• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.5
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• pp.265-278
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• 2021

When a dangerous event arises for people inside a building and an immediate evacuation is required, it is important that suitable routes have been previously defined. These situations can happen especially when buildings are crowded, making the occupants have a very high vulnerability and can be trapped if they do not evacuate quickly and safely. However, in most cases, routes are considered based just on their proximity or short distance to the exit areas, and evacuation simulations that include more variables are not performed. This work aims to propose a methodology for building's indoor evacuation activities under the premise of processing simulation scenarios in multi-agent environments. In the methodology, importance indexes of simplified and validated geometry data from a BIM (Building Information Modeling) are considered as heuristic input data in a proposed algorithm. The algorithm is based on AP-Theta^* pathfinding and collision avoidance machine learning techniques. It also includes conditioning variables such as the number of people, speed of movement as well as reaction ability of the agents that influence the evacuation times. Moreover, collision avoidance is applied between people or with objects along the route. The simulations using the proposed algorithm are tested in NetLogo for diverse scenarios, showing feasible evacuation routes and calculating evacuation times in a multi-agent environment. The experimental results are obtained by applying the method in a study case and demonstrate the level of effectiveness of the algorithm, and the influence of the conditioning variables analyzed together when performing safe evacuation routes.

• Journal of the Korea Society for Simulation
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• v.30 no.1
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• pp.113-126
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• 2021

The future energy consumption pattern will show a very different pattern from the present due to the increase of distributed power sources such as renewable energy and the birth of the concept of prosumers, etc. Accordingly, it can be predicted that the direction of establishment of an appropriate production and supply plan considering the stability and consumption efficiency of the entire power grid will also be different from now. This paper proposes a simulation model that can test a new operational strategy when faced with a number of possible future environments. Through the proposed model, it is possible to simulate and analyze power consumed and supplied in a future Smart Grid environment, in which a large amount of new concepts including energy storage service (ESS) and distributed energy resources (DER) will be added. In particular, it is possible to model complex systems structurally by using DEVS formalism among the ABM (Agent-Based Model) methodologies that can model decision-making for each agent existing in the grid, and several factors can be easily added to the grid. The simulation model was verified using given dataset in the current situation, and scenario analysis was performed by simply adding an ESS, one of the main elements of the smart grid, to the model.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.12
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• pp.1231-1237
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• 2014

This paper proposes a reduced-order disturbance observer based coordinated tracking controller for uncertain heterogeneous multi-agent systems. To this end, first the control problem is converted as a robust control problem. Then, a dynamic coordinated controller is designed based on the recently proposed reduced-order disturbance observer. Simulation results are given to show the effectiveness of the proposed control scheme.

• The Transactions of the Korea Information Processing Society
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• v.7 no.2
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• pp.454-460
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• 2000

In this paper, an architecture is suggested which efficiently detects intrusions in network environments. In the architecture, the Blackboardbased agent coordinates opinions of several independent agents which are performing unique functions, by resolving conflicts and reconfirming notices of intrusion. In the simulation, it was found that conventional agents judge simple resource access activities as 'intrusion' while blakcboard-based agent reserves the judgement until additional information confirms notices of independent agents. Reconfirmation process based on additional questioning will roduce positive errors.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.05a
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• pp.471-474
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• 2004

In order to quickly respond to the rapidly changing manufacturing environment, it is imperative for the system to have such capabilities as flexibility, adaptability, reusability, etc. One of the promising approaches for new manufacturing paradigm satisfying those capabilities is the fractal manufacturing system (FrMS). FrMS is based on the concept of autonomously cooperating and self-reconfigurable agents referred to as fractals. In this paper, a fractal template is proposed to have both fractal-specific and agent-specific characteristics and proper techniques for implementation are also selected. The proposed template can be easily extended to the platform of FrMS which supports simulation, shop flow control, and other research issues existed in the manufacturing systems. An example of applying the proposed template to the simulation is also presented.

• Journal of Korea Technical Association of The Pulp and Paper Industry
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• v.36 no.3
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• pp.35-43
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• 2004

Reduction of fresh water consumption and effluent discharge provide diverse advantages in raw materials and energy savings. Papermaking system closure, however, reduces the efficiency of additives, decreases retention and dewatering, and causes many other Problems in papermaking. Accumulation of inorganic and organic substances in the process white water is the prime cause of these problems. Understanding of the accumulation phenomena of the detrimental substances in the papermaking process is of great importance for papermaking system closure. In this study a process simulation method was employed to analyze the accumulation phenomena of anionic starch in the process white water as the reuse rate of dry broke and pick up of surface sizing agent is increased. Steady state simulation studies were carried out based on the model developed in previous study. The variation of dissolved starch concentration in each process unit was monitored as a function of reuse rate of dry broke and surface sizing agent pick up rate. The result showed that dissolved starch concentration Increased as reuse rate of dry broke and surface sizing agent pick up rate was increased.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.1114-1121
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• 2022

Construction laborers and crews play a critical role in achieving a safe and productive construction site. Many past research studies used top-down approaches/perspectives for studying the impact of laborers' performance on overall construction site outputs with limited flexibility in accounting for laborers' various characteristics. However, the recent reap in computational advances allowed applications of bottom-up architectures, which can potentially incorporate heterogeneous characteristics of laborers' individual behavioral and decision-making features effectively. Accordingly, agent-based modeling (ABM), as a tool to leverage a bottom-up methodological approach, has been widely adopted by recent research. Existing literature investigated the influence of changes in laborers' behaviors and interactions on either construction sites' safety performance or productivity performance individually, leaving the tradeoff between safety and productivity in this context relatively unexplored. Accordingly, this study aims to develop an agent-based framework to study the tradeoff between project safety and productivity performances resulting from changes in laborers' behaviors after attending safety trainings. Our findings via simulations indicate that proper safety trainings can improve safety performance without negatively impacting productivity performance.

• Journal of Korea Spatial Information System Society
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• v.12 no.1
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• pp.76-84
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• 2010

Many pedestrian simulation models for micro-scale spaces as building indoor areas have been proposed for the last decade and two models - social force model and floor field model - are getting attention. Among these, CA-based floor field model is viewed more favourable for computer simulations than computationally complex social force model. However, Kirchner's floor field model has limitations in capturing the differences in dynamic values of different agents and this study proposes an enhanced algorithm. This study improved the floor field model in order for an agent to be able to exclude the influences of its own dynamic values by changing the data structure, and, also modified the initial dynamic value problem in order to fit more realistic environment. In the simulations, real 3D building data stored in a spatial DBMS were used considering future integration with indoor localization sensors and real time applications.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.201-205
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• 1997

As manufacturing system have become complex and globalized, rapid development and production of products are essentially requisites for competitiveness. The importance of agility in manufacturing is being emphasized and a new paradigm is necessary for reduction of the time and expenses related to planning, product development and production. To meet such requirements, virtual manufacturing (VM) environment was suggested. In this paper, Multi-agent system is adopted into VM operating system. Because our system is flexible due to agent technology, agents can be added or deleted with ease. VM unit modules which were defined as DEVS models execute independent simulation of other modules in unit level and compose one VM system with other modules. They also execute simulation in system level. This research can contribute to usefulness of VM environment due to flexibility and extensibility of this system.

• Journal of the Korea Society for Simulation
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• v.30 no.1
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• pp.43-54
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• 2021

Since COVID-19 (Severe acute respiratory syndrome coronavirus type 2, SARS-Cov-2) was first discovered at the end of 2019, it has spread rapidly around the world. This study introduces an agent-based simulation model representing COVID-19 spread in South Korea to investigate the effect of detect level (contact tracing) on the virus spread. To develop the model, related data are aggregated and probability distributions are inferred based on the data. The entire process of infection, quarantine, recovery, and death is schematically described and the interaction of people is modeled based on the traffic data. A composite logistic functions are utilized to represent the compliance of people to the government move control such as social distancing. To demonstrate to effect of detect level on the virus spread, detect level is changed from 0% to 100%. The results indicate active contact tracing inhibits the virus spread and the inhibitory effect increases geometrically as the detect level increases.