• Title/Summary/Keyword: Self-Optimization

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MINLP optimization of a composite I beam floor system

  • Zula, Tomaz;Kravanja, Stojan;Klansek, Uros
    • Steel and Composite Structures
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    • v.22 no.5
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    • pp.1163-1192
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    • 2016
  • This paper presents the cost optimization of a composite I beam floor system, designed to be made from a reinforced concrete slab and steel I sections. The optimization was performed by the mixed-integer non-linear programming (MINLP) approach. For this purpose, a number of different optimization models were developed that enable different design possibilities such as welded or standard steel I sections, plastic or elastic cross-section resistances, and different positions of the neutral axes. An accurate economic objective function of the self-manufacturing costs was developed and subjected to design, resistance and deflection (in)equality constraints. Dimensioning constraints were defined in accordance with Eurocode 4. The Modified Outer-Approximation/Equality-Relaxation (OA/ER) algorithm was applied together with a two-phase MINLP strategy. A numerical example of the optimization of a composite I beam floor system, as presented at the end of this paper, demonstrates the applicability of the proposed approach. The optimal result includes the minimal produced costs of the structure, the optimal concrete and steel strengths, and dimensions.

System Optimization of Orthotropic Steel-Deck Bridges by Load and Resistance Factor Design (LRFD에 의한 강상판형교의 시스템 최적설계)

  • 조효남;민대홍;김현우
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 1998.04a
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    • pp.262-271
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    • 1998
  • Recent, more and more steel deck bridges are adopted for the design of long span bridges and the upgrading of existing concrete deck bridges, mainly because of reduced self weight, higher stiffness and efficient erection compared to concrete decks. The main objective of this study is to propose on formulation of the design optimizations to develop an optimal desist program required for optimum desist for orthotropic steel-deck bridges. The objective function of the optimization is formulated as a minimum initial cost design problem. The behavior and design constraints are formulated based on the ASD and LRFD criteria of the Korean Bridge Design Code(1996). The optimum design program developed in this study consists of two steps. In the first step the system optimization of the steel box girder bridges is carried out. And in the second step the program provided the optimum design of the orthotropic steel-deck with close ribs. In the optimal design program the analysis module for the deck optimization is based on the Pelican Esslinger method. The optimizer module of the program utilizes the ADS(Automated Desist Synthesis) routines using the optimization techniques fuor constrained optimization. From the results of real application examples, The cost effectiveness of optimum orthotropic steel-deck bridges designs based on both ASD and LRFD methods is investigated by comparing the results with those of conventional designs, and it may be concluded that the design developed in this study seems efficient and robust for the optimization of orthotropic steel-deck bridges

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A Novel Virtual Space Vector Modulation Strategy for the Neutral-Point Potential Comprehensive Balance of Neutral-Point-Clamped Converters

  • Zhang, Chuan-Jin;Tang, Yi;Han, Dong;Zhang, Hui;Zhang, Xiao;Wang, Ke
    • Journal of Power Electronics
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    • v.16 no.3
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    • pp.946-959
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    • 2016
  • A novel Virtual Space Vector (VSV) modulation strategy for complete control of potential neutral point (NP) issues is proposed in this paper. The neutral point potential balancing problems of multi-level converters, which include elimination of low frequency oscillations and self-balancing for NP dc unbalance, are investigated first. Then a set of improved virtual space vectors with dynamic adjustment factors are introduced and a multi-objective optimization algorithm which aims to optimize these adjustment factors is presented in this paper. The improved virtual space vectors and the multi-objective optimization algorithm constitute the novel Virtual Space Vector modulation. The proposed novel Virtual Space Vector modulation can simultaneously recover NP dc unbalance and eliminate low frequency oscillations of the neutral point. Experiment results show that the proposed strategy has excellent performance, and that both of the neutral point potential issues can be solved.

3D Modeling of Self-Occluding Objects from 2D Drawings (자기폐색 물체의 2D 커브로부터의 3D모델링)

  • Cordier Frederic;Seo Hye-Won;Cho Young-Sang
    • Journal of KIISE:Software and Applications
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    • v.33 no.9
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    • pp.741-750
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    • 2006
  • In this paper, we propose a method for reconstructing a 3D object (or a set of objects) from a 2D drawing provided by a designer. The input 2D drawing consists of a set of contours that may partially overlap each other or be self-overlapping. Accordingly, the resulting 3D object(s) may occlude each other or be self-occluding. The proposed method is composed of three major steps: 2D contour analysis, 3D skeleton computation, and 3D object construction. Our main contribution is to compute the 3D skeleton from the self-intersecting 2D counterpart. We formulate the 3D skeleton construction problem as a sequence of optimization problems, to shape the skeleton and place it in the 3D space while satisfying C1-continuity and intersection-free conditions. Our method is mainly for a silhouette-based sketching interface for the design of 3D objects including self-intersecting objects.

Development of Self-Adaptive Meta-Heuristic Optimization Algorithm: Self-Adaptive Vision Correction Algorithm (자가 적응형 메타휴리스틱 최적화 알고리즘 개발: Self-Adaptive Vision Correction Algorithm)

  • Lee, Eui Hoon;Lee, Ho Min;Choi, Young Hwan;Kim, Joong Hoon
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.20 no.6
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    • pp.314-321
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    • 2019
  • The Self-Adaptive Vision Correction Algorithm (SAVCA) developed in this study was suggested for improving usability by modifying four parameters (Modulation Transfer Function Rate, Astigmatic Rate, Astigmatic Factor and Compression Factor) except for Division Rate 1 and Division Rate 2 among six parameters in Vision Correction Algorithm (VCA). For verification, SAVCA was applied to two-dimensional mathematical benchmark functions (Six hump camel back / Easton and fenton) and 30-dimensional mathematical benchmark functions (Schwefel / Hyper sphere). It showed superior performance to other algorithms (Harmony Search, Water Cycle Algorithm, VCA, Genetic Algorithms with Floating-point representation, Shuffled Complex Evolution algorithm and Modified Shuffled Complex Evolution). Finally, SAVCA showed the best results in the engineering problem (speed reducer design). SAVCA, which has not been subjected to complicated parameter adjustment procedures, will be applicable in various fields.

Self-Learning Control of Cooperative Motion for Humanoid Robots

  • Hwang, Yoon-Kwon;Choi, Kook-Jin;Hong, Dae-Sun
    • International Journal of Control, Automation, and Systems
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    • v.4 no.6
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    • pp.725-735
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    • 2006
  • This paper deals with the problem of self-learning cooperative motion control for the pushing task of a humanoid robot in the sagittal plane. A model with 27 linked rigid bodies is developed to simulate the system dynamics. A simple genetic algorithm(SGA) is used to find the cooperative motion, which is to minimize the total energy consumption for the entire humanoid robot body. And the multi-layer neural network based on backpropagation(BP) is also constructed and applied to generalize parameters, which are obtained from the optimization procedure by SGA, in order to control the system.

A Study on Optimal Layout of Two-Dimensional Rectangular Shapes Using Neural Network (신경회로망을 이용한 직사각형의 최적배치에 관한 연구)

  • 한국찬;나석주
    • Transactions of the Korean Society of Mechanical Engineers
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    • v.17 no.12
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    • pp.3063-3072
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    • 1993
  • The layout is an important and difficult problem in industrial applications like sheet metal manufacturing, garment making, circuit layout, plant layout, and land development. The module layout problem is known to be non-deterministic polynomial time complete(NP-complete). To efficiently find an optimal layout from a large number of candidate layout configuration a heuristic algorithm could be used. In recent years, a number of researchers have investigated the combinatorial optimization problems by using neural network principles such as traveling salesman problem, placement and routing in circuit design. This paper describes the application of Self-organizing Feature Maps(SOM) of the Kohonen network and Simulated Annealing Algorithm(SAA) to the layout problem of the two-dimensional rectangular shapes.

ON FIXED POINT THEOREMS SATISFYING COMPATIBILITY PROPERTY IN MODULAR G-METRIC SPACES

  • Daniel Francis;Godwin Amechi Okeke;Ho Geun Hyun
    • Nonlinear Functional Analysis and Applications
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    • v.29 no.2
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    • pp.361-391
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    • 2024
  • In this paper, a pair of ω-compatible self mappings in the setting of modular G-metric space is defined. We prove the existence and uniqueness of common fixed point of pairs of ω-compatible self mappings in a G-complete modular G-metric space. Furthermore, we give an example to justify our claims. The results established in this paper extend, improve, generalize and complement some existing results in literature.

Teaching learning-based optimization for design of cantilever retaining walls

  • Temur, Rasim;Bekdas, Gebrail
    • Structural Engineering and Mechanics
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    • v.57 no.4
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    • pp.763-783
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    • 2016
  • A methodology based on Teaching Learning-Based Optimization (TLBO) algorithm is proposed for optimum design of reinforced concrete retaining walls. The objective function is to minimize total material cost including concrete and steel per unit length of the retaining walls. The requirements of the American Concrete Institute (ACI 318-05-Building code requirements for structural concrete) are considered for reinforced concrete (RC) design. During the optimization process, totally twenty-nine design constraints composed from stability, flexural moment capacity, shear strength capacity and RC design requirements such as minimum and maximum reinforcement ratio, development length of reinforcement are checked. Comparing to other nature-inspired algorithm, TLBO is a simple algorithm without parameters entered by users and self-adjusting ranges without intervention of users. In numerical examples, a retaining wall taken from the documented researches is optimized and the several effects (backfill slope angle, internal friction angle of retaining soil and surcharge load) on the optimum results are also investigated in the study. As a conclusion, TLBO based methods are feasible.

Shape Optimization of Piezoelectric Materials for Piezoelectric-Structure-Acoustic System (압전-구조-음향 연성계의 압전 액츄에이터 최적설계)

  • Wang, Se-Myung;Lee, Kang-Hoon
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2000.06a
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    • pp.1627-1632
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    • 2000
  • Recently, piezoelectric materials have attracted considerable attention because of its self-sensing and actuating properties. To model smart structures, numerical modeling of structures with piezoelectric devices is essential. As many factors affect the performance of smart structures, optimization of these parameters is necessary. In this paper, the shape design sensitivity analysis of the 3D piezoelectric and structural elements is developed and shape optimization is performed. For the evaluation of the sensitivity, the finite element method is used. For the shape sensitivity, the domain velocity field is calculated. An acoustic cavity model is presented as a numerical example to study the feasibility of the formulation. The continuum sensitivity is compared with the results of the finite difference method by ANSYS. And the sequential linear programming (SLP) algorithm is used as the optimization algorithm.

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