• Journal of Environmental Science International
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• v.26 no.10
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• pp.1185-1200
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• 2017

Solid waste management is currently a topic of concern, particularly in the protection of humans and the environment from toxic pollutants and hazardous materials. The importance of solid waste management is recognized at international, national, and community levels. Different agendas have been prioritized and assigned to improve quality of life, productivity, and health, and reduce the burden of pollution. Suitable management of solid waste requires appropriate technology that is affordable, socially accepted, and environmentally friendly. The use of a smart management system involving system dynamics can save energy, money, and labor. System dynamics is a computer-based approach that aids in predicting the behavioral patterns of variables, and correlating dependent and independent variables. The inclusion of system dynamics-based models in solid waste management has recently become more common. In this review, we used system dynamics to determine methods to disentangle solid waste management systems and analyzed different studies on solid waste management using system dynamics in different countries in detail. We also discussed the various software packages that are available for system dynamics and their usefulness for waste management. This review may help in understanding current solid waste management practices using system dynamics.

• Structural Engineering and Mechanics
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• v.42 no.6
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• pp.815-829
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• 2012

This paper proposes a nonlinear computational modeling approach for the behaviors of structural systems subjected to fire. The proposed modeling approach consists of fire dynamics analysis, nonlinear transient-heat transfer analysis for predicting thermal distributions, and thermomechanical analysis for structural behaviors. For concretes, transient heat formulations are written considering temperature dependent heat conduction and specific heat capacity and included within the thermomechanical analyses. Also, temperature dependent stress-strain behaviors including compression hardening and tension softening effects are implemented within the analyses. The proposed modeling technique for transient heat and thermomechanical analyses is first validated with experimental data of reinforced concrete (RC) beams subjected to high temperatures, and then applied to a bridge model. The bridge model is generated to simulate the fire incident occurred by a gas truck on April 29, 2007 in Oakland California, USA. From the simulation, not only temperature distributions and deformations of the bridge can be found, but critical locations and time frame where collapse occurs can be predicted. The analytical results from the simulation are qualitatively compared with the real incident and show good agreements.

• Proceedings of the Korean Fiber Society Conference
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• 2000.04a
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• pp.311-314
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• 2000

• Proceedings of the Membrane Society of Korea Conference
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• 2000.04a
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• pp.35-37
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• 2000

• Proceedings of the Korean Magnestics Society Conference
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• 2008.12a
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• pp.138.1-138.1
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• 2008

• Journal of Korean Society on Water Environment
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• v.24 no.3
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• pp.365-377
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• 2008

Large artificial dam reservoirs and associated downstream ecosystems are under increased pressure from long-term negative impacts of turbid flood runoff. Despite various emerging issues of reservoir turbidity flow, turbidity modeling studies have been rare due to lack of experimental data that can support scientific interpretation. Modeling suspended sediment (SS) dynamics, and therefore turbidity ($C_T$), requires provision of constitutive relationships ($SS-C_T$) and accounting for deposition of different SS size fractions/types distribution in order to display this complicated dynamic behavior. This study explored the performance of a coupled two-dimensional (2D) hydrodynamic and particle dynamics model that simulates the fate and transport of a turbid density flow in a negatively buoyant density flow regime. Multiple groups of suspended sediment (SS), classified by the particle size and their site-specific $SS-C_T$ relationships, were used for the conversion between field measurements ($C_T$) and model state variables (SS). The 2D model showed, in overall, good performance in reproducing the reservoir thermal structure, flood propagation dynamics and the magnitude and distribution of turbidity in the stratified reservoir. Some significant errors were noticed in the transitional zone due to the inherent lateral averaging assumption of the 2D hydrodynamic model, and in the lacustrine zone possibly due to long-term decay of particulate organic matters induced during flood runoffs.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.341-344
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• 1997

This paper presents a dynamics failure detection algorithm developed for the two-motor-driven electric vehicle system. The algorithm is based on the application of the fault detection filter. The fault detection includes the identification of sudden pressure drops of the two rear tires in driving axis and dynamics faults of the two inverter-motor-paired actuators An E.V. dynamics simulator is developed, which includes the modeling of the E.V. dynamics as well as the driving dynamics. The simulator, which allows the generation of various fault situations, is utilized in the verification of the developed fault detection algorithm. The results of the simulations are also presented.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.11a
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• pp.668-669
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• 2008

In this paper, we introduce various coarse-grained elastic network modeling (ENM) techniques as a novel computational method for simulating atomic scale dynamics in macromolecules including DNA, RNA, protein, and polymer. In ENM, a system is modeled as a spring network among representative atoms in which each linear elastic spring is well designed to replace both bonded and nonbonded interactions among atoms in the sense of quantum mechanics. Based on this simplified system, a harmonic Hookean potential is defined and used for not only calculating intrinsic vibration modes of a given system, but also predicting its anharmonic conformational change, both of which are strongly related with its functional features. Various nano and bio applications of ENM such as fracture mechanics of nanocomposite and protein dynamics show that ENM is one of promising tools for simulating atomic scale dynamics in a more effective and efficient way comparing to the traditional molecular dynamics simulation.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.8 no.1
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• pp.43-47
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• 2009

Recently, an approach for nano-scale material deformation has been developed that couples the atomistic and continuum approaches using Finite Element Method (FEM) and Molecular Dynamics (MD). However, this approach still has problems to connect two approaches because of the difference of basic assumptions, continuum and atomistic modeling. To solve this problem, an alternative way is developed that connects the QuasiMolecular Dynamics (QMD) and molecular dynamics. In this paper, we suggest the way to make and validate the MD-QMD coupled model.

• Korean System Dynamics Review
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• v.13 no.4
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• pp.57-80
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• 2012

This research studies effect of FDA regulations in pharmaceutical industry on new drug development. System dynamics is implemented to demonstrate dynamic relationship between FDA regulations and R&D costs, firm's profits, sales. This research is focused on clinical trials of new medical entity process 50~60% portion of total development cost. Simulation results say that firm's profit is more sensitive to increasing the regulation than alleviating the regulation and effect of regulation policy make different result depending on the intensity of regulation and policy direction. Our simulation model provides the instrumental means for the policy makers and strategic decision in pharmaceutical industry.