• Structural Engineering and Mechanics
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• v.86 no.3
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• pp.337-348
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• 2023

The optimization of reinforced concrete (RC) cantilever retaining walls is a complex problem and requires the use of advanced techniques like metaheuristic algorithms. For this purpose, an optimization model must first be developed, which involves mathematical complications, multidisciplinary knowledge, and programming skills. This task has proven to be too arduous and has halted the mainstream acceptance of optimization. Therefore, it is necessary to unravel the complications of optimization into an easily applicable form. Currently, the most commonly used method for designing retaining walls is by following the proportioning limits provided by the ACI handbook. However, these limits, derived manually, are not verified by any optimization technique. There is a need to validate or modify these limits, using optimization algorithms to consider them as optimal limits. Therefore, this study aims to propose updated proportioning limits for the economical design of a RC cantilever retaining wall through a comprehensive parametric investigation using the genetic algorithm (GA). Multiple simulations are run to examine various design parameters, and trends are drawn to determine effective ranges. The optimal limits are derived for 5 geometric and 3 reinforcement variables and validated by comparison with their predecessor, ACI's preliminary proportioning limits. The results indicate close proximity between the optimized and code-provided ranges; however, the use of optimal limits can lead to additional cost optimization. Modifications to achieve further optimization are also discussed. Besides the geometric variables, other design parameters not covered by the ACI building code, like reinforcement ratios, bar diameters, and material strengths, and their effects on cost optimization, are also discussed. The findings of this investigation can be used by experienced engineers to refine their designs, without delving into the complexities of optimization.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2008.04a
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• pp.416-421
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• 2008

A Metropolis genetic algorithm (MGA) is a newly-developed hybrid algorithm combining simple genetic algorithm (SGA) and simulated annealing (SA). In the algorithm, favorable features of Metropolis criterion of SA are incorporated in the reproduction operations of SGA. This way, MGA alleviates the disadvantages of finding imprecise solution in SGA and time-consuming computation in SA. It has been successfully applied and the efficiency has been verified for the practical structural design optimization. However, applicability of MGA for the wider range of problems should be rigorously proved through the solution of mathematical optimization problems. Thus, performances of MGA for the typical mathematical problems are investigated and compared with those of conventional algorithms such as SGA, micro genetic algorithm (${\mu}GA$), and SA. And, for better application of MGA, the effects of acceptance level are also presented. From numerical Study, it is again verified that MGA is more efficient and robust than SA, SGA and ${\mu}GA$ in the solution of mathematical optimization problems having various features.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.14 no.2
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• pp.14-20
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• 2005

This paper describes a dwell time calculation algorithm for polishing tool path generation in the small toot polishing process of the axis-symmetrical lens. Generally dwell time control in the polishing machines means that small polishing tool stays for a dwell time at the specific surface position to get the expected polishing depth. Polishing depth distribution on an aspherical lens surface consists of the superposition of the local polishing depth at the each dwell position. Therefore, tool path generation needs each dwell time together with tool positioning data during the polishing tool movements on the aspherical lens surface. The linear algebraic equation of removal depth removal matrix and dwell time is formulated. Parametric effects such as the dwell d interval are simulated to validate the dwell time calculation algorithm.

• IE interfaces
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• v.15 no.4
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• pp.474-482
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• 2002

In this paper, we propose a parametric optimization approach to simultaneously determining trip distribution, mode choice, and user-equilibrium assignment. In our model, mode choice decisions are based on a binomial logit model and passenger and cargo demands are divided into appropriate mode according to the user equilibrium minimum travel time. Underlying network consists of road and rail networks combined and mode choice available is auto, bus, truck, passenger rail, and cargo rail. We provide an equivalent convex optimization problem formulation and efficient algorithm for solving this problem. The proposed algorithm was applied to a large scale network examples derived from the National Intermodal Transportation Plan (2000-2019).

• Journal of the Korean Society for Precision Engineering
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• v.17 no.3
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• pp.136-148
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• 2000

In this work, a general method for the mathematical description of three-dimensional trimmed surface is proposed by introducing the base parametric surface and boundary curves. Since mesh density distribution for the analysis may vary by cases, a grid-based mesh generation algorithm using quadtree is proposed in the present work. For the assurance of connectivity of generated meshes among surfaces, a method for the pre-cleaning of boundary curves has been developed to be used in the automatic generation of the finite elements. In addition, mesh-smoothing algorithm is suggested which can be used in the general trimmed surface. In this algorithm nodes are moved on the original surface by the normal projection in each iterative smoothing procedure.

• Proceedings of the KIEE Conference
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• 1999.11c
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• pp.703-705
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• 1999

In this paper, we introduce the direction of arrival(DOA) estimation of distributed signal based on the improved ESPRIT algorithm. Most research on the estimation of DOA has been performed based on the assumption that the signal sources are point sources. However, we consider a two-dimensional distributed signal source model using improved ESPRIT algorithm. In the distributed signal source model, a source is represented by two parameters, the azimuth angle and elevation angle. We address the estimation of the elevation and azimuth angles of distributed sources based on the parametric source modeling in the three-dimensional space with two uniform linear arrays. The array output vector is obtained by integrating a steering vector over all direction of arrival with the weighting of a distributed source density function. We also develop an efficient estimation procedures that can reduce the computational complexity. Some examples are shown to demonstrate explicity the estimation procedures under the distributed signal source model.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.5
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• pp.1001-1004
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• 2010

Acoustic feedback and background noise variation can degrade the performance of an active noise control (ANC) system. In this paper, nonlinear ANC using a non-parametric VSS-NLMS (or NPVSS-NLMS) algorithm and online feedback path modeling is proposed, whereby the conventional linear ANC with online acoustic feedback-path modeling is further extended to nonlinear Volterra ANC with a linear acoustic feedback path. In particular, the step-size of the NPVSS-NLMS algorithm is controlled to reduce the effect of background noise variation in the ANC system. Simulation results demonstrate that the proposed approach yields better nonlinear ANC performance compared with the conventional nonlinear ANC method.

• Korean Journal of Computational Design and Engineering
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• v.8 no.4
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• pp.262-269
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• 2003

An approach to compute characteristic curves such as section curves, reflection characteristic lines, and asymptotic curves on a surface is introduced. Each problem is formulated as a surface-plane inter-section problem. A single-valued function that represents the characteristics of a problem constructs a property surface on parametric space. Using a contouring algorithm, the property surface is intersected with a horizontal plane. The solution of the intersection yields a series of points which are mapped into object space to become characteristic curves. The approach proposed in this paper eliminates the use of traditional searching methods or non-linear differential equation solvers. Since the contouring algorithm has been known to be very robust and rapid, most of the problems are solved efficiently in realtime for the purpose of visualization. This approach can be extended to any geometric problem, if used with an appropriate formulation.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.51-55
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• 1995

An adaptive unified predictive control (UPC) algorithm is applied to a batch polymerization reactor for poly(methyl methancrylate) (PMMA) and the effects of controller parameters are investigated. Computational studies are performed for a batch polymerization system model developed in this study. A transfer function in parametric form is estimated by recursive least squares (RLS) method, and the UPC algorithm is implemented to control the reactor temperature on the basis of this transfer function. The adaptive unified predictive controller shows a better performance than the PID controller for tracking set point changes, especially in the latter part of reaction course when gel effect becomes significant. Various performance can be acquired by selecting adequate values for parameters of the adaptive unified predictive controller; in other words, the optimal set of parameters exists for a given set of reaction conditions and control objective.

• Proceedings of the KIEE Conference
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• 1999.11b
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• pp.18-20
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• 1999

In this paper, the space mapping algorithm is proposed for the design of electric machines. By the algorithm, we can combine the magnetic equivalent circuit and the finite element models mathematically and got the final design parameters with a few iterations while preserving the accuracy offered by the finite element model. The finite element model is generated by parametric techniques. For the validity of this algorithm, a simple permanent magnet device with fringing and leakage flux is dealt as a numerical example.