Modell zum turbulenten Wärmeübergang in Rohren auf der Basis radialer und axialer Turbulenzintensitäten für Newtonsche Fluide

Zusammenfassung Ausgehend von vereinfachenden Annahmen zum Verlauf der radialen und axialen Geschwindigkeitsschwankungen in einem turbulent durchstr?mten Rohr wird eine den W?rmetransport beschreibende Differentialgleichung aufgestellt und numerisch gel?st. Es zeigt sich für den Fall der thermisch ausgebildeten Str?mung bei konstanter Wandtemperatur, da? bei Newtonschen Fluiden die über dem Rohrquerschnitt vorliegende Mitteltemperatur („Mischtemperatur”) stets in einem Wandabstand von ca. 0,3·Rohrradius im radialen Temperaturprofil auftritt. Aufgrund dieses Sachverhalts kann mit Hilfe eines einfachen Widerstandsmodells ein Parameter R_T relativ schnell an experimentelle Werte bzw. entsprechende Gebrauchsformeln angepa?t werden. Eine überprüfung mit dem in der Literatur h?ufig angewendeten Ansatz, bei dem ein turbulenter W?rmeaustauschkoeffizient ε _q (eddy diffusity of heat) definiert wird, zeigt die Gültigkeit der durchgeführten Vereinfachungen. Mit der Modellvorstellung kann auch der W?rmeübergang nicht-Newtonscher Flüssigkeiten (z.B. reibungsmindernde Polymerl?sungen) beschrieben werden, wenn deren Turbulenzintensit?ten durch Messungen gegeben sind.     

Stability and calorimetric studies of silico‐ferrites of calcium aluminum and magnesium

In a systematic study on silico‐ferrites of calcium aluminum and magnesium (SFCA phases) this investigation focuses on synthesis of silicon‐free SFCA‐type compounds with low‐MgO contents (~1.00 apfu—atoms per formula unit). Previous studies revealed the existence of iron‐rich SFCA phases similar to the SFCA‐I structure with the chemical composition Ca₃MgAl₆Fe₁₀O₂₈ (Metall Mater Trans B. 2017;48:2207). The experimental results in the quaternary Fe₂O₃‐CaO‐Al₂O₃‐MgO system confirm large stability fields of 2 silicon‐free ferrites FCAM‐I and FCAM‐III, which are members of the homologous series M_14+6nO_20+8n (n = 1, 2). Starting with compositions corresponding to Ca₃MgAl_xFe_16‐xO₂₈ (with increasing aluminum content from x = 0‐12 apfu), it was possible to synthesize these phases with an x‐value ≥2 apfu, which corresponds to Al₂O₃ contents ≥7.14 wt%. Synthesis of pure silicon‐free ferrites with n = 1 (FCAM‐I) and 2 (FCAM‐III) and silicon‐bearing ferrites with n = 0 (SFCA) was possible. Samples were characterized by electron probe microanalysis, powder diffraction, and subsequently studied using relaxation calorimetry measurements in combination with differential scanning calorimetry for determination of the heat capacities and standard entropies S°(298). The corresponding values are S°(298) = 650.3 ± 4.6 J/mol·K for SFCA, S°(298) = 864.5 ± 6.1 J/mol·K for FCAM‐I, and S°(298) = 1206.2 ± 8.4 J/mol·K for FCAM‐III. These thermodynamic data are a step toward a rigorous quantitative thermodynamic modeling of the iron ore sintering process.     

ETL workflow reparation by means of case-based reasoning

Data sources (DSs) being integrated in a data warehouse frequently change their structures/schemas. As a consequence, in many cases, an already deployed ETL workflow stops its execution, yielding errors. Since in big companies the number of ETL workflows may reach dozens of thousands and since structural changes of DSs are frequent, an automatic repair of an ETL workflow after such changes is of high practical importance. In our approach, we developed a framework, called E-ETL, for handling the evolution of an ETL layer. In the framework, an ETL workflow is semi-automatically or automatically (depending on a case) repaired as the result of structural changes in DSs, so that it works with the changed DSs. E-ETL supports two different repair methods, namely: (1) user defined rules, (2) and Case-Based Reasoning. In this paper, we present how Case-Based Reasoning may be applied to repairing ETL workflows. In particular, we contribute an algorithm for selecting the most suitable case for a given ETL evolution problem. The algorithm applies a technique for reducing cases in order to make them more universal and capable of solving more problems. The algorithm has been implemented in prototype E-ETL and evaluated experimentally. The obtained results are also discussed in this paper.     

Representation and analysis of enterprise models with semantic techniques: an application to ArchiMate,e3value and business model canvas

Enterprise models assist the governance and transformation of organizations through the specification, communication and analysis of strategy, goals, processes, information, along with the underlying application and technological infrastructure. Such models cross-cut different concerns and are often conceptualized using domain-specific modelling languages. This paper explores the application of graph-based semantic techniques to specify, integrate and analyse multiple, heterogeneous enterprise models. In particular, the proposal described in this paper (1) specifies enterprise models as ontological schemas, (2) uses transformation mapping functions to integrate the ontological schemas and (3) analyses the integrated schemas with graph querying and logical inference. The proposal is evaluated through a scenario that integrates three distinct enterprise modelling languages: the business model canvas, e3value, and the business layer of the ArchiMate language. The results show, on the one hand, that the graph-based approach is able to handle the specification, integration and analysis of enterprise models represented with different modelling languages and, on the other, that the integration challenge resides in defining appropriate mapping functions between the schemas.     

An analytic solution to the coupled pressure–temperature equations for modeling of photoacoustic trace gas sensors

Trace gas sensors have a wide range of applications including air quality monitoring, industrial process control, and medical diagnosis via breath biomarkers. Quartz-enhanced photoacoustic spectroscopy and resonant optothermoacoustic detection are two techniques with several promising advantages. Both methods use a quartz tuning fork and modulated laser source to detect trace gases. To date, these complementary methods have been modeled independently and have not accounted for the damping of the tuning fork in a principled manner. In this paper, we discuss a coupled system of equations derived by Morse and Ingard for the pressure, temperature, and velocity of a fluid, which accounts for both thermal effects and viscous damping, and which can be used to model both types of trace gas sensors simultaneously. As a first step toward the development of a more realistic model of these trace gas sensors, we derive an analytic solution to a pressure–temperature subsystem of the Morse–Ingard equations in the special case of cylindrical symmetry. We solve for the pressure and temperature in an infinitely long cylindrical fluid domain with a source function given by a constant-width Gaussian beam that is aligned with the axis of the cylinder. In addition, we surround this cylinder with an infinitely long annular solid domain, and we couple the pressure and temperature in the fluid domain to the temperature in the solid. We show that the temperature in the solid near the fluid–solid interface can be at least an order of magnitude larger than that computed using a simpler model in which the temperature in the fluid is governed by the heat equation rather than by the Morse–Ingard equations. In addition, we verify that the temperature solution of the coupled system exhibits a thermal boundary layer. These results strongly suggest that for computational modeling of resonant optothermoacoustic detection sensors, the temperature in the fluid should be computed by solving the Morse–Ingard equations rather than the heat equation.     

Protein‐Corona‐by‐Design in 2D: A Reliable Platform to Decode Bio–Nano Interactions for the Next‐Generation Quality‐by‐Design Nanomedicines

Hard corona (HC) protein, i.e., the environmental proteins of the biological medium that are bound to a nanosurface, is known to affect the biological fate of a nanomedicine. Due to the size, curvature, and specific surface area (SSA) 3‐factor interactions inherited in the traditional 3D nanoparticle, HC‐dependent bio–nano interactions are often poorly probed and interpreted. Here, the first HC‐by‐design case study in 2D is demonstrated that sequentially and linearly changes the HC quantity using functionalized graphene oxide (GO) nanosheets. The HC quantity and HC quality are analyzed using NanoDrop and label‐free liquid chromatography–mass spectrometry (LC‐MS) followed by principal component analysis (PCA). Cellular responses (uptake and cytotoxicity in J774 cell model) are compared using imaging cytometry and the modified lactate dehydrogenase assays, respectively. Cellular uptake linearly and solely correlates with HC quantity (R² = 0.99634). The nanotoxicity, analyzed by retrospective design of experiment (DoE), is found to be dependent on the nanomaterial uptake (primary), HC composition (secondary), and nanomaterial exposure dose (tertiary). This unique 2D design eliminates the size–curvature–SSA multifactor interactions and can serve as a reliable screening platform to uncover HC‐dependent bio–nano interactions to enable the next‐generation quality‐by‐design (QbD) nanomedicines for better clinical translation.     

Green Cloud Provisioning Throughout Cooperation of a WDM Wide Area Network and a Hybrid Power IT Infrastructure

The paper focuses on cooperation between cloud and network operators, as well as on fitting particular routing strategies to various cloud services. Three cooperation models are presented, analyzed and compared in the paper: the proposed model and two widely used reference models. The main difference between the models is the set of information being exchanged between the involved parties. Additionally, we analyze the applicability of four fitting schemas for each considered model. It is shown that the proposed model, alongside with an appropriate fitting schema, is able to reduce the blocking probability of cloud services requests. At the same time, thanks to the use of green anycast strategies, it is able to significantly reduce carbon dioxide emission.