• Proceedings of the Korean Powder Metallurgy Institute Conference
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• 2006.09a
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• pp.189-190
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• 2006

During cold compaction processes loose powder is pressed under tooling action in order to produce complex shaped engineering components. Here, the analysis of the plastic deformation of granular packings is of fundamental importance to the development of computer simulation models. Powders can be idealized by packing discrete particles, where each particle is a sphere meshed with finite elements. The pressing of a body centered cubic packing was compared with numerical prediction and experimental data. The global response was expressed in force-displacement curve, and the accuracy of the numerical models analyzed for high relative densities up to 0.95.

• IE interfaces
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• v.2 no.2
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• pp.51-62
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• 1989

A computer-aided simulation modeling system has been developed to allow the automatic construction of complete discrete simulation models for queueing systems. Three types of knowledge are used in the specification and construction of a simulation modeling: Knowledge of queueing system, simulation modeling, and a target simulation language. This knowledge has been incorporated into the underlying rule base in the form of extraction and construction rule, and implemented via the expert system building tool, OPS5. This paper suggested a knowledge based approach for automatic programming to enable a user who lacks modeling knowledge and simulation language expertize to quickly build executable models.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.409-414
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• 2005

In the literatures, the FFT-based SAM has been well applied to the computation of the steady-state responses of discrete dynamic systems. In this paper, a fast fourier transforms (FFT)-based spectral analysis method (SAM) is proposed fur the dynamic analysis of spectral element models subjected to the non-zero initial conditions. However, the FFT-based SAM has not yet been developed for the continuous systems represented by the spectral element model.

• Proceedings of the Korea Society for Simulation Conference
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• 2001.10a
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• pp.425-434
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• 2001

In this paper we introduce a general framework for the modeling, analysis and costing of logistic networks including supply chains (SCs). The employed modeling notation, the so-called Process Chain paradigm, is specifically developed for the application field of logistic networks which includes SCs. We view SCs as discrete event dynamic systems (DEDS) and apply corresponding simulative techniques in order to derive performance measures of the Process Chain model under investigation. For this purpose Process Chain models are automatically transformed into the input language of the simulation tool HIT. Subsequently, a cost accounting model using the performance measures is applied to obtain costs which are actually subject of interest. The usefulness and applicability of the approach is illustrated by a typical supply chain example. We investigate the impact of an additional SC channel between a manufacturer and web-consumers on the overall supply chain costs.

• Journal of Korean Society of Transportation
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• v.26 no.1
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• pp.145-153
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• 2008

Existing shortest-path algorithms mainly consider a single attribute. But traveler actually chooses a route considering not single attribute but various attributes which are synthesized travel time, route length, personal preference, etc. Therefore, to search the optimal path, these attributes are considered synthetically. In this study route searching algorithm which selects the maximum utility route using discrete choice model has developed in order to consider various attributes. Six elements which affect route choice are chosen for the route choice model and parameters of the models are estimated using survey data. A multinomial logit models are developed to design the function of route choice model. As a result, the model which has route length, delay time, the number of turning as parameter is selected based on the significance test. We use existing shortest path algorithm, which can reflect urban transportation network such as u-turn or p-turn, and apply it to the real network.

• Smart Structures and Systems
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• v.14 no.1
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• pp.39-54
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• 2014

Node layout optimization of structural wireless systems is investigated as a means to prolong the network lifetime without, if possible, compromising information quality of the measurement data. The trade-off between these antagonistic objectives is studied within a multi-objective layout optimization framework. A Genetic Algorithm is adopted to obtain a set of Pareto-optimal solutions from which the end user can select the final layout. The information quality of the measurement data collected from a heterogeneous WSN is quantified from the placement quality indicators of strain and acceleration sensors. The network lifetime or equivalently the network energy consumption is estimated through WSN simulation that provides realistic results by capturing the dynamics of the wireless communication protocols. A layout optimization study of a monitoring system on the Great Belt Bridge is conducted to evaluate the proposed approach. The placement quality of strain gauges and accelerometers is obtained as a ratio of the Modal Clarity Index and Mode Shape Expansion values that are computed from a Finite Element model of the monitored bridge. To estimate the energy consumption of the WSN platform in a realistic scenario, we use a discrete-event simulator with stochastic communication models. Finally, we compare the optimization results with those obtained in a previous work where the network energy consumption is obtained via deterministic communication models.

• Journal of the Korea Institute of Military Science and Technology
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• v.17 no.2
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• pp.235-247
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• 2014

Based on two dimensional model partition method proposed in Part 1, Part 2 provides detailed model specification and implementation. To mathematically delineate a model's behaviors and interactions among them, we extend the DEVS (Discrete Event Systems Specification) formalism and newly propose CE-DEVS (Combat Entity-DEVS) for an upper abstraction sub-model of a combat entity model. The proposed CE-DEVS additionally define two sets and one function to reflect essential semantics for the model's behaviors explicitly. These definitions enable us to understand and represent the model's behaviors easily since they eliminate differences of meaning between real-world expressions and model specifications. For model implementation, upper abstraction sub-models are implemented with DEVSim++, while the lower sub-models are realized using the C++ language. With the use of overall modeling techniques proposed in Part 1 and 2, we can conduct constructive simulation and assess factors about combat logics as well as battle field functions of the next-generation combat entity, minimizing additional modeling efforts. From the anti-torpedo warfare experiment, we can gain interesting experimental results regarding engagement situations employing developing weapons and their tactics. Finally, we expect that this work will serve an immediate application for various engagement warfare.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.401-404
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• 2003

In this paper, $H_2$, $H_{\infty}$, and mixed $H_2/H_{\infty}$ FIR filters are newly proposed for discrete-time state space signal models. The proposed filters require linearity, unbiased property, FIR structure, and independence of the initial state information in addition to the performance criteria in both $H_2$ and $H_{\infty}$ sense. It is shown that $H_2$, $H_{\infty}$, and mixed $H_2/H_{\infty}$ FIR filter design problems can be converted into convex programming problems via linear matrix inequalities (LMIs) with a linear equality constraint. Simulation studies illustrat that the proposed FIR filter is more robust against uncertainties and has faster convergence than the conventional IIR filters. the conventional IIR filters.

• Nuclear Engineering and Technology
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• v.56 no.7
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• pp.2881-2892
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• 2024

Annular flow refers to a special type of two-phase flow pattern in which liquid flows as a thin film at the periphery of a pipe, tube, or conduit, and gas with relatively high velocity flows at the center of the flow section. This gas also includes dispersed liquid droplets. The liquid film flow rate continuously changes inside the tube due to two processes-entrainment and deposition. To determine the liquid holdup, pressure drop, the onset of dryout, and heat transfer characteristics in annular flow, it is important to have proper knowledge of flow characteristics. Especially a better understanding of entrainment fraction is important for the heat transfer and safe operation of two-phase flow systems operating in an annular two-phase flow regime. Therefore, the objective of this work is to develop a computational model for the simulation of the annular two-phase flow regime and assess the various existing models for the entrainment rate. In this work, Computational Fluid Dynamics (CFD) in ANSYS FLUENT has been applied to determine annular flow characteristics such as liquid film thickness, film velocity, entrainment rate, deposition rate, and entrainment fraction for various gas-liquid flow conditions in a vertical upward tube. The gas core with droplets was simulated using the Discrete Phase Model (DPM) which is based on the Eulerian-Lagrangian approach. The Eulerian Wall Film (EWF) model was utilized to simulate liquid film on the tube wall. Three different models of Entrainment rate were implemented and assessed through user-defined functions (UDF) in ANSYS. Finally, entrainment for fully developed flow was determined and compared with the experimental data available in the literature. From the simulations, it was obtained that the Bertodano correlation performed best in predicting entrainment fraction and the results were within the ±30 % limit when compared to experimental data.

• Smart Structures and Systems
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• v.16 no.6
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• pp.1107-1132
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• 2015

A damage detection algorithm based on neuro fuzzy hybrid system is presented in this study for location and severity predictions of cracks in beam-like structures. A combination of eigenfrequencies and rotation deviation curves are utilized as input to the soft computing technique. Both single and multiple damage cases are considered. Theoretical expressions leading to modal properties of damaged beam elements are provided. The beam formulation is based on Euler-Bernoulli theory. The cracked section of beam is simulated employing discrete spring model whose compliance is computed from stress intensity factors of fracture mechanics. A hybrid neuro fuzzy technique is utilized to solve the inverse problem of crack identification. Two different neuro fuzzy systems including grid partitioning (GP) and subtractive clustering (SC) are investigated for the highlighted problem. Several error metrics are utilized for evaluating the accuracy of the hybrid algorithms. The study is the first in terms of 1) using the two models of neuro fuzzy systems in crack detection and 2) considering multiple damages in beam elements employing the fused neuro fuzzy procedures. At the end of the study, the developed hybrid models are tested by utilizing the noise-contaminated data. Considering the robustness of the models, they can be employed as damage identification algorithms in health monitoring of beam-like structures.