298 research outputs found

    ACCPM with a nonlinear constraint and an active set strategy to solve nonlinear multicommodity flow problems

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    This paper proposes an implementation of a constrained analytic center cutting plane method to solve nonlinear multicommodity flow problems. The new approach exploits the property that the objective of the Lagrangian dual problem has a smooth component with second order derivatives readily available in closed form. The cutting planes issued from the nonsmooth component and the epigraph set of the smooth component form a localization set that is endowed with a self-concordant augmented barrier. Our implementation uses an approximate analytic center associated with that barrier to query the oracle of the nonsmooth component. The paper also proposes an approximation scheme for the original objective. An active set strategy can be applied to the transformed problem: it reduces the dimension of the dual space and accelerates computations. The new approach solves huge instances with high accuracy. The method is compared to alternative approaches proposed in the literatur

    Quantitative optical determination of the shape of Cu nanocrystals in a composite film

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    5 pages, 4 figures, 1 table.We demonstrate that optical extinction spectroscopy can be used to determine the effective shape of Cu nanocrystals (NCs) embedded in a transparent amorphous Al2O3 host both produced by pulsed laser deposition. The axial ratio of the NCs was extracted from the positions of the surface plasmon modes of the optical extinction spectra of the nanocomposite film. Comparison to the results obtained by grazing incidence small angle x-ray scattering shows excellent agreement. Thus, optical spectroscopy can be used as a simple, easily accessible, and versatile tool for the characterization of the NCs that form nanocomposite films.This work was supported by the European Union (BRITE Project No. 98-0616).Peer reviewe

    PLASIM-ENTSem v1.0: a spatio-temporal emulator of future climate change for impacts assessment

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    Many applications in the evaluation of climate impacts and environmental policy require detailed spatio-temporal projections of future climate. To capture feedbacks from impacted natural or socio-economic systems requires interactive two-way coupling, but this is generally computationally infeasible with even moderately complex general circulation models (GCMs). Dimension reduction using emulation is one solution to this problem, demonstrated here with the GCM PLASIM-ENTS (Planet Simulator coupled with the efficient numerical terrestrial scheme). Our approach generates temporally evolving spatial patterns of climate variables, considering multiple modes of variability in order to capture non-linear feedbacks. The emulator provides a 188-member ensemble of decadally and spatially resolved (~ 5◩ resolution) seasonal climate data in response to an arbitrary future CO2 concentration and non-CO2 radiative forcing scenario. We present the PLASIM-ENTS coupled model, the construction of its emulator from an ensemble of transient future simulations, an application of the emulator methodology to produce heating and cooling degree-day projections, the validation of the simulator (with respect to empirical data) and the validation of the emulator (with respect to high-complexity models). We also demonstrate the application to estimates of sea-level rise and associated uncertainty

    Enhancement of the magnetic anisotropy of nanometer-sized Co clusters: influence of the surface and of the inter-particle interactions

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    We study the magnetic properties of spherical Co clusters with diameters between 0.8 nm and 5.4 nm (25 to 7500$ atoms) prepared by sequential sputtering of Co and Al2O3. The particle size distribution has been determined from the equilibrium susceptibility and magnetization data and it is compared to previous structural characterizations. The distribution of activation energies was independently obtained from a scaling plot of the ac susceptibility. Combining these two distributions we have accurately determined the effective anisotropy constant Keff. We find that Keff is enhanced with respect to the bulk value and that it is dominated by a strong anisotropy induced at the surface of the clusters. Interactions between the magnetic moments of adjacent layers are shown to increase the effective activation energy barrier for the reversal of the magnetic moments. Finally, this reversal is shown to proceed classically down to the lowest temperature investigated (1.8 K).Comment: 13 figures submitted to Phys. Rev.

    Worldwide impacts of climate change on energy for heating and cooling

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    The energy sector is not only a major contributor to greenhouse gases, it is also vulnerable to climate change and will have to adapt to future climate conditions. The objective of this study is to analyze the impacts of changes in future temperatures on the heating and cooling services of buildings and the resulting energy and macro-economic effects at global and regional levels. For this purpose, the techno-economic TIAM-WORLD (TIMES Integrated Assessment Model) and the general equilibrium GEMINI-E3 (General Equilibrium Model of International-National Interactions between Economy, Energy and Environment) models are coupled with a climate model, PLASIM-ENTS (Planet-Simulator - Efficient Numerical Terrestrial Scheme). The key results are as follows. At the global level, the climate feedback induced by adaptation of the energy system to heating and cooling is found to be insignificant, partly because heating and cooling-induced changes compensate and partly because they represent a limited share of total final energy consumption. However, significant changes are observed at regional levels, more particularly in terms of addi- tional power capacity required to satisfy additional cooling services, resulting in increases in electricity prices. In terms of macro-economic impacts, welfare gains and losses are associated more with changes in energy exports and imports than with changes in energy consumption for heating and cooling. The rebound effect appears to be non-negligible. To conclude, the coupling of models of different nature was successful and showed that the energy and economic impacts of climate change on heating and cooling remain small at the global level, but changes in energy needs will be visible at more local scale

    Producing Policy-relevant Science by Enhancing Robustness and Model Integration for the Assessment of Global Environmental Change

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    We use the flexible model coupling technology known as the bespoke framework generator to link established existing modules representing dynamics in the global economy (GEMINI_E3), the energy system (TIAM-WORLD), the global and regional climate system (MAGICC6, PLASIM-ENTS and ClimGEN), the agricultural system, the hydrological system and ecosystems (LPJmL), together in a single integrated assessment modelling (IAM) framework, building on the pre-existing framework of the Community Integrated Assessment System. Next, we demonstrate the application of the framework to produce policy-relevant scientific information. We use it to show that when using carbon price mechanisms to induce a transition from a high-carbon to a low-carbon economy, prices can be minimised if policy action is taken early, if burden sharing regimes are used, and if agriculture is intensified. Some of the coupled models have been made available for use at a secure and user-friendly web portal

    Large-scale optimization with the primal-dual column generation method

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    The primal-dual column generation method (PDCGM) is a general-purpose column generation technique that relies on the primal-dual interior point method to solve the restricted master problems. The use of this interior point method variant allows to obtain suboptimal and well-centered dual solutions which naturally stabilizes the column generation. As recently presented in the literature, reductions in the number of calls to the oracle and in the CPU times are typically observed when compared to the standard column generation, which relies on extreme optimal dual solutions. However, these results are based on relatively small problems obtained from linear relaxations of combinatorial applications. In this paper, we investigate the behaviour of the PDCGM in a broader context, namely when solving large-scale convex optimization problems. We have selected applications that arise in important real-life contexts such as data analysis (multiple kernel learning problem), decision-making under uncertainty (two-stage stochastic programming problems) and telecommunication and transportation networks (multicommodity network flow problem). In the numerical experiments, we use publicly available benchmark instances to compare the performance of the PDCGM against recent results for different methods presented in the literature, which were the best available results to date. The analysis of these results suggests that the PDCGM offers an attractive alternative over specialized methods since it remains competitive in terms of number of iterations and CPU times even for large-scale optimization problems.Comment: 28 pages, 1 figure, minor revision, scaled CPU time
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