• Nuclear Engineering and Technology
• /
• v.44 no.6
• /
• pp.639-652
• /
• 2012

A three-dimensional discrete fracture network model was developed in order to simulate the hydraulic characteristics of a granitic rock mass at Korea Atomic Energy Research Institute (KAERI) Underground Research Tunnel (KURT). The model used a three-dimensional discrete fracture network (DFN), assuming a correlation between the length and aperture of the fractures, and a trapezoid flow path in the fractures. These assumptions that previous studies have not considered could make the developed model more practical and reasonable. The geologic and hydraulic data of the fractures were obtained in the rock mass at the KURT. Then, these data were applied to the developed fracture discrete network model. The model was applied in estimating the representative elementary volume (REV), the equivalent hydraulic conductivity tensors, and the amount of groundwater inflow into the tunnel. The developed discrete fracture network model can determine the REV size for the rock mass with respect to the hydraulic behavior and estimate the groundwater flow into the tunnel at the KURT. Therefore, the assumptions that the fracture length is correlated to the fracture aperture and the flow in a fracture occurs in a trapezoid shape appear to be effective in the DFN analysis used to estimate the hydraulic behavior of the fractured rock mass.

• 제어로봇시스템학회:학술대회논문집
• /
• 1997.10a
• /
• pp.807-810
• /
• 1997

Digital control of robot manipulator employs discrete-time robot models. It is important to explore effective discrete-time robot models and to analyze their properties in control system designs. This paper presents a new type discrete-time robot model. The model is derived by using trapezoid rule to approximate the convolution integral term, then eliminating nonlinear force terms from robot dynamical equations. The new model obtained has very simple structure, and owns the properties of independence to the nonlinear force terms. According to evaluation criteria, three aspects of the model properties: model accuracy, model validity range and model simplicity are examined and compared with commonly used discrete-time robot models. The validity of the proposed model and its advantages to control system designs are verified by simulation results.

• Journal of Ocean Engineering and Technology
• /
• v.21 no.2 s.75
• /
• pp.75-80
• /
• 2007

The design variables for structural systems, in most practical designs, are chosen from a list of discrete values, which are commercially available sizing. This paper presents the application of Genetic Algorithms for determining the optimum design for two-dimensional structures with discrete and pseudocontinuous design variables. Genetic Algorithms are heuristic search algorithms and are effective tools for finding global solutions for discrete optimization. In this paper, Genetic Algorithms are used as the method of Elitism and penalty parameters, in order to improve fitness in the reproduction process. Examples in this paper include: 10 bar planar truss and 1 bay 8-story frame. Truss with discrete and pseudoucontinuous design variables and steel frame with W-sections are used for the design of discrete optimization.

• Proceedings of the Korea Society for Simulation Conference
• /
• 2000.11a
• /
• pp.142-149
• /
• 2000

Most of supply chain simulation models have been developed on the basis of discrete-event simulation. Since supply chain systems are neither completely discrete nor continuous, the need of constructing a model with aspects of both discrete-event simulation and continuous is provoked, resulting in a combined discrete-continuous simulation. Continuous simulation concerns the modeling over time of a system by a representation in which the state variables change continuously with respect to time. In this paper, an architecture of combined modeling for supply chain simulation is proposed, which presents the equation of continuous part in supply chain and how these equations are used supply chain simulation models. A simple supply chain model is demonstrated the possibility and the capability of this approach.

• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.680-684
• /
• 2005

This paper presents a data-based stability analysis of a MIMO linear time-invariant discrete-time system, as an extension of the previous results for a SISO system. In the MIMO case, a similar discussion as in the case of a SISO system is also applied, except that an augmented input and output space is considered whose dimension is determined in relation to both the orders of the input and output vectors and the numbers of inputs and outputs. As certain subspaces of the input and output space, both output data space and closed-loop data space are defined, which contain all the behaviors of a system, respectively, with zero input in open-loop and with a control input in closed-loop. Then, we can derive the data-based stability conditions, in which the open-loop stability can be checked by using a data matrix whose column vectors span the output data space and the closed-loop stability can also be checked by using a data matrix whose column vectors span the closed-loop data space.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.27 no.1
• /
• pp.15-21
• /
• 2017

In this paper, the decentralized fuzzy observer design technique is presented for discrete-time nonlinear interconnected systems, which are assumed to be with unknown interconnections. To design the decentralized fuzzy observer, the design problem is considered and the performance function is defined to solve the design problem. Based on the performance function, the sufficient condition is derived for the observer design, and its condition is formulated into linear matrix inequalities. Finally, by the simulation result, the validity of the proposed observer design technique is shown.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.18 no.2
• /
• pp.284-310
• /
• 2024

Identifying clinical pathways for disease diagnosis and treatment process recommendations are seriously decision-intensive tasks for health care practitioners. It requires them to rely on their expertise and experience to analyze various categories of health parameters from a health record to arrive at a decision in order to provide an accurate diagnosis and treatment recommendations to the end user (patient). Technological adaptation in the area of medical diagnosis using AI is dispensable; using expert systems to assist health care practitioners in decision-making is becoming increasingly popular. Our work architects a novel knowledge-based recommender system model, an expert system that can bring adaptability and transparency in usage, provide in-depth analysis of a patient's medical record, and prescribe diagnostic results and treatment process recommendations to them. The proposed system uses a set of parallel discrete fuzzy rule-based classifier systems, with each of them providing recommended sub-outcomes of discrete medical conditions. A novel knowledge-based combiner unit extracts significant relationships between the sub-outcomes of discrete fuzzy rule-based classifier systems to provide holistic outcomes and solutions for clinical decision support. The work establishes a model to address disease diagnosis and treatment recommendations for primary lung disease issues. In this paper, we provide some samples to demonstrate the usage of the system, and the results from the system show excellent correlation with expert assessments.

• Journal of Institute of Control, Robotics and Systems
• /
• v.14 no.11
• /
• pp.1155-1164
• /
• 2008

Supervisory control theory, which was first proposed by Ramadge and Wonahm, is a well-suited control theory for the control of complex systems such as semiconductor manufacturing systems, automobile manufacturing systems, and chemical processes because these are better modeled by discrete event models than by differential or difference equation models at higher levels of abstraction. Moreover, decentralized supervisory control is an efficient method for large complex systems according to the divide-and-conquer principle. Decentralized supervisors cannot observe the events those of which occur only within the other supervisors. Therefore decentralized supervisors can be designed according to supervisory control theory under partial observation. This paper presents a solution and a design procedure of supervisory control problem (SCP) for the case of decentralized control and SCP under partial observation (SCPPO). We apply the proposed design procedure to an experimental CIM Testbed. And we compare and analyze the designed decentralized supervisors and partially observed supervisors.

• Proceedings of the KIEE Conference
• /
• 1999.07b
• /
• pp.643-645
• /
• 1999

In between of linear and nonlinear systems lies a large class of bilinear systems. The major importance of bilinear systems lies in the applications to the real world systems such as many physical processes, many biological process, some economic process. Despite vast application of bilinear systems they have not been studied extensively in the domain of singularly perturbations except for a few minor results. In this paper we will utilize singular peturbations theory to obtain the closed-loop optimal solution for discrete-time bilinear systems.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.19 no.6
• /
• pp.865-871
• /
• 2009

In this paper, a novel feedback linearization is proposed for discrete-time nonlinear systems described by discrete-time T-S fuzzy models. The local linear models of a T-S fuzzy model are transformed to a controllable canonical form respectively, and their T-S fuzzy combination results in a feedback linearizable Tagaki-Sugeno fuzzy model. Based on this model, a nonlinear state feedback linearizing input is determined. Nonlinear state transformation is inferred from the linear state transformations for the controllable canonical forms. The proposed method of this paper is more intuitive and easier to understand mathematically compared to the well-known feedback linearization technique which requires a profound mathematical background. The feedback linearizable condition of this paper is also weakened compared to the conventional feedback linearization. This means that larger class of nonlinear systems is linearizable compared to the case of classical linearization.