• Journal of the Computational Structural Engineering Institute of Korea
• /
• v.32 no.2
• /
• pp.103-108
• /
• 2019

Non-equilibrium molecular dynamics simulation on the thermal boundary resistance(TBR) of an aluminum(Al)/silicon(Si) interface was performed in the present study. The constant heat flux across the Si/Al interface was simulated by adding the kinetic energy in hot Si region and removing the same amount of the energy from the cold Al region. The TBR estimated from the sharp temperature drop at the interface was independent of heat flux and equal to $5.13{\pm}0.17K{\cdot}m^2/GW$ at 300K. The simulation result was experimentally confirmed by the time-domain thermoreflectance technique. A 90nm thick Al film was deposited on a Si(100) wafer using an e-beam evaporator and the TBR on the film/substrate interface was measured using the time-domain thermoreflectance technique based on a femtosecond laser system. A numerical solution of the transient heat conduction equation was obtained using the finite difference method to estimate the TBR value. Experimental results were compared to the prediction and discussions on the nanoscale thermal transport phenomena were made.

• Journal of the Korea Society for Simulation
• /
• v.19 no.3
• /
• pp.37-43
• /
• 2010

In field, one can observe without difficulties that two flocks are intersected or combined with each other. For example, a fish flock in a stream separates into two part by obstacles (e.g. stone) and rejoins behind the obstacles. The dynamics of two flocks guided by their leader were studied in the situation where the flocks cross each other with a crossing angle, ${\theta}$, between their moving directions. Each leader is unaffected by its flock members whereas each member is influenced by its leader and other members. To understand the dynamics, I investigated the order parameter, ${\phi}$, defined by the absolute value of the average unit velocity of the flocks' members. When the two flocks were encountered, the first peak in ${\phi}$ was appeared due to the breaking of the flocks' momentum balance. When the flocks began to separate, the second peak in ${\phi}$ was observed. Subsequently, erratic peaks were emerged by some individuals that were delayed to rejoin their flock. The amplitude of the two peaks, $d_1$ (first) and $d_2$ (second), were measured. Interestingly, they exhibited a synchronized behavior for different ${\theta}$. This simulation model can be a useful tool to explore animal behavior and to develop multi-agent robot systems.

• Journal of KIISE
• /
• v.43 no.12
• /
• pp.1365-1375
• /
• 2016

One of the most important capabilities for autonomous service robots working in living environments is to recognize and understand the correct context in dynamically changing environment. To generate high-level context knowledge for decision-making from multiple sensory data streams, many technical problems such as multi-modal sensory data fusion, uncertainty handling, symbolic knowledge grounding, time dependency, dynamics, and time-constrained spatio-temporal reasoning should be solved. Considering these problems, this paper proposes an effective dynamic context management and spatio-temporal reasoning method for intelligent service robots. In order to guarantee efficient context management and reasoning, our algorithm was designed to generate low-level context knowledge reactively for every input sensory or perception data, while postponing high-level context knowledge generation until it was demanded by the decision-making module. When high-level context knowledge is demanded, it is derived through backward spatio-temporal reasoning. In experiments with Turtlebot using Kinect visual sensor, the dynamic context management and spatio-temporal reasoning system based on the proposed method showed high performance.

• Journal of the Korean Institute of Telematics and Electronics S
• /
• v.36S no.12
• /
• pp.10-19
• /
• 1999

Cellular Automata Neural Systems(CANS) are neural networks based on biological development and evolution. Each neuron of CANS has local connection and acts as a form of pulse according to the dynamics of the chaotic neuron. CANS are generated from initial cells according to the CA rule. In the previous study, to obtain the useful ability of CANS, we make the pattern of initial cells evolve. However, it is impossible to represent all solution space, so we propose an evolving method of CA rule to overcome this defect in this paper. DNA coding has the redundancy and overlapping of gene and is apt for the representation of the rule. In this paper, we show the general expression of CA rule and propose translation method from DNA code to CA rule. The effectiveness of the proposed scheme was verified by applying it to the navigation problem of autonomous mobile robot.

• Journal of the Korea Society of Computer and Information
• /
• v.22 no.1
• /
• pp.63-69
• /
• 2017

In this paper, we propose a method to optimize the geometry and installation position of the mixer in the selective catalytic reduction (SCR) system by computational fluid dynamic(CFD). Using the commercial CFD software of CFD-ACE+, the flow dynamics of the flue gas was numerically analyzed for improving the injection uniformity of the reduction agent. Numerical analysis of the mixed gas heat flow into the upstream side of the primary SCR catalyst layer was performed when the denitrification facility was operated. The characteristics such as the flow rate, temperature, pressure loss and ammonia concentration of the mixed gas consisting of the flue gas and the ammonia reducing gas were examined at the upstream of the catalyst layer of SCR. The temperature difference on the surface of the catalyst layer is very small compared to the flow rate of the exhaust gas, and the temperature difference caused by the reducing gas hardly occurs because the flow rate of the reducing gas is very small. When the mixed gas is introduced into the SCR reactor, there is a slight tendency toward one wall. When the gas passes through the catalyst layer having a large pressure loss, the flow angle of the exhaust gas changes because the direction of the exhaust gas changes toward a smaller flow. Based on the uniformity of the flow rate of the mixed gas calculated at the SCR, it is judged that the position of the test port reflected in the design is proper.

• Journal of the Korea Society of Computer and Information
• /
• v.25 no.2
• /
• pp.189-195
• /
• 2020

In this study, the inlet duct and guide vane of the gas floating absorption tower were redesigned to improve the desulfurization efficiency so that the exhaust gas can be uniformly introduced into the absorption tower. In order to reduce the sulfur oxide pollutants among the main sources of air pollutants in industrial boilers, the existing equipment is redesigned and solved. For this purpose, change the exhaust gas, the slurry and recycling the adsorbent to improve the removal efficiency of SOx component in the exhaust gas inside the gas floating absorption tower so as to uniformly contact. And the initial design value and CFD value for the pressure loss from the boiler outlet to the gas floating absorption tower outlet are verified. Also, the velocity distribution of the exhaust gas, the concentration distribution of the recycled adsorbent, the liquid slurry behavior, and the pressure loss were compared. The results confirmed that the desulfurization efficiency was improved because the pressure loss from the boiler outlet to the absorption tower outlet was reduced and the deflection of the exhaust gas was minimized.

• Journal of the Korea Society of Computer and Information
• /
• v.26 no.3
• /
• pp.9-17
• /
• 2021

In this paper, an autonomous multi-agent path planning using reinforcement learning for monitoring of infrastructures and resources in a computationally distributed system was proposed. Reinforcement-learning-based multi-agent exploratory system in a distributed node enable to evaluate a cumulative reward every action and to provide the optimized knowledge for next available action repeatedly by learning process according to a learning policy. Here, the proposed methods were presented by (a) approach of dynamics-based motion constraints multi-agent path-planning to reduce smaller agent steps toward the given destination(goal), where these agents are able to geographically explore on the environment with initial random-trials versus optimal-trials, (b) approach using agent sub-goal selection to provide more efficient agent exploration(path-planning) to reach the final destination(goal), and (c) approach of reinforcement learning schemes by using the proposed autonomous and asynchronous triggering of agent exploratory phases.

• Journal of the Korea Society of Computer and Information
• /
• v.28 no.1
• /
• pp.121-127
• /
• 2023

In this study, the design conditions and CFD analysis results are compared and reviewed in SCR that can optimally reduce nitrogen compounds. To this end, it was analyzed and compared using CFD to see if the design criteria were satisfied for the shell and tube areas of the boiler. In the SCR system, the analysis area is the gas/air heat exchanger on the shell side, and eight tubes of the gas/air heat exchanger on the tube side. Through CFD analysis, the gas velocity distribution on the primary catalyst side of the SCR system was designed to be 2.4%, and the NH3/NOx molar ratio distribution was 3.7%, which satisfied the design criteria. In addition, the uniformity of the temperature distribution was confirmed and the required condition of 260℃ or higher was satisfied. The angle of the gas entering the catalyst met the design conditions at 2.9 degrees, and the pressure loss that occurred also satisfied the design requirements. Through this CFD analysis, it was confirmed that it was designed and operated by satisfying the design conditions required for each area.

• Journal of Institute of Control, Robotics and Systems
• /
• v.7 no.9
• /
• pp.717-722
• /
• 2001

This paper presents a methodology on the backward path tracking control of a trailer type robot which consists of two parts: a tractor and a trailer. It is difficult to control the motion of a trailer vehicle since its dynamics is non-holonomic. Therefore, in this paper, the modeling and parameter estimation of the system using a real-coded genetic algorithm(RCGA) is proposed and a backward path tracking control algorithm is then obtained based on the linearized model. Experimental results verify the effectiveness of the proposed method.

• The Journal of Information Systems
• /
• v.32 no.4
• /
• pp.211-227
• /
• 2023

Purpose In the contemporary landscape, marked by the enduring impact of COVID-19 and the recent disruptions stemming from the conflict in Ukraine, the purpose of this study is to navigate the era characterized by pervasive risk and uncertainty. Specifically, the study aims to dissect the impact of the COVID-19 outbreak on digital transformation, exploring the factors influencing this process and considering the multifaceted dynamics at play. The focus extends to the post-COVID-19 landscape, scrutinizing the implications and meanings of digital transformation both before and after the pandemic. Additionally, the study delves into future digital trends, with particular attention to climate and environmental issues, emphasizing corporate responsibilities in averting crises similar to COVID-19. The overarching goal is to provide a holistic perspective, shedding light on both positive and negative facets of digital transformation, and advocating for regulatory enhancements and legal frameworks conducive to a balanced and resilient digital future. Design/methodology/approach This study employs a comprehensive approach to analyze the impact of the COVID-19 outbreak on digital transformation. It considers various facets, such as smart devices reshaping daily routines, transformative changes in corporate ecosystems, and the adaptation of government institutions to the digital era within the broader context of the Fourth Industrial Revolution. The analysis extends to the post-COVID-19 landscape, examining the implications and meanings of digital transformation. Future digital trends, especially those related to climate and environmental issues, are prognosticated. The methodology involves a proactive exploration of challenges associated with digital transformation, aiming to advocate for regulatory enhancements and legal frameworks that contribute to a balanced and resilient digital future. Findings The findings of this study reveal that the digital economy has gained momentum, accelerated by the proliferation of non-face-to-face industries in response to social distancing imperatives during the COVID-19 pandemic. Digital transformation, both preceding and succeeding the onset of the pandemic, has precipitated noteworthy shifts in various aspects of daily life. However, challenges persist, and the study highlights factors that either bolster or hinder the transformative process. In the post-COVID-19 era, corporate responsibilities in averting crises, particularly those resembling the pandemic, take center stage. The study emphasizes the need for a holistic perspective, acknowledging both positive and negative facets of digital transformation. Additionally, it calls for proactive measures, including regulatory enhancements and legal frameworks, to ensure a balanced and resilient digital future.