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.     

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.     

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.     

Experience-Driven Model of Decision-Making Processes in Project Teams

This article presents a model of decision-making processes in project teams. Project teams constitute a specific type of organization appointed to implement a project. Decisions made by project teams result from the methods of project management and best management practices. The authors have undertaken the task of formalizing these processes using the classical method of constructing decision trees. It has been established that this method cannot be fully exploited because the decision-making paths need changing (the decision tree must be dynamically generated after every decision). Therefore, the authors applied a method for collecting experiences, the Set of Experience Knowledge Structure (SOEKS), to support the structure of a decision tree. This method was used to support decision-making processes regarding the selection of methods and technologies of project management and to classify the location decisions resulting from exceeding levels of particulate matter.     

Growth of novel carbon phases by methane infiltration of free-standing single-walled carbon nanotube films

High-temperature methane infiltration of thin, free-standing films of acid-treated single-walled carbon nanotubes (SWCNT) has been studied by means of scanning electron microscopy, transmission electron microscopy and Raman spectroscopy. In the early stages of infiltration, carbon nuclei form predominantly at SWCNT bundle intersections. Further growth proceeds via the formation of graphite nanosheets - without further influence of the nanotube support. Both sheet edges and their structural imperfections act as reaction centers for subsequent deposition, likely giving rise to autocatalytic deposition kinetics. In contrast, infiltration with a H₂:CH₄ (24:1) mixture leads to the reductive activation of residual Ni/Co impurities embedded in the precursor SWCNT-felt. This is associated with a different predominant carbon deposition mode in which multiwalled carbon nanotubes grow out from the substrate.     

SpaDeS: Detecting spammers at the source network

Despite the large variety and wide adoption of different techniques to detect and filter unsolicited messages (spams), the total amount of such messages over the Internet remains very large. Some reports point out that around 80% of all emails are spams. As a consequence, significant amounts of network resources are still wasted as filtering strategies are usually performed only at the email destination server. Moreover, a considerable part of these unsolicited messages is sent by users who are unaware of their spamming activity and may thus inadvertently be classified as spammers. In this case, these oblivious users act as spambots, i.e., members of a spamming botnet. This paper proposes a new method for detecting spammers at the source network, whether they are individual malicious users or oblivious members of a spamming botnet. Our method, called SpaDeS, is based on a supervised classification technique and relies only on network-level metrics, thus not requiring inspection of message content. We evaluate SpaDeS using real datasets collected from a Brazilian broadband ISP. Our results show that our method is quite effective, correctly classifying the vast majority (87%) of the spammers while misclassifying only around 2% of the legitimate users.     

Rapid tooling aided by reverse engineering to manufacture EDM electrodes

The present work deals with the application of indirect rapid tooling (RT) technology to manufacture electrical discharge machining (EDM) copper electrodes from investment casting, with wax prototypes made by ThermoJet 3D printing, a rapid prototyping (RP) technique. The reverse engineering (RE) method is utilised to transform the point cloud data of an object surface, obtained from 3D digitising, in a 3D CAD surface model dataset. The methodology presented is fundamental to verify the prototype’s geometry for tooling so as to assure its metrological accuracy and to optimise foundry process parameters using finite element analysis (FEA). Based on a case study, some functional conclusions are presented for the application of RT in manufacturing EDM electrodes aided by 3D digitising and RE, validating the accomplishment by the integration of these technologies and methodologies in EDM manufacturing processes.