• Geomechanics and Engineering
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• v.16 no.5
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• pp.495-501
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• 2018

Geogrid application that has proved to be an effective and economic method of reinforcing particles, is widely used in geotechnical engineering. The discrete element method (DEM) has been used to investigate the micro mechanics of the geogrid deformation and also the interlocking mechanism that cannot be easily studies in laboratory tests. Two types of realistically shaped geogrid models with square and triangle apertures were developed using parallel bonds in PFC3D. The calibration test simulations have demonstrated that the precisely shaped triangular geogrid model is also able to reproduce the deformation and strength characteristics of geogrids. Moreover, the square and triangular geogrid models were also used in DEM pull-out test simulations with idealized shape particle models for validation. The simulation results have been shown to provide good predictions of pullout force as a function of displacement especially for the initial 30 mm displacement. For the granular material of size 40 mm, both the experimental and DEM results demonstrate that the triangular geogrid of size 75 mm outperforms the square geogrid of size 65 mm. Besides, the simulations have given valuable insight into the interaction between particle and geogrid and also revealed similar deformation behavior of geogrids during pullout. Therefore, the DEM provides a tool which enable to model other possible prototype geogrid and investigate their performance before manufacture.

• Computers and Concrete
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• v.21 no.2
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• pp.189-197
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• 2018

A discrete element approach is used to investigate the effects of confining stress on the shear behaviour of joint's bridge area. A punch-through shear test is used to model the concrete cracks under different shear and confining stresses. Assuming a plane strain condition, special rectangular models are prepared with dimension of $75mm{\times}100mm$. Within the specimen model and near its four corners, four equally spaced vertical notches of the same depths are provided so that the central portion of the model remains intact. The lengths of notches are 35 mm. and these models are sequentially subjected to different confining pressures ranging from 2.5 to 15 MPa. The axial load is applied to the punch through the central portion of the model. This testing and models show that the failure process is mostly governed by the confining pressure. The shear strengths of the specimens are related to the fracture pattern and failure mechanism of the discontinuities. The shear behaviour of discontinuities is related to the number of induced shear bands which are increased by increasing the confining pressure while the cracks propagation lengths are decreased. The failure stress and the crack initiation stress both are increased due to confining pressure increase. As a whole, the mechanisms of brittle shear failure changes to that of the progressive failure by increasing the confining pressure.

• Proceedings of the Korean Society of Computational and Applied Mathematics Conference
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• 2003.09a
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• pp.1-1
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• 2003

In this talk, a reduced-order modeling methodology based on centroidal Voronoi tessellations (CVT's)is introduced. CVT's are special Voronoi tessellations for which the generators of the Voronoi diagram are also the centers of mass (means) of the corresponding Voronoi cells. The discrete data sets, CVT's are closely related to the h-means clustering techniques. Even with the use of good mesh generators, discretization schemes, and solution algorithms, the computational simulation of complex, turbulent, or chaotic systems still remains a formidable endeavor. For example, typical finite element codes may require many thousands of degrees of freedom for the accurate simulation of fluid flows. The situation is even worse for optimization problems for which multiple solutions of the complex state system are usually required or in feedback control problems for which real-time solutions of the complex state system are needed. There hava been many studies devoted to the development, testing, and use of reduced-order models for complex systems such as unsteady fluid flows. The types of reduced-ordered models that we study are those attempt to determine accurate approximate solutions of a complex system using very few degrees of freedom. To do so, such models have to use basis functions that are in some way intimately connected to the problem being approximated. Once a very low-dimensional reduced basis has been determined, one can employ it to solve the complex system by applying, e.g., a Galerkin method. In general, reduced bases are globally supported so that the discrete systems are dense; however, if the reduced basis is of very low dimension, one does not care about the lack of sparsity in the discrete system. A discussion of reduced-ordering modeling for complex systems such as fluid flows is given to provide a context for the application of reduced-order bases. Then, detailed descriptions of CVT-based reduced-order bases and how they can be constructed of complex systems are given. Subsequently, some concrete incompressible flow examples are used to illustrate the construction and use of CVT-based reduced-order bases. The CVT-based reduced-order modeling methodology is shown to be effective for these examples and is also shown to be inexpensive to apply compared to other reduced-order methods.

• Korean Journal of Ecology and Environment
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• v.46 no.1
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• pp.1-9
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• 2013

Algal blooms in potable water supplies are becoming an increasingly prevalent and serious water quality problem around the world. In addition to precipitating taste and odor problems, blooms damage the environment, and some classes like cyanobacteria (blue-green algae) release toxins that can threaten human health, even causing death. There is a recognized need in the water industry for models that can accurately forecast in real-time algal bloom events for planning and mitigation purposes. In this study, using data for an interconnected system of rivers and reservoirs operated by a New Jersey water utility, various ANN models, including both discrete prediction and classification models, were developed and tested for forecasting counts of three different algal classes for one-week and two-weeks ahead periods. Predictor model inputs included physical, meteorological, chemical, and biological variables, and two different temporal schemes for processing inputs relative to the prediction event were used. Despite relatively limited historical data, the discrete prediction ANN models generally performed well during validation, achieving relatively high correlation coefficients, and often predicting the formation and dissipation of high algae count periods. The ANN classification models also performed well, with average classification percentages averaging 94 percent accuracy. Despite relatively limited data events, this study demonstrates that with adequate data collection, both in terms of the number of historical events and availability of important predictor variables, ANNs can provide accurate real-time forecasts of algal population counts, as well as foster increased understanding of important cause and effect relationships, which can be used to both improve monitoring programs and forecasting efforts.

• Smart Structures and Systems
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• v.25 no.5
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• pp.569-580
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• 2020

The identification of delays and delay compensation are critical problems in real-time hybrid simulations (RTHS). Conventional delay compensation methods are mostly based on the assumption of a constant delay. However, the system delay may vary during tests owing to the nonlinearity of the loading system and/or the behavioral variations of the specimen. To address this issue, this study presents an adaptive delay compensation method based on a discrete model of the loading system. In particular, the parameters of this discrete model are identified and updated online with the least-squares method to represent a servo hydraulic loading system. Furthermore, based on this model, the system delays are compensated for by generating system commands using the desired displacements, achieved displacements, and previous displacement commands. This method is more general than the existing compensation methods because it can predict commands based on multiple displacement categories. Moreover, this method is straightforward and suitable for implementation on digital signal processing boards because it relies solely on the displacements rather than on velocity and/or acceleration data. The virtual and real RTHS results show that the studied method exhibits satisfactory estimation smoothness and compensation accuracy. Furthermore, considering the measurement noise, the low-order parameter models of this method are more favorable than that the high-order parameter models.

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

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.6
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• pp.33-43
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• 2021

A60 class bulkhead penetration piece is a fire resistance system installed on a bulkhead compartment to protect lives and to prevent flame diffusion in a fire accident on a ship and offshore plant. This study focuses on the approximate optimization of the fire resistance design of the A60 class bulkhead penetration piece using a multi-island genetic algorithm. Transient heat transfer analysis was performed to evaluate the fire resistance design of the A60 class bulkhead penetration piece. For approximate optimization, the bulkhead penetration piece length, diameter, material type, and insulation density were considered discrete design variables; moreover, temperature, cost, and productivity were considered constraint functions. The approximate optimum design problem based on the meta-model was formulated by determining the discrete design variables by minimizing the weight of the A60 class bulkhead penetration piece subject to the constraint functions. The meta-models used for the approximate optimization were the Kriging model, response surface method, and radial basis function-based neural network. The results from the approximate optimization were compared to the actual results of the analysis to determine approximate accuracy. We conclude that the radial basis function-based neural network among the meta-models used in the approximate optimization generates the most accurate optimum design results for the fire resistance design of the A60 class bulkhead penetration piece.

• International Journal of Highway Engineering
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• v.15 no.5
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• pp.31-45
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• 2013

PURPOSES : Determination of particle packing model variables that can be used for formulation of new DEM based particle packing model by examining existing particle packing models METHODS : Existing particle packing models are thoroughly examined by analytical reformulation and sensitivity analysis in order to set up DEM based new particle packing model and to determine its variables. All model equations considered in this examination are represented with consistent expressions and are compared to each others to find mathematical and conceptual similarity in expressions. RESULTS : From the examination of existing models, it is observed that the models are very similar in their shapes although the derivation of the models may be different. As well, it is observed that variables used in some existing models are comprehensive enough to estimate particle packing but not applicable to DEM simulation. CONCLUSIONS : A set of variables that can be used in DEM based particle packing model is determined.

• Journal of the Korea Society for Simulation
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• v.18 no.4
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• pp.127-136
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• 2009

Modeling and Simulation, especially in mobile ad hoc network(MANET), are the most effective way to analyze performance or optimize system parameters without establishing real network environment. Focusing mainly on overall network behaviors in MANET concerns dynamics of network transport operations, which can efficiently be characterized with event based system states rather than execution details of protocols. We thus consider the network as a discrete event system to analyze dynamics of network transport performance. Zeigler's set-theoretic DEVS(Discrete Event Systems Specification) formalism can support specification of a discrete event system in hierarchical, modular manner. The DEVSim++ simulation environment can not only provide a rigorous modeling methodology based on the DEVS formalism but also support modelers to develop discrete event models using the hierarchical composition methodology in object-orientation. This environment however hardly supports to specify connection paths of network nodes, which are continuously altered due to mobility of nodes. This paper proposes a DEVS-based modeling and simulation methodology of enabling node mobility, and develops DEVS models for the mobile ad hoc network. We also simulate developed models with the DEVSim++ engine to verify the proposal.

• Structural Engineering and Mechanics
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• v.52 no.2
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• pp.369-389
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• 2014

Two-layer coupled or composite beams with discrete shear connectors of finite dimensions are commonly encountered in pre-fabricated construction. This paper presents the development of simplified closed-form solutions for such type of coupled beams for practical applications. A new coupled beam element is proposed to represent the unconnected segments in the beam. General solutions are then developed by an inductive method based on the results from the finite element analysis. A modification is subsequently considered to account for the effect of local deformations. For typical cases where the local deformation is primarily concerned about its distribution over the depth of the coupled beam, empirical modification factors are developed based on parametric calculations using finite element models. The developed analytical method for the coupled beams in question is simple, sufficiently accurate, and suitable for quick calculation in engineering practice.