• Title/Summary/Keyword: Computational cost

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Life-Cycle Cost Optimization for Steel Box Girder Bridges (강상자형교의 생애주기비용 최적설계)

  • 조효남;민대홍;권우성;정기영
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 2001.04a
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    • pp.128-136
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    • 2001
  • This paper presents an optimum deck and girder system design for minimizing the life-cycle cost (LU) of steel box girder bridges. The problem of optimum LCC design of steel box girder bridges is formulated as that of minimization of the expected total LCC that consists of initial cost, maintenance cost, expected retrofit costs for strength, deflection, and crack. To demonstrate the effect of LCC optimum design of steel box girder bridges, the LCC optimum design is compared with conventional design method for steel box girder bridges design. From the numerical investigations, it may be positively stated that the optimum design of steel box girder bridges based on LCC will lead to more rational, economical and safer design.

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Reliability-based Life Cycle Cost Analysis for Optimal Seismic Upgrading of Bridges

  • Alfredo H-S. Ang;Cho, Hyo-Nam;Lim, Jong-Kwon;An, Joong-San
    • Computational Structural Engineering : An International Journal
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    • v.1 no.1
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    • pp.59-69
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    • 2001
  • This study is intended to propose a systematic approach for reliability-based assessment of life cycle cost (LCC) effectiveness and economic efficiency for cost-effective seismic upgrading of existing bridges. The LCC function is expressed as the sum of the upgrading cost and all the discounted life cycle damage costs, which is formulated as a function of the Park-Ang damage index and structural damage probability. The damage costs are expressed in terms of direct damage costs such as repair/replacement costs, human losses and property damage costs, and indirect damage costs such as road user costs and indirect regional economic losses. For dealing with a variety of uncertainties associated with earthquake loads and capacities, a simulation-based reliability approach is used. The SMART-DRAIN-2DX, which is a modified version of the well-known DRAIN-2DX, is extended by incor-porating LCC analysis based on the LCC function developed in the study. Economic efficiencies for optimal seismic upgradings of the continuous PC segmental bridges are assessed using the proposed LCC functions and benefit-cost ratio.

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ROBUST MIXED $H_2/H_{\infty}$ GUARANTEED COST CONTROL OF UNCERTAIN STOCHASTIC NEUTRAL SYSTEMS

  • Mao, Weihua;Deng, Feiqi;Wan, Anhua
    • Journal of applied mathematics & informatics
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    • v.30 no.5_6
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    • pp.699-717
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    • 2012
  • In this paper, we deal with the robust mixed $H_2/H_{\infty}$ guaranteed-cost control problem involving uncertain neutral stochastic distributed delay systems. More precisely, the aim of this problem is to design a robust mixed $H_2/H_{\infty}$ guaranteed-cost controller such that the close-loop system is stochastic mean-square exponentially stable, and an $H_2$ performance measure upper bound is guaranteed, for a prescribed $H_{\infty}$ attenuation level ${\gamma}$. Therefore, the fast convergence can be fulfilled and the proposed controller is more appealing in engineering practice. Based on the Lyapunov-Krasovskii functional theory, new delay-dependent sufficient criteria are proposed to guarantee the existence of a desired robust mixed $H_2/H_{\infty}$ guaranteed cost controller, which are derived in terms of linear matrix inequalities(LMIs). Furthermore, the design problem of the optimal robust mixed $H_2/H_{\infty}$ guaranteed cost controller, which minimized an $H_2$ performance measure upper bound, is transformed into a convex optimization problem with LMIs constraints. Finally, two simulation examples illustrate the design procedure and verify the expected control performance.

Real-time simulation on B-spline deformable volume-part III (B-spline volume 변형체의 실시간 시뮬레이션 II)

  • 전성기;조맹효
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 2002.10a
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    • pp.70-77
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    • 2002
  • Since our physical world cannot be modeled as rigid body, deformable object models are important. For real-time simulation of elastic object, it must be guaranteed by its exact solution and low-latency computational cost. In this paper, we describe the boundary integral equation formulation of linear elastic body and related boundary element method(BEM). The deformation of elastic body can be effectively solved with 1ow run-time computational costs, using precomputed Green Function and fast low-rank updates based on Capacitance Matrix Algorithm.

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Estimating Telephone Network Structure and Investment Cost Changes (교환/전송 기술진화에 따른 전화교환망 구조변화-시뮬레이션 모형에 의한 사례 분석-)

  • 송석재;장석권;전용수
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 1997.10a
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    • pp.138-141
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    • 1997
  • In this study, a simulation model is developed to analyze the effects of routing and scale-economy of transmission facilities on the traffic network topology and investment cost changes in a metropolitan telephone network. Computational experiments showed that the wide deployment of bifurcated routing in a dual-homing configuration reduces significantly the traffic network connectivity and the investment cost. Its enhanced version, when combined with the subscriber network cost model, can be used as a prototype cost proxy model for figuring out the access charges in a multi-operator environment.

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An efficient method to structural static reanalysis with deleting support constraints

  • Liu, Haifeng;Yue, Shigang
    • Structural Engineering and Mechanics
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    • v.52 no.6
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    • pp.1121-1134
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    • 2014
  • Structural design is usually an optimization process. Numerous parameters such as the member shapes and sizes, the elasticity modulus of material, the locations of nodes and the support constraints can be selected as design variables. These variables are progressively revised in order to obtain a satisfactory structure. Each modification requires a fresh analysis for the displacements and stresses, and reanalysis can be employed to reduce the computational cost. This paper is focused on static reanalysis problem with modification of deleting some supports. An efficient reanalysis method is proposed. The method makes full use of the initial information and preserves the ease of implementation. Numerical examples show that the calculated results of the proposed method are the identical as those of the direct analysis, while the computational time is remarkably reduced.

The Cholesky rank-one update/downdate algorithm for static reanalysis with modifications of support constraints

  • Liu, Haifeng;Zhu, Jihua;Li, Mingming
    • Structural Engineering and Mechanics
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    • v.62 no.3
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    • pp.297-302
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    • 2017
  • Structural reanalysis is frequently utilized to reduce the computational cost so that the process of design or optimization can be accelerated. The supports can be regarded as the design variables and may be modified in various types of structural optimization problems. The location, number, and type of supports can make a great impact on the performance of the structure. This paper presents a unified method for structural static reanalysis with imposition or relaxation of some support constraints. The information from the initial analysis has been fully utilized and the computational time can be significantly reduced. Numerical examples are used to validate the effectiveness of the proposed method.

An efficient approach to structural static reanalysis with added support constraints

  • Liu, Haifeng;Wu, Baisheng;Li, Zhengguang
    • Structural Engineering and Mechanics
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    • v.43 no.3
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    • pp.273-285
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    • 2012
  • Structural reanalysis is frequently used to reduce the computational cost during the process of design or optimization. The supports can be regarded as the design variables in various types of structural optimization problems. The location, number, and type of supports may be varied in order to yield a more effective design. The paper is focused on structural static reanalysis problem with added supports where some node displacements along axes of the global coordinate system are specified. A new approach is proposed and exact solutions can be provided by the approach. Thus, it belongs to the direct reanalysis methods. The information from the initial analysis has been fully exploited. Numerical examples show that the exact results can be achieved and the computational time can be significantly reduced by the proposed method.

CHEYSHEFF-HALLEY-LIKE METHODS IN BANACH SPACES

  • Argyros, Ioannis-K.
    • Journal of applied mathematics & informatics
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    • v.4 no.1
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    • pp.83-108
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    • 1997
  • Chebysheff-Halley methods are probably the best known cubically convergent iterative procedures for solving nonlinear equa-tions. These methods however require an evaluation of the second Frechet-derivative at each step which means a number of function eval-uations proportional to the cube of the dimension of the space. To re-duce the computational cost we replace the second Frechet derivative with a fixed bounded bilinear operator. Using the majorant method and Newton-Kantorovich type hypotheses we provide sufficient condi-tions for the convergence of our method to a locally unique solution of a nonlinear equation in Banach space. Our method is shown to be faster than Newton's method under the same computational cost. Finally we apply our results to solve nonlinear integral equations appearing in radiative transfer in connection with the problem of determination of the angular distribution of the radiant-flux emerging from a plane radiation field.

A Proposal of Shuffle Graph Convolutional Network for Skeleton-based Action Recognition

  • Jang, Sungjun;Bae, Han Byeol;Lee, HeanSung;Lee, Sangyoun
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.14 no.4
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    • pp.314-322
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    • 2021
  • Skeleton-based action recognition has attracted considerable attention in human action recognition. Recent methods for skeleton-based action recognition employ spatiotemporal graph convolutional networks (GCNs) and have remarkable performance. However, most of them have heavy computational complexity for robust action recognition. To solve this problem, we propose a shuffle graph convolutional network (SGCN) which is a lightweight graph convolutional network using pointwise group convolution rather than pointwise convolution to reduce computational cost. Our SGCN is composed of spatial and temporal GCN. The spatial shuffle GCN contains pointwise group convolution and part shuffle module which enhances local and global information between correlated joints. In addition, the temporal shuffle GCN contains depthwise convolution to maintain a large receptive field. Our model achieves comparable performance with lowest computational cost and exceeds the performance of baseline at 0.3% and 1.2% on NTU RGB+D and NTU RGB+D 120 datasets, respectively.