1,257 research outputs found

    Algebraic equations of state for the liquid crystalline phase behavior of hard rods

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    Based on simplifications of previous numerical calculations [Graf and L\"{o}wen, Phys. Rev. E \textbf{59}, 1932 (1999)], we propose algebraic free energy expressions for the smectic-A liquid crystal phase and the crystal phases of hard spherocylinders. Quantitative agreement with simulations is found for the resulting equations of state. The free energy expressions can be used to straightforwardly compute the full phase behavior for all aspect ratios and to provide a suitable benchmark for exploring how attractive interrod interactions mediate the phase stability through perturbation approaches such as free-volume or van der Waals theory.Comment: 12 pages,accepted for publication in Phys. Rev.

    Patch behaviour and predictability properties of modelled finite-amplitude sand ridges on the inner shelf

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    The long-term evolution of shoreface-connected sand ridges is investigated with a nonlinear spectral model which governs the dynamics of waves, currents, sediment transport and the bed level on the inner shelf. Wave variables are calculated with a shoaling-refraction model instead of using a parameterisation. The spectral model describes the time evolution of amplitudes of known eigenmodes of the linearised system. Bottom pattern formation occurs if the transverse bottom slope of the inner shelf, ÎČ, exceeds a critical value β<sub>c</sub>. For fixed model parameters the sensitivity of the properties of modelled sand ridges to changes in the number (<i>N</i>−1) of resolved subharmonics (of the initially fastest growing mode) is investigated. For any <i>N</i> the model shows the growth and subsequent saturation of the height of the sand ridges. The saturation time scale is several thousands of years, which suggests that observed sand ridges have not reached their saturated stage yet. The migration speed of the ridges and the average longshore spacing between successive crests in the saturated state differ from those in the initial state. Analysis of the potential energy balance of the ridges reveals that bed slope-induced sediment transport is crucial for the saturation process. In the transient stage the shoreface-connected ridges occur in patches. The overall characteristics of the bedforms (saturation time, final maximum height, average longshore spacing, migration speed) hardly vary with <i>N</i>. However, individual time series of modal amplitudes and bottom patterns strongly depend on <i>N</i>, thereby implying that the detailed evolution of sand ridges can only be predicted over a limited time interval. Additional experiments show that the critical bed slope β<sub>c</sub> increases with larger offshore angles of wave incidence, larger offshore wave heights and longer wave periods, and that the corresponding maximum height of the ridges decreases whilst the saturation time increases

    Defying the Gibbs Phase Rule: Evidence for an Entropy-Driven Quintuple Point in Colloid-Polymer Mixtures

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    Using a minimal algebraic model for the thermodynamics of binary rod--polymer mixtures, we provide evidence for a quintuple phase equilibrium; an observation that seems to be at odds with the Gibbs phase rule for two-component systems. Our model is based on equations of state for the relevant liquid crystal phases that are in quantitative agreement with computer simulations. We argue that the appearance of a quintuple equilibrium, involving an isotropic fluid, a nematic and smectic liquid crystal, and two solid phases can be reconciled with a generalized Gibbs phase rule in which the two intrinsic length scales of the athermal colloid--polymer mixture act as additional field variables

    Integration of returns and decomposition of customer orders in e-commerce warehouses

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    In picker-to-parts warehouses, order picking is a cost- and labor-intensive operation that must be designed efficiently. It comprises the construction of order batches and the associated order picker routes, and the assignment and sequencing of those batches to multiple order pickers. The ever-increasing competitiveness among e-commerce companies has made the joint optimization of this order picking process inevitable. Inspired by the large number of product returns and the many but small-sized customer orders, we address a new integrated order picking process problem. We integrate the restocking of returned products into regular order picking routes and we allow for the decomposition of customer orders so that multiple batches may contain products from the same customer order. We thereby generalize the existing models on order picking processing. We provide Mixed Integer Programming (MIP) formulations and a tailored adaptive large neighborhood search heuristic that, amongst others, exploits these MIPs. We propose a new set of practically-sized benchmark instances, consisting of up to 5547 to be picked products and 2491 to be restocked products. On those large-scale instances, we show that integrating the restocking of returned products into regular order picker routes results in cost-savings of 10 to 15%. Allowing for the decomposition of the customer orders' products results in cost savings of up to 44% compared to not allowing this. Finally, we show that on average cost-savings of 17.4% can be obtained by using our ALNS instead of heuristics typically used in practice.Comment: Authors' preprin

    Towards Low-carbon Power Networks: Optimal Integration of Renewable Energy Sources and Hydrogen Storage

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    This paper proposes a new optimization model and solution method for determining optimal locations and sizing of renewable energy sources and hydrogen storage in a power network. We obtain these strategic decisions based on the multi-period alternating current optimal power (AC OPF) flow problem that considers the uncertainty of renewable output, electricity demand, and electricity prices. We develop a second-order cone programming approach within a Benders decomposition framework to provide globally optimal solutions. To the best of our knowledge, our paper is the first to propose a systematic optimization framework based on AC OPF that jointly analyzes power network, renewable, and hydrogen storage interactions in order to provide optimal locations and sizing decisions of renewables and hydrogen storage. In a test case, we show that the joint integration of renewable sources and hydrogen storage and consideration of the AC OPF model significantly reduces the operational cost of the power network. In turn, our findings can provide quantitative insights to decision-makers on how to integrate renewable sources and hydrogen storage under different settings of the hydrogen selling price, renewable curtailment costs, emission tax prices, and conversion efficiency

    Assessment of the value of remotely sensed surface water extent data for the calibration of a lumped hydrological model

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    For many catchments, there is insufficient field data to calibrate the hydrological models that are needed to answer water resources management questions. One way to overcome this lack of data is to use remotely sensed data. In this study, we assess whether Landsat‐based surface water extent observations can inform the calibration of a lumped bucket‐type model for Brazilian catchments. We first performed synthetic experiments with daily, monthly, and limited monthly data (April–October), assuming a perfect monotonic relation between streamflow and stream width. The median relative performance was 0.35 for daily data and 0.17 for monthly data, where values above 0 imply an improvement in model performance compared to the lower benchmark. This indicates that the limited temporal resolution of remotely sensed data is not an impediment for model calibration. In a second step, we used real remotely sensed water extent data for calibration. For only 76 of the 671 sites the remotely sensed water extent was large and variable enough to be used for model calibration. For 30% of these sites, calibration with the actual remotely sensed water extent data led to a model fit that was better than the lower benchmark (i.e., relative performance >0). Model performance increased with river width and variation therein. This indicates that the coarse spatial resolution of the freely‐available, long time series of water extent used in this study hampered model calibration. We, therefore, expect that newer higher‐resolution imagery will be helpful for model calibration for more sites, especially when time series length increases
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