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"Egal ob Pump- oder Druckspeicher, Batterien oder "virtuelle" Pufferung im Netz - alle Technologien zur Stromspeicherung besitzen ihre spezifischen Vor- und Nachteile. Angesichts wachsender Marktanteile regenerativer Stromerzeugung nimmt die Bedeutung effizienter Techniken zur Energiespeicherung zu. Nur so werden "fluktuierende" Quellen wie Windkraft und Photovoltaik planbar."

In 2008 the Large Hadron Collider (LHC) and its experiments started operation at the European Centre of Nuclear Research (CERN) in Geneva with the main aim of finding or excluding the Higgs boson. Only four years later, on the 4th of July 2012, the discovery of a Higgs-like particle was proven and first published by the two main experiments ATLAS and CMS. Even though proton–proton collisions are the main operation mode of the LHC, it also acts as an heavy-ion collider. Here, the term “heavy-ion collisions” refers to the collision between fully stripped nuclei. While the major hardware system of the LHC is compatible with heavy-ion operation, the beam dynamics and performance limits of ion beams are quite different from those of protons. Because of the higher mass and charge of the ions, beam dynamic effects like intra-beam scattering and radiation damping are stronger. Also the electromagnetic cross-sections in the collisions are larger, leading to significantly faster intensity decay and thus shorter luminosity lifetimes. As the production cross-sections for various physics processes under study of the experiments are still small at energies reachable with the LHC and because the heavy-ion run time is limited to a few days per year, it is essential to obtain the highest possible collision rate, i.e. maximise the instantaneous luminosity, in order to obtain enough events and therefore low statistical errors. Within this thesis, the past performance of the LHC in lead-lead (Pb-Pb) collisions, at a centre-of-mass energy of 2.76 TeV per colliding nucleon pair, is analysed and potential luminosity limitations are identified. Tools are developed to predict future performance and techniques are presented to further increase the luminosity. Finally, a perspective on the future of high energy heavy-ion colliders is given.

Sustainability of agro-food supply chains has recently become the subject of greater interest from consumers, firms, governmental organizations and academia as the environment continues to deteriorate. One of the most critical factors influencing the sustainability of an agro-food supply chain is its network design. A particularly challenging aspect in this context is the broad range of influencing indicators associated with the Triple Bottom Line (TBL) of sustainability that need to be considered. However, many of these indicators could not be fully integrated or measured by single-step optimization problems. This paper presents a critical literature review of operational research methods for the design of sustainable supply chains. A novel two-stage hybrid solution methodology is proposed. In the first stage, a partner selection is performed using a hybrid multi criteria decision making based on Analytic Hierarchy Process (AHP) method and the Ordered Weighted Averaging (OWA) aggregation method. The result obtained in the first stage is used in the second stage to develop a multi-objective mathematical model to optimize the design of the supply chain network. This approach allows the simultaneous consideration of all three dimensions of sustainability including carbon footprint, water footprint, number of jobs created and the total cost of the supply chain design. The proposed approach generates a Pareto frontier to aid users in making decisions. Numerical experiments are completed utilizing data from an agro-food company to demonstrate the efficiency and effectiveness of the proposed solution methodology. The analyzes of the numerical results provide important organizational, practical and policy insights on (1) the impact of financial and environmental sustainability on supply chain network design (2) the tradeoff analysis between environmental emission, water footprint, societal implications and associated cost for making informed decision on supply chain investment.

Since the invention of fluorescent light sources, there is strong interest in Eu3+ activated phosphors as they are able to provide a high color rendering index (CRI) and luminous efficacy, which will also hold for phosphor converted light emitting diodes. Due to an efficient U6+ to Eu3+ energy transfer in Gd3Li3Te2O12:U6+,Eu3+, this inorganic composition shows red photoluminescence peaking at 611 nm. That means Eu3+ photoluminescence can be nicely sensitized via excitation into the U6+ excitation bands. Therefore, photoluminescence properties, such as temperature dependent emission and emission lifetime measurements, are presented. Charge transfer bands were investigated in detail. Additionally, density functional theory calculations reveal the band structure of the pure, i.e., non-doped host material. Obtained theoretical results were evaluated experimentally by the aid of diffuse UV reflectance spectroscopy.

Using a combination of numerical and analytical techniques we demonstrate that a metal stripe surrounded by the active and passive dielectrics supports propagation of stable spatial surface-plasmon solitons. Our analytical methods include the multiple scale reduction of the Maxwell's equations to the coupled Ginzburg-Landau system, and the soliton perturbation theory developed in the framework of the latter.

ABSTRACTThe California generation fleet manages the existing variability and uncertainty in the demand for electric power (load). When wind power is added, the dispatchable generators manage the variability and uncertainty of the net load (load minus wind power). The variability and uncertainty of the load and the net load are compared when 8790 MW of wind power are added to the California power system, a level expected when California achieves its 33% renewable portfolio standard, using a data set of 26,296 h of synchronous historic load and modeled historic wind power output. Variability was calculated as the rate of change in power generated by wind farms or consumed by the load from 1 h to the next (MW/h). Uncertainty was calculated as the 1 h ahead forecast error [MW] of the wind power or of the load. The data show that wind power adds no additional variability than is already present in the load variability. However, wind power adds additional uncertainty through increased forecast errors in the net load compared with the load. Forecast errors in the net load increase 18.7% for negative forecast errors (actual less than forecast) and 5.4% for positive forecast errors (actual greater than forecast). The increase in negative forecast errors occurs only during the afternoon hours when negative load forecasts and positive wind forecasts are strongly correlated. Managing the integration of wind power in the California power system should focus on reducing wind power forecast uncertainty for wind ramp ups during the afternoon hours. Copyright © 2013 John Wiley & Sons, Ltd.

Mixing under high pressure conditions plays a central role in several engineering applications, such as direct-injection engines and liquid rocket engines. Numerical flow simulations have become a complementary tool to study the mixing process under these conditions but require complex thermodynamic modeling as well as validation with accurate experimental data. For this reason, we use experiments of supercritical single-phase jet mixing from the literature, where the mixing is quantified by the mixture speed of sound, as a reference for our work. We here focus on the thermodynamic modeling of multi-component flows under high pressure conditions and the analytical calculation of the mixture speed of sound. Our thermodynamic model is based on cubic equations of state extended for multi-components. Using an extension of OpenFOAM, we perform large-eddy simulations of hexane and pentane injections and compare our results with the experimentally measured mixture speed of sound at specific positions. The simulation results show the same characteristic trends, indicating that the mixing effects are well reproduced in the simulations. Additionally, the effect of the sub-grid scale modeling is assessed by comparing results using different models (Smagorinsky, Vreman, and Wall-Adapting Local Eddy-viscosity). The comprehensive simulation data presented here, in combination with the experimental data, provide a benchmark for numerical simulations of jet mixing in high pressure conditions.