13 research outputs found

    GSI Scientific Report 2016

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    PLEASE GO TO FILES TO SELECT YOUR DOWNLOAD SECTION. Lience: https://creativecommons.org/licenses/by/4.0

    GSI Scientific Report 2014 / GSI Report 2015-1

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    GSI Scientific Report 2009 [GSI Report 2010-1]

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    Displacement design response spectrum is an essential component for the currently-developing displacement-based seismic design and assessment procedures. This paper proposes a new and simple method for constructing displacement design response spectra on soft soil sites. The method takes into account modifications of the seismic waves by the soil layers, giving due considerations to factors such as the level of bedrock shaking, material non-linearity, seismic impedance contrast at the interface between soil and bedrock, and plasticity of the soil layers. The model is particularly suited to applications in regions with a paucity of recorded strong ground motion data, from which empirical models cannot be reliably developed

    GSI Scientific Report 2009 [GSI Report 2010-1]

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    GSI Scientific Report 2013

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    GSI Scientific Report 2011 [GSI Report 2012-1]

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    GSI Scientific Report 2012 [GSI Report 2013-1]

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    Optimization of Operation Sequencing in CAPP Using Hybrid Genetic Algorithm and Simulated Annealing Approach

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    In any CAPP system, one of the most important process planning functions is selection of the operations and corresponding machines in order to generate the optimal operation sequence. In this paper, the hybrid GA-SA algorithm is used to solve this combinatorial optimization NP (Non-deterministic Polynomial) problem. The network representation is adopted to describe operation and sequencing flexibility in process planning and the mathematical model for process planning is described with the objective of minimizing the production time. Experimental results show effectiveness of the hybrid algorithm that, in comparison with the GA and SA standalone algorithms, gives optimal operation sequence with lesser computational time and lesser number of iterations

    Optimization of Operation Sequencing in CAPP Using Hybrid Genetic Algorithm and Simulated Annealing Approach

    Get PDF
    In any CAPP system, one of the most important process planning functions is selection of the operations and corresponding machines in order to generate the optimal operation sequence. In this paper, the hybrid GA-SA algorithm is used to solve this combinatorial optimization NP (Non-deterministic Polynomial) problem. The network representation is adopted to describe operation and sequencing flexibility in process planning and the mathematical model for process planning is described with the objective of minimizing the production time. Experimental results show effectiveness of the hybrid algorithm that, in comparison with the GA and SA standalone algorithms, gives optimal operation sequence with lesser computational time and lesser number of iterations

    Autonomous Navigation of Automated Guided Vehicle Using Monocular Camera

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    This paper presents a hybrid control algorithm for Automated Guided Vehicle (AGV) consisting of two independent control loops: Position Based Control (PBC) for global navigation within manufacturing environment and Image Based Visual Servoing (IBVS) for fine motions needed for accurate steering towards loading/unloading point. The proposed hybrid control separates the initial transportation task into global navigation towards the goal point, and fine motion from the goal point to the loading/unloading point. In this manner, the need for artificial landmarks or accurate map of the environment is bypassed. Initial experimental results show the usefulness of the proposed approach.COBISS.SR-ID 27383808
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