Bewertung von Abfallbehandlungsverfahren: Entscheidungsunterstützung durch die neue VDI‐Richtline 3925

The new VDI guideline 3925 presents assessment tools for the comparison of economic, ecological and also social aspects of different waste treatment processes. Objective of the guideline is to describe the application of suitable scientific and technical assessment methods to waste management strategies. The methods, their applicability, complexity, opportunities and limits are illustrated using practical examples.     

Bonded aerospace repairs under tensile loading: Wet chemical surface treatment and selected environmental conditions

Repair of composite structures and the impact of demanding environmental conditions is a crucial issue for the aircraft industry because of the increasing use of composites in modern aircraft. Consequently, the impact of environmental conditions common for aircraft applications on repair specimens in comparison to nonrepaired specimens is studied. All specimens are produced from a woven carbon fiber-reinforced epoxy-based prepreg. For the repair-specimens, an epoxy-based film adhesive is used for the soft patch repair approach. During the repair process, the surface of the precured prepreg is prepared by a mechanical method (sanding) and an additional chemical functionalization, respectively. Moisture absorption of the repair specimens is independent of the surface preparation method and higher for the repaired than for the nonrepaired specimens. The key influencing environmental conditions for the tensile strength and the failure mode of the repair specimens are elevated temperature testing as well as hot/wet conditioning and conditioning in deionized water. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 47506.     

Fouling Detection in an Optically Accessible Microstructured Heat Exchanger

The application of highly effective microstructured devices in continuous production and industrial environments is frequently prone to fouling. A new method is presented to characterize fouling in these microstructures. Thermal fouling of aqueous solutions containing whey protein were used as a test system. Different fouling effects could be observed and distinguished. Integral fouling indicators, such as thermal fouling resistance and pressure drop, as conventional criteria for the occurrence of fouling were compared with direct local optical observation. Low thermal fouling resistances could be detected.     

Transferrin-Decorated Niosomes with Integrated InP/ZnS Quantum Dots and Magnetic Iron Oxide Nanoparticles: Dual Targeting and Imaging of Glioma

The development of multifunctional nanoscale systems that can mediate efficient tumor targeting, together with high cellular internalization, is crucial for the diagnosis of glioma. The combination of imaging agents into one platform provides dual imaging and allows further surface modification with targeting ligands for specific glioma detection. Herein, transferrin (Tf)-decorated niosomes with integrated magnetic iron oxide nanoparticles (MIONs) and quantum dots (QDs) were formulated (PEGNIO/QDs/MIONs/Tf) for efficient imaging of glioma, supported by magnetic and active targeting. Transmission electron microscopy confirmed the complete co-encapsulation of MIONs and QDs in the niosomes. Flow cytometry analysis demonstrated enhanced cellular uptake of the niosomal formulation by glioma cells. In vitro imaging studies showed that PEGNIO/QDs/MIONs/Tf produces an obvious negative-contrast enhancement effect on glioma cells by magnetic resonance imaging (MRI) and also improved fluorescence intensity under fluorescence microscopy. This novel platform represents the first niosome-based system which combines magnetic nanoparticles and QDs, and has application potential in dual-targeted imaging of glioma.     

Oxide scale formation of modified FeCrAl coatings exposed to liquid lead

Modified FeCrAl coatings were studied with respect to their capability to form a thin protective oxide scale in liquid lead environment. They were manufactured by low pressure plasma spraying and GESA surface melting, thereby tuning the Al content. The specimens were exposed for 900 h to liquid lead containing 10^?6 and 10^?8 wt.% oxygen, respectively, at various temperatures from 400 to 550 °C. Threshold values for an Al content that guarantees the formation of thin protective Al-rich oxide scales are determined, dependent on the respective chromium content, on the presence of yttrium in the modified coating, and on the exposure conditions.     

Using internal domain-specific languages to inherit tool support and modularity for model transformations

Software and Systems Modeling - Model-driven engineering (MDE) has proved to be a useful approach to cope with today’s ever-growing complexity in the development of software systems;...     

Dynamic rough clustering and its applications

Dynamic data mining has gained increasing attention in the last decade. It addresses changing data structures which can be observed in many real-life applications, e.g. buying behavior of customers. As opposed to classical, i.e. static data mining where the challenge is to discover pattern inherent in given data sets, in dynamic data mining the challenge is to understand – and in some cases even predict – how such pattern will change over time. Since changes in general lead to uncertainty, the appropriate approaches for uncertainty modeling are needed in order to capture, model, and predict the respective phenomena considered in dynamic environments. As a consequence, the combination of dynamic data mining and soft computing is a very promising research area. The proposed algorithm consists of a dynamic clustering cycle when the data set will be refreshed from time to time. Within this cycle criteria check if the newly arrived data have structurally changed in comparison to the data already analyzed. If yes, appropriate actions are triggered, in particular an update of the initial settings of the cluster algorithm. As we will show, rough clustering offers strong tools to detect such changing data structures. To evaluate the proposed dynamic rough clustering algorithm it has been applied to synthetic as well as to real-world data sets where it provides new insights regarding the underlying dynamic phenomena.