• IE interfaces
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• v.25 no.2
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• pp.153-162
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• 2012

The reliability is defined as a probability that a system will operate properly for a specified period of time under the design operating conditions without failure and it has been considered as one of the major design parameters in the field of industries. Reliability-Redundancy Optimization Problem(RROP) involves selec tion of components with multiple choices and redundancy levels for maximizing system reliability with constraints such as cost, weight, etc. However, in practice both active and cold standby redundancies may be used within a particular system design. Therefore, a redundancy strategy(active, cold standby) for each subsystem in order to maximize system reliability is considered in this study. Due to the nature of RROP, i.e. NP-hard problem, A Parallel Particle Swarm Optimization(PPSO) algorithm is proposed to solve the mathematical programming model and it gives consistently better quality solutions than existing studies for benchmark problems.

• Journal of Applied Reliability
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• v.1 no.1
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• pp.1-8
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• 2001

Redundancy allocation problems have been considered at single-level systems and it may be the best policy in some specific situations, but not in general. With regards to reliability, it is most effective to allocate the lowest objects, because parallel-series systems are more reliable than series-parallel systems. However, the smaller and lower in the system an object is, the more time and accuracy are needed for duplicating it, and so, the cost can be decreased by using modular redundancy Therefore, providing redundancy at high levels like as modules or subsystems, can be more economical than providing redundancy at low levels or duplicating components. In this paper, the problem in which redundancy is allocated at all level in a series system is addressed, a mixed integer nonlinear programming model is presented and a genetic algorithm is proposed. An example illustrates the procedure.

• 한국전산유체공학회:학술대회논문집
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• 2004.03a
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• pp.172-177
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• 2004

In the present work, we have interests on the modification of parallel implemented with MPI(Message Passing Interface) programming method, 3-Dimensional, unsteady, incompressible Navier-Stokes equation solver to analyze the low-Reynolds number flow In order to accurate calculation aerodynamic coefficients in low-Reynolds number flow field, we modified the two-equation turbulence model. This paper describes the development and validation of a new two-equation model for the prediction of flow transition. It is based on Mentor's low Reynolds $\kappa-\omega$ model with modifications to include Total Stresses Limitation (TSL) and Separation Transition Trigger (STT)

• IE interfaces
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• v.23 no.2
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• pp.147-155
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• 2010

Reliability allocation is defined as a problem of determination of the reliability for subsystems and components to achieve target system reliability. The determination of both optimal component reliability and the number of component redundancy allowing mixed components to maximize the system reliability under resource constraints is called reliability-redundancy allocation problem(RAP). The main objective of this study is to suggest a mathematical programming model and a hybrid parallel genetic algorithm(HPGA) for reliability-redundancy allocation problem that decides both optimal component reliability and the number of component redundancy to maximize the system reliability under cost and weight constraints. The global optimal solutions of each example are obtained by using CPLEX 11.1. The component structure, reliability, cost, and weight were computed by using HPGA and compared the results of existing metaheuristic such as Genetic Algoritm(GA), Tabu Search(TS), Ant Colony Optimization(ACO), Immune Algorithm(IA) and also evaluated performance of HPGA. The result of suggested algorithm gives the same or better solutions when compared with existing algorithms, because the suggested algorithm could paratactically evolved by operating several sub-populations and improve solution through swap, 2-opt, and interchange processes. In order to calculate the improvement of reliability for existing studies and suggested algorithm, a maximum possible improvement(MPI) was applied in this study.

• Management Science and Financial Engineering
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• v.19 no.1
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• pp.29-36
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• 2013

This paper considers common due-date assignment and scheduling on parallel machines. The main decisions are: (a) deter-mining the common due-date; (b) allocating jobs to machines; and (c) sequencing the jobs assigned to each machine. The objective is to minimize the sum of the penalties associated with common due-date assignment, earliness and tardiness. As an extension of the existing studies on the problem, we consider sequence-dependent setup times that depend on the type of job just completed and on the job to be processed. The sequence-dependent setups, commonly found in various manufacturing systems, make the problem much more complicated. To represent the problem more clearly, a mixed integer programming model is suggested, and due to the complexity of the problem, two heuristics, one with individual sequence-dependent setup times and the other with aggregated sequence-dependent setup times, are suggested after analyzing the characteristics of the problem. Computational experiments were done on a number of test instances and the results are reported.

• Journal of Internet Computing and Services
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• v.15 no.2
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• pp.41-47
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• 2014

In this paper, we implemented a CUDA Fortran parallel program to run the CFD_NIMR model on GP-GPU's, which simulates air diffusion on urban terrains. A GP-GPU is graphic processing unit in the form of a PCI card, and a general calculation accelerator to perform a large amount of high speed calculations with low cost and electric power. The GP-GPU gives performance enhancement of speed by 15 times to compare the Nvidia Tesla C1060 GPU with Intel XEON 2.0 GHz CPU. In addition, the program on a GP-GPU shows efficient performance compared to an MPI parallel program on multiple CPU's. It is expected that a proposed programming method on the GP-GPU parallel program can be used for numerical models with a similar structure.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.30 no.4
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• pp.44-52
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• 2002

Aerodynamic characteristics of a flapping airfoil in low Reynolds number flows are numerically studied using the unsteady, incompressible Navier-Stokes flow solver with a two-equation turbulence model. For more efficient computation of unsteady flows over flapping airfoil, the flow solver is parallel-implemented by MPI programming method Unsteady computations are performed for low Reynolds number flows over a NACA four-digit series airfoils. Effects of pitching, plunging, and flapping motion with different reduced frequency, amplitude, thickness and camber on aerodynamic characteristics are investigated. Present computational results yield a better agreement in thrust at various reduced frequency with experimental data.

• Journal of Institute of Control, Robotics and Systems
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• v.6 no.5
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• pp.426-432
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• 2000

A novel mixed-integer linear programming model for the short-term scheduling of a sequential multipurpose batch plant is addressed. First, a time slot domain to each unit is introduced. By assigning each time slot to a product, we obtain the production sequence that minimizes makespan. For multiple-unit assignment problem where a few parallel units with the same function exist, production paths are defined for the distinction of the same stage with a different unit. As a second issue, the model adapted for sequence dependent changeover is presented. For a time slot of a unit, if a product is assigned to the time slot and a different product is assigned to the adjacent time slot, the changeover time considering this situation is included. The performance of the proposed models are illustrated through two examples.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.37 no.3
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• pp.307-312
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• 2013

The interest in reducing the emissions and increasing the fuel economy of ICE vehicles has prompted research on hybrid vehicles, which come in the series, parallel, and power-split types. This study focuses on the series-type hybrid electric vehicle, which has a simple structure. Because each component of a series hybrid vehicle is larger than the corresponding component of the parallel type, the sizing of the vehicle is very important. This is because the performance may be greater or less than what is required. Thus, in this research, the optimal fuel economy was determined and simulated in a real-world system. The optimal sizing was achieved based on the motor, engine/generator, and battery for 13 cycles, where DP was used. The model was developed using ASCET or a Simulink-Amisim Co-simulation platform on the rapid controller prototype, ES-1000.

• Geophysics and Geophysical Exploration
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• v.20 no.3
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• pp.129-136
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• 2017

3D seismic data processing methods such as full waveform inversion or reverse-time migration require 3D wave propagation modeling and heavy calculations. We compared efficiency and accuracy of a Xeon Phi coprocessor to those of a high-end server CPU using 3D frequency-domain wave propagation modeling. We adopted the OpenMP parallel programming to the time-domain finite difference algorithm by considering the characteristics of the Xeon Phi coprocessors. We applied the Fourier transform using a running-integration to obtain the frequency-domain wavefield. A numerical test on frequency-domain wavefield modeling was performed using the 3D SEG/EAGE salt velocity model. Consequently, we could obtain an accurate frequency-domain wavefield and attain a 1.44x speedup using the Xeon Phi coprocessor compared to the CPU.