• Computers and Concrete
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• v.24 no.4
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• pp.313-327
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• 2019

The purpose of the present study is to present a new approach to designing and selecting the details of multidimensional continuous RC beam by applying all strength, serviceability, ductility and other constraints based on ACI318-14 using Teaching Learning Based Optimization (TLBO) algorithm. The optimum reinforcement detailing of longitudinal bars is done in two steps. in the first stage, only the dimensions of the beam in each span are considered as the variables of the optimization algorithm. in the second stage, the optimal design of the longitudinal bars of the beam is made according to the first step inputs. In the optimum shear reinforcement, using gradient-based methods, the most optimal possible mode is selected based on the existing assumptions. The objective function in this study is a cost function that includes the cost of concrete, formwork and reinforcing steel bars. The steel used in the objective function is the sum of longitudinal and shear bars. The use of a catalog list consisting of all existing patterns of longitudinal bars based on the minimum rules of the regulation in the second stage, leads to a sharp reduction in the volume of calculations and the achievement of the best solution. Three example with varying degrees of complexity, have been selected in order to investigate the optimal design of the longitudinal and shear reinforcement of continuous beam.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.12
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• pp.3236-3245
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• 1994

The nesting of two-dimensional patterns onto a given raw sheet has applications in a number industries. It is a common problem often faced by designers in the shipbuilding, garment making, blanking die design, glass and wood industries. This paper presents a multi-stage layout approach for nesting two-dimensional patterns by using artificial intelligence techniques with a relatively short computation time. The raw material with irregular boundaries and internal defects which must be considered in various cases of nesting was also investigated in this study. The proposed nesting approach consists of two stages : initial layout stage and layout improvement stage. The initial layout configuration is achieved by the self-organizing assisted layout(SOAL) algorithm while in the layout improvement stage, the simulated annealing(SA) is adopted for a finer optimization.

• Proceedings of the KIEE Conference
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• 1998.07c
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• pp.926-928
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• 1998

A fast optimization algorithm has been evolved from a simple two stage optimal power flow(OPF) algorithm for constrained power economic dispatch. In the proposed algorithm, we consider various constraints such as power balance, generation capacity, transmission line capacity, transmission losses, security equality, and security inequality constraints. The proposed algorithm consists of four stages. At the first stage, we solve the aggregated problem that is the crude classical economic dispatch problem without considering transmission losses. An initial solution is obtained by the aggregation concept in which the solution satisfies the power balance equations and generation capacity constraints. Then, after load flow analysis, the transmission losses of an initial generation setting are matched by the slack bus generator that produces power with the cheapest cost. At the second stage we consider transmission losses. Formulation of the second stage becomes classical economic dispatch problem involving the transmission losses, which are distributed to all generators. Once a feasible solution is obtained from the second stage, transmission capacity and other violations are checked and corrected locally and quickly at the third stage. The fourth stage fine tunes the solution of the third stage to reach a real minimum. The proposed approach speeds up the coupled LP based OPF method to an average gain of 53.13 for IEEE 30, 57, and 118 bus systems and EPRI Scenario systems A through D testings.

• Transactions of the Korean Society of Automotive Engineers
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• v.18 no.6
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• pp.114-121
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• 2010

This paper presents a design process of light-weighted fuel cell vehicle (FCV) frame to meet design target of natural frequency in early design stage. At first, using validated FE model for the current design, thickness optimization was carried out. Next. optimization process, comprised of beam model size optimization, shell model design and shell model thickness optimization, was investigated for two frame types. In addition, in order to ensure hydrogen tanks safety against rear impact load, structural collapse characteristics was estimated for the rear frame model finally produced from the previous optimization process and, with the target of equal collapse characteristics to the current design model, structural modification with small weight increase was studied through static structural collapse analyses. The same attempt was applied to the front side frame. The results explain that the proposed process enables to design light-weighted frames with high structural performance in early stage.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.413-418
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• 1991

Two methods are applied to the problem of trajectory optimization for launch vehicles which burn solid propellant. One is 'Optimal Control' theory, the other is 'NonLinear Programming' method. Trajectory optimization for solid rocket motors has a special problem. The special problem is that the payload of launch vehicle is not the function of control variable. This paper deals with this special problem.

• Clean Technology
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• v.22 no.4
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• pp.225-231
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• 2016

In this study, modeling and optimization study have been performed to obtain $1,524.58kg\;h^{-1}$ of a solidified NaCl by evaporating a 21.0 wt% of NaCl aqueous solution in order to reduce the steam consumption from $3,139kg\;h^{-1}$ to $496kg\;h^{-1}$ using a two-stage evaporation and a vapor recompression processes. Aspen Plus release 8.8 at AspenTech was utilized for the modeling of two stage evaporation process and PRO/II with PROVISION release 9.4 at Schneider Electric was also used for the simulation of two-stage vapor recompression process with an inter-cooler. For the simulation of the evaporation process containing NaCl aqueous solution, Aspen Plus release 8.8 at AspenTech Inc. was utilized and for the modeling of vapor recompression process PRO/II with PROVISION release at Schneider Electric Inc. For the vapor recompression process, single stage compression and two-stage compression system was compared.

• Korean Journal of Optics and Photonics
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• v.20 no.6
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• pp.319-327
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• 2009

We introduce a new design technique by treating a two-group zoom lens system with a wide angle of view. First, the concept of the global optimization is introduced in the initial design stage, and from this, the global design technique is completed by analyzing and summarizing large quantities of modern design data. That is, we define the global structure function to achieve a new conceptual design technique for global optimization. And the function is put in a simple form by referring lots of patent data, manipulated with other algebraic equations, and solved finally such that we obtain the global solution region. The global solution region corresponds to the global optimization and suggests insightful systematized directions for the design of two-group zoom lens systems. These directions are attractive compared to global optimization.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.11
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• pp.4355-4371
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• 2020

Phase retrieval, recovering a signal from phaseless measurements, is generally considered to be an NP-hard problem. This paper adopts an amplitude-based nonconvex optimization cost function to develop a new stochastic gradient algorithm, named stochastic reweighted phase retrieval (SRPR). SRPR is a stochastic gradient iteration algorithm, which runs in two stages: First, we use a truncated sample stochastic variance reduction algorithm to initialize the objective function. The second stage is the gradient refinement stage, which uses continuous updating of the amplitude-based stochastic weighted gradient algorithm to improve the initial estimate. Because of the stochastic method, each iteration of the two stages of SRPR involves only one equation. Therefore, SRPR is simple, scalable, and fast. Compared with the state-of-the-art phase retrieval algorithm, simulation results show that SRPR has a faster convergence speed and fewer magnitude-only measurements required to reconstruct the signal, under the real- or complex- cases.

• Proceedings of the IEEK Conference
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• 2003.07d
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• pp.1515-1518
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• 2003

This paper suggests the condensed two-stage retrieval method for fast image retrieval in the content-based image retrieval system, and proves the validity of the performance. The condensed two-stage retrieval method reduces the overall response time remarkably while it maintains relevance with the conventional exhaustive search method. It is explained by properties of the Cauchy-Schwartz inequality. In experimental result, it turns out that there is an optimal value of condensation ratio which minimizes the overall response time. We analyze the optimal condensation ratio by modeling a similarity computation time mathematically.

• International conference on construction engineering and project management
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• 2007.03a
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• pp.777-786
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• 2007

This paper presents a modified simulated annealing algorithm to optimize linear scheduling projects with multiple resource constraints and its effectiveness is verified with a proposed problem. A two-stage solution-finding procedure is used to model the problem. Then the simulated annealing and the modified simulated annealing are compared in the same condition. The comparison results and the reasons of improvement by the modified simulated annealing are presented at the end.