1,506 research outputs found

    On the Transformation Mechanism for Formulating a Multiproduct Two-Layer Supply Chain Network Design Problem as a Network Flow Model

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    The multiproduct two-layer supply chain is very common in various industries. In this paper, we introduce a possible modeling and algorithms to solve a multiproduct two-layer supply chain network design problem. The decisions involved are the DCs location and capacity design decision and the initial distribution planning decision. First we describe the problem and give a mixed integer programming (MIP) model; such problem is NP-hard and it is not easy to reduce the complexity. Inspired by it, we develop a transformation mechanism of relaxing the fixed cost and adding some virtual nodes and arcs to the original network. Thus, a network flow problem (NFP) corresponding to the original problem has been formulated. Given that we could solve the NFP as a minimal cost flow problem. The solution procedures and network simplex algorithm (INS) are discussed. To verify the effectiveness and efficiency of the model and algorithms, the performance measure experimental has been conducted. The experiments and result showed that comparing with MIP model solved by genetic algorithm (GA) and Benders, decomposition algorithm (BD) the NFP model and INS are also effective and even more efficient for both small-scale and large-scale problems

    Cyclic thermo-mechanical performance of granular beds: Effect of elastoplasticity

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    Understanding the coupled thermo-mechanical behaviour of compacted granular beds can benefit various industrial applications, such as pebble bed design in fusion reactors. In this study, a thermo-mechanical discrete element method based on our previous work is improved and adapted to investigate the cyclic thermo-mechanical performance of gas-filled granular materials composed of elastoplastic grains. An interparticle contact model is developed considering the plastic deformation of grains. Through the simulation on a representative volume element of beryllium pebble beds, we provide grain-scale insight into the evolution of thermal conductivity and stress. The simulation results suggest that the network of thermal contacts is impeded by plastic deformation leading to a significant drop of thermal conductivity during cooling. This effect can be suppressed by increasing the initial packing factor. Not limited to pebble bed design, the conclusion of this work can also pave the way for optimizing powder-based manufacturing and energy storage, where combined thermo-mechanical loading conditions and elastoplastic deformation of individual particles are involved

    Novel fusion computing method for bio-medical image of WSN based on spherical coordinate

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    In bio-medical field, embedded numerous sensing nodes can be used to monitor and interact with physical world based on signal analysis and processing. Data from many different sources can be collected into massive data sets via localized sensor networks. Understanding the environment requires collecting and analyzing data from thousands of sensors monitoring, this is big data environment. The application of bio-medical image fusion for big-data computing has strong development momentum, big-data bio-medical image fusion is one of key problems, so the fusion method study is a hot topic in the field of signal analysis and processing. The existing methods have many limitations, such as large delay, data redundancy, more energy cost, low quality, so novel fusion computing method based on spherical coordinate for big-data bio-medical image of WSN is proposed in this paper. In this method, the three high-frequency coefficients in wavelet domain of bio-medical image are pre-processed. This pre-processing strategy can reduce the redundant ratio of big-data bio-medical image. Firstly, the high-frequency coefficients are transformed to the spherical coordinate domain to reduce the correlation in the same scale. Then, a multi-scale model product (MSMP) is used to control the shrinkage function so as to make the small wavelet coefficients and some noise removed. The high-frequency parts in spherical coordinate domain are coded by improved SPIHT algorithm. Finally, based on multi-scale edge of bio-medical image, it can be fused and reconstructed. Experimental results indicate the novel method is effective and very useful for transmission of big-data bio-medical image, which can solve the problem of data redundancy, more energy cost and low quality
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