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Abstract Conventional spouted beds have been extensively used in many real-life applications but are not suited for all types of materials, especially fine particles, which require internal devices to improve their motion in the spouted bed. However, unlike conventional spouted beds, there are almost no mechanistic or empirical models available for the design of spouted beds with internals. Given the availability of an extensive but not experimentally designed database, the main purpose of this study is to present an analysis of neural networks and empirical models in terms of their suitability to fit and predict average cycle times in conical spouted beds with and without draft tubes. The parameters investigated are particle size, density, contactor angle, gas inlet diameter, static bed height, and draft tube features. Although the amount of information is always a key factor when fitting models, the size of the database used in this study strongly affects the fitting performance of empirical models, whereas artificial neural networks are more influenced by how the data are scaled. Results of model verification show that both techniques are suitable for predicting average cycle times for data outside the range covered by the database.

"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.

Five years after the efficiency tests of the European COST ES0601 project (known as “HOME”) new tests are planned with the use of a new benchmark dataset. New tests are needed for three reasons: i) Several homogenization methods have newer versions since HOME, while some other methods were not tested by HOME; ii) The HOME benchmark represented only one climatic region (i.e. the central-western European climate) and a not very large selection of inhomogeneity problems; and iii) The number of networks in the HOME benchmark was small, and thus certain kinds of results with them have large statistical uncertainty. For all these reasons the representativeness of HOME results is limited. The new tests will be performed by researchers of the Centre for Climate Change of the University Rovira i Virgili and those of the Spanish Meteorological Agency (AEMET) with the support of a Spanish national project. We will develop and use a much larger benchmark dataset than the HOME benchmark, but we will test automatic methods only, thus the amount of the required work remains feasible. Primarily, the openly accessible automatic methods will be tested, which do not need the direct collaboration of the method developers. However, we intend to keep contact with the developers in order to test the best versions of the methods with the best possible parameterizations . Until the autumn of 2016 we will be accepting newly developed methods and versions for testing. In the development of the new benchmark, we will build on the knowledge gathered before the creation of HOME benchmark, but we aim to create an even more realistic benchmark including various segments representing particular climatic regions and inhomogeneity problems. For instance, the new benchmark will consider that a) The frequency of breaks of detectable size is generally much higher for temperature series than for precipitation series; b) The annual cycle of biases depends both on the examined variable and the geographical region; c) The frequent presence of short-term, platform-shaped inhomogeneities in observed temperature series. The efficiencies will be evaluated with the residual root mean square error of monthly and annual values in homogenized series, as well as with the residual trend bias errors for individual time series and network mean trends. Presentación realizada en: 10th EUMETNET Data Management Workshop celebrado en St. Gallen, Suiza, del 28 al 30 de octubre de 2015.

The utilisation of thermoelectric technology as a heat pump in heating applications necessitates comprehensive investigation. The scalable nature of thermoelectric technology enables its operation at elevated temperatures without the requirement of refrigerants. In this work, an accurate computational model that can simulate one- and two-stage thermoelectric heat pumps is developed. This model uses the electric-thermal analogy and the finite difference method, including the thermoelectric effects, temperature dependent properties, thermal contact resistances and all heat exchangers, even the intermediate heat exchanger in the case of a two-stage configuration. Moreover, the model has been experimentally validated by built and tested prototypes, being the first time that a two-stage thermoelectric heat pump model is experimentally validated. The discrepancy between the simulated and experimental results is below the ± 10 % for , ± 8 % for generated heat and temperature lift in the airflow, and less than the ± 6 % for consumed power. Additonally, the model simulates real tendencies under different operating conditions, proving the reliability of the developed thermoelectric heat pump model. Finally, the model is used to optimise a thermoelectric system combining one- and two-stage thermoelectric heat pumps, and hybridising them with electric resistances. An airflow of 16.5 m3/h is heated from 25 °C to 160 °C, achieving a maximum of 1.21. Lastly, the importance of considering the thermal resistances of the heat exchangers is computationally modelled and demonstrated. Not taking them into account would overestimate the performance of the TEHP system by more than the 7 %. The authors would like to acknowledge the support of the grant TED2021-130071A-I00 funded by MCIN/AEI/10.13039/501100011033 and, as appropriate, by 'European Union Next Generation EU/PRTR', as well as the Government of Navarre, as part of the 'Grants to SINAI agents for the realization of collaborative R&D projects' under the PC066-067-068 FlexORCStorage. Open access funding provided by Universidad Pública de Navarra.

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.

The SBE19 Brussels - BAMB-CIRCPATH "Building as Material Banks - A Pathway for a Circular held in Brussels on 5 to 7 of February 2019, is an initiative of the Consortium of the H2020 BAMB Project together with the Sustainable Built Environment (SBE) series of conferences. Being within the SBE series, this event gathers the support of CIB International Council for Research and Innovation in Building and Construction, iiSBE International Initiative for a Sustainable Built Environment, the United Nations Environment Programme, and FIDIC International Federation of Consulting Engineers. The goal of this series of regional and international conferences is to disseminate innovative policies and developments in the field of sustainable urban environment to a broad international audience of specialists in policy, design, construction and operation of buildings and related infrastructure. info:eu-repo/semantics/publishedVersion

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.