• The KSFM Journal of Fluid Machinery
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• v.4 no.1 s.10
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• pp.7-13
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• 2001

In developing a multistage compressor, the stage matching is one of the critical design issues. The mismatching can be often observed even if each stage has been proven good and then used as part of a compression system. A good matching among the stages can be achieved by changing various design parameters (i.e., passage cross sectional areas, blades angles, stagger angles, curvature, solidity, etc.). Therefore, designers need to find out what parameters must be changed and how much. In this study, a method to search the design parameters for optimum stage matching has been used based on an 1-D mathematical model of a compressor, which uses the data obtained from the preliminary test to identify the design parameters. This methodology is applied with a two-stage axial compressor, which was originally designed for a helicopter gas turbine engine. After identifying design parameters using preliminary test data, an optimization process has been employed to achieve the best matching between the stages (i.e., maximum efficiency of the compressor at its operation modes within a given range of the rotor speed under given restrictions for required stall margins and mass flow). 3-D flow calculations have been performed to confirm the usefulness of the corrections based on the 1-D mathematical model. Calculational results agree well with the experimental data in view of the performance characteristics. Some promising results were produced through the methodology proposed in this paper in conjunction with flow calculations.

• Journal of Korean Society for Quality Management
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• v.5 no.1
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• pp.23-29
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• 1977

Geometric programming is very useful for the solution of certain nonlinear programming problems in which the objective function and the constraints are posynomial expressions. By solving the dual program, it can be obtained that the solution of the primal program of Geometric programming. And, more efficient solution is to form an Augmented program possessing degree of difficult zero. A regional water-quality management problem may involve a multistage constrained optimization with many decision variables. In this problem, especially, appling that solution to it is also useful. This paper is described that : 1) the efficient solution of a water-quality management model formed by Geometric programming and 2) the algorithm developed to apply easily a real system by modifing and simplifing the solution.

• Journal of the Korean Operations Research and Management Science Society
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• v.18 no.3
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• pp.13-34
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• 1993

By operating on many part of a software system concurrently, the parallel processing computers may provide several orders of magnitude more computing power than traditional serial computers. If the Lagrangean approximation procedure is applied to a large scale manufacturing problem which is decomposable into many subproblems, the procedure is a perfect candidate for parallel processing. By distributing Lagrangean subproblems for given multiplier to multiple processors, concurrently running processors and modifying Lagrangean multipliers at the end of each iteration of a subgradient method,a parallel processing of a Lagrangean approximation procedure may provide a significant speedup. This purpose of this research is to investigate the potential of the parallelized Lagrangean approximation procedure (PLAP) for certain combinational optimization problems in manufacturing systems. The framework of a Plap is proposed for some combinatorial manufacturing problems which are decomposable into well-structured subproblems. The synchronous PLAP for the multistage dynamic lot-sizing problem is implemented on a parallel computer Alliant FX/4 and its computational experience is reported as a promising application of vector-concurrent computing.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.5
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• pp.407-412
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• 2003

An effective methodology is .reported for determining the optimal capacity (lot-size) of batch processing and storage networks which include material recycle or reprocessing streams. We assume that any given storage unit can store one material type which can be purchased from suppliers, be internally produced, internally consumed and/or sold to customers. We further assume that a storage unit is connected to all processing stages that use or produce the material to which that storage unit is dedicated. Each processing stage transforms a set of feedstock materials or intermediates into a set of products with constant conversion factors. The objective for optimization is to minimize the total cost composed of raw material procurement, setup and inventory holding costs as well as the capital costs of processing stages and storage units. A novel production and inventory analysis formulation, the PSW(Periodic Square Wave) model, provides useful expressions for the upper/lower bounds and average level of the storage inventory hold-up. The expressions for the Kuhn-Tucker conditions of the optimization problem can be reduced to two subproblems. The first yields analytical solutions for determining batch sizes while the second is a separable concave minimization network flow subproblem whose solution yields the average material flow rates through the networks. For the special case in which the number of storage is equal to the number of process stages and raw materials storage units, a complete analytical solution for average flow rates can be derived. The analytical solution for the multistage, strictly sequential batch-storage network case can also be obtained via this approach. The principal contribution of this study is thus the generalization and the extension to non-sequential networks with recycle streams. An illustrative example is presented to demonstrate the results obtainable using this approach.

• Journal of Power Electronics
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• v.16 no.4
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• pp.1396-1406
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• 2016

A novel controller design is presented for the recently proposed electric springs (ESs). The dynamic modeling is analyzed first, and the initial Bode diagram is derived from the s-domain transfer function in the open loop. The design objective is set according to the characteristics of a minimum phase system. Step-by-step optimizations of the Bode diagram are provided to illustrate the proposed controller, the design of which is different from the classical multistage leading/lagging design. The final controller is the accumulation of the transfer function at each step. With the controller and the recently proposed δ control, the critical load voltage can be regulated to follow the desired waveform precisely while the fluctuations and distortions of the input voltage are passed to the non-critical loads. Frequency responses at any point can be modified in the Bode diagram. The results of the modeling and controller design are validated via simulations. Hardware and software designs are provided. A digital phase locked loop is realized with the platform of a digital signal processor. The effectiveness of the proposed control is also validated by experimental results.

• Industrial Engineering and Management Systems
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• v.12 no.2
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• pp.74-84
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• 2013

Modern companies have been facing devastating impacts from unexpected events such as demand uncertainties, natural disasters, and terrorist attacks due to the increasing global supply chain complexity. This paper proposes a multi stage logistic network model under disruption risk. To formulate the problem practically, we consider the effect of continuity rate, which is defined as a percentage of ability of the facility to provide backup allocation to customers in the abnormal situation and affect the investments and operational costs. Then we vary the fixed charge for opening facilities and the operational cost according to the continuity rate. The operational level of the company decreases below the normal condition when disruption occurs. The backup source after the disrup-tion is recovered not only as soon as possible, but also as much as possible. This is a concept of the business continuity plan to reduce the recovery time objective such a continuity rate will affect the investments and op-erational costs. Through numerical experiments, we have shown the proposed idea is capable of designing a resilient logistic network available for business continuity management/plan.

• Membrane and Water Treatment
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• v.8 no.3
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• pp.279-292
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• 2017

This study was aimed at ultrafiltration (UF) as a pretreatment before reverse osmosis (RO) within the scheme of hybrid reverse osmosis-multistage flush (RO-MSF) desalination. Seawater at elevated temperature (after MSF heat-exchangers) was used as a feed in this process. The pretreatment system was represented as a set of functionally-linked technological segments such as: UF filtration, backwashing, chemical- enhanced backwashing, cleaning, waste disposal, etc. The process represents the sequences of operating cycles. The cycle, in turn, consists of the following unit operations: filtration, backwashing and chemical-enhanced backwashing (CEB). Quantitative assessment was based on the following indicators: normalized permeability, transmembrane pressure, specific energy and water consumption, specific waste generation. UF pre-treatment is accompanied by the following waste streams: $W1=1.19{\times}10$ power of $-2m^3$ (disposed NaOCl with 0.0044% wt.)/$m^3$ (filtrate); $W2=5.95{\times}10$ power of $-3m^3$ (disposed $H_2SO_4$ with 0.052% wt.)/$m^3$(filtrate); $W3=7.26{\times}10$ power of $-2m^3$ (disposed sea water)/$m^3$ (filtrate). Specific energy consumption is $1.11{\times}10$ power of $-1kWh/m^3$ (filtrate). The indicators evaluated over the cycles with conventional (non-chemical) backwashing were compared with the cycles accompanied by CEB. A positive impact of CEB on performance indicators was demonstrated namely: normalized UF resistance remains unchanged within the regime accompanied by CEB, whereas the lack of CEB results in 30% of its growth. Those quantitative indicators can be incorporated into the target function for solving different optimization problems. They can be used in the software for optimisation of operating regimes or in the synthesis of optimal flow- diagram. The cycle characteristics, process parameters and water quality data are attached.