Simulation und Messung der thermischen Behaglichkeit

Vorgestellt wird ein Ansatz, der eine Bewertung der thermischen Behaglichkeit auch unter komplexen, inhomogenen raumklimatischen Verhältnissen unter Berücksichtung der menschlichen Physiologie zulässt. Dabei wird die Strömungssimulation an ein numerisches Modell (UC Berkeley Comfort Model), welches die Thermoregulation des menschlichen Körpers abbildet, gekoppelt. Mit Hilfe der Strömungssimulation können die klimatischen Bedingungen in Räumen detailliert ermittelt werden. Darauf basierend können durch das Thermoregulationsmodell die Temperaturverteilung im menschlichen Körper, die resultierende Wärmeabgabe an die Umgebung sowie die thermische Behaglichkeit bestimmt werden. Beispielhaft wird dieser Ansatz bei der Simulation der thermischen Behaglichkeit sowie des Empfindens bei einer Flächenkühlung angewendet. Simulation and measurement of thermal comfort. An approach is introduced, which enables the assessment of thermal comfort considering the complex and inhomogeneous climatic conditions in buildings as well as the human physiology. Computational fluid dynamic is linked with a numerical model representing the thermophysiological behavior of the human body (UC Berkeley Comfort Model). By dint of CFD, the climatic conditions in buildings are simulated with a detailed resolution. Basing on the simulations, the thermophysiological model is able to determine the temperature distribution of the human body, the heat flux to the environment as well as thermal comfort. The approach is used for the exemplified investigation of thermal comfort and sensation in a room equipped with a radiant cooling floor.     

Thermal analysis and microstructural evaluation of conventional land developed high speed tool steels

Thermal analyses and microstructural evaluation were carried out for the conventional AISI M2 and M10 high speed steels as well as for alloys with varying Nb and/or Ti contents to assess their liquidus, solidus and other high temperature reactions. It has been found that the slope change of cooling curves marks the formation of MC type carbides, while the break is due to the crystallization of delta ferrite and much larger volume fraction of different type of carbides including M6C mostly by eutectic reactions. Results show that the formation of dendrites is the most basic characteristic of the solidification process for the AISI M2 and M10 alloys but for the steels containing niobium and/or titanium carbides, these primary carbides insert an inoculating effect and modify the coarse dendritic structure.     

Korngrenzenphasen in Schmelzlötverbindungen,Bildung – Schmelzen – Zusammensetzung

At the thermal solidification of metallic and non metallic melts with technical purity the thermal solidification of polycristalline substances is carried out under beginning of the corresponding grains and the beginning of a grain boundary phase between these grains. For the examination of the kinetics of melting thermally the authors used the gradual heating of eutectic SnPb solder pearls in an oxygen free heat up liquid. The developed method for the ultrasound supported dispersion of solid solder metals in an oxygen free heat up liquid was used for the separated thermal melt of the grain boundary phase and the grains.     

Modeling the thermal decomposition of friction composite systems based on yarn reinforced polymer matrices using artificial neural networks

The presented work deals with the application of artificial neural networks in the modelling of the thermal decomposition process of friction composite systems based on polymer matrices reinforced by yarns. The thermal decomposition of the automotive clutch friction composite system consisting of a polymer blend reinforced by yarns from organic, inorganic and metallic fibres impregnated with resin, as well as its individual components, was monitored by a method of non‐isothermal thermogravimetry over a wide temperature range. A supervised feed‐forward back‐propagation multi‐layer artificial neural network model, with temperature as the only input parameter, has been developed to predict the thermogravimetric curves of weight loss and time derivative of weight loss of studied friction composite system and its individual components acquired at a fixed constant heating rate under a pure dry nitrogen atmosphere at a constant flow rate. It has been proven that an optimized model with a 1‐25‐6 architecture of an artificial neural network trained by a Levenberg‐Marquardt algorithm is able to predict simultaneously all the analyzed experimental thermogravimetric curves with a high level of reliability and that it thus represents the highly effective artificial intelligence tool for the modelling of thermal stability also of relatively complicated friction composite systems.