control are required in advance. The proposed RHFMC is chosen to minimize an optimal criterion with these constraints. The RHFMC is obtained in an explicit closed form using the output and input information on the recent time interval. It is shown that the RHFMC consists of a receding horizon control and an FIR filter. The stability of the RHFMC is investigated for stochastic systems.

• Journal of the Korean Institute of Gas
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• v.3 no.2 s.7
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• pp.34-42
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• 1999

The discrete variables such as time and sequence must be considered for automating HAZOP analysis of batch processes in contrast with continuous processes. Because these variables can not be explained by the method used in the HAZOP analysis of continuous processes, we have developed the methodology for HAZOP analysis of batch processes on the basis of the relation between discrete variables and continuous ones. In this study, we have discussed the performance of the methodology on a Latex batch process to evaluate its effectiveness.

• Journal of the Korea Society for Simulation
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• v.1 no.1
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• pp.64-76
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• 1992

The DEVS(discrete event system specificaition) formalism specifies a discrete event system in a hierarchical, modular form. DEVSIM++ is a C++based general purpose DEVS abstract simulator which can simulate systems modeled by the DEVS formalism in a sequential environment. This paper describes P-DEVSIM++which is a parallel version of DEVSIM++ . In P-DEVSIM++, the external and internal event of DEVS models can by processed in parallel. For such processing, we propose a parallel, distributed optimistic simulation algorithm based on the Time Warp approach. However, the proposed algorithm localizes the rollback of a model within itself, not possible in the standard Time Warp approach. An advantage of such localization is that the simulation time may be reduced. To evaluate its performance, we simulate a single bus multiprocessor architecture system with an external common memory. Simulation result shows that significant speedup is made possible with our algorithm in a parallel environment.

• Proceedings of the KIPE Conference
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• 2011.07a
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• pp.481-482
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• 2011

New discrete time domain models for the peak current controlled (PCC) power LED drivers in continuous conduction mode include for the first time the effects of time delay in the pulse-width-modulator. Realistic amounts of time delay are found to have significant effects on the average output LED current and on the critical inductor value at the boundary between two conduction modes. Especially, the time delay can provide an accurate LED current for the PCC buck converter with a wide input voltage. The models can also predict the critical inductor values at the mode boundary as functions of the input voltage and the time delay.