Creep testing of carbon containing refractories under reducing conditions

Mechanical testing of carbon containing refractories at high temperatures requires measures to protect the sample from oxidation. Therefore, special setups for tensile and compressive creep testing were developed to prevent the oxidation of carbon in the sample. A MgO-C refractory was selected for a case study. These developments allow the quantification of the tensile and compressive creep behaviour of MgO-C refractories at temperatures up to 1500?°C. The creep parameters are determined by an inverse evaluation method for the obtained experimental data. They enable the consideration of creep in a thermomechanical finite element simulation of refractory linings in service.     

Expanding the Toolbox of R-Selective Amine Transaminases by Identification and Characterization of New Members

Amine transaminases (ATAs) are used to synthesize enantiomerically pure amines, which are building blocks for pharmaceuticals and agrochemicals. R-selective ATAs belong to the fold type IV PLP-dependent enzymes, and different sequence-, structure- and substrate scope-based features have been identified in the past decade. However, our knowledge is still restricted due to the limited number of characterized (R)-ATAs, with additional bias towards fungal origin. We aimed to expand the toolbox of (R)-ATAs and contribute to the understanding of this enzyme subfamily. We identified and characterized four new (R)-ATAs. The ATA from Exophiala sideris contains a motif characteristic for d -ATAs, which was previously believed to be a disqualifying factor for (R)-ATA activity. The crystal structure of the ATA from Shinella is the first from a Gram-negative bacterium. The ATAs from Pseudonocardia acaciae and Tetrasphaera japonica are the first characterized (R)-ATAs with a shortened/missing N-terminal helix. The active-site charges vary significantly between the new and known ATAs, correlating with their diverging substrate scope.     

Sugar replacement in sweetened bakery goods

This review presents the state‐of‐the‐art concerning the application of natural and artificial high‐intensity sweeteners, fructans and bulking agents such as polyols as sugar replacers in sweet‐baked goods and their effects on product characteristics. The recent much publicised attention given to weight gain of the population and its consequences on the occurrence of diet‐related diseases in developed countries has influenced the food manufacturers attempts to provide the consumer with reduced energy products. The replacement of sucrose in sweet bakery products by alternative natural or artificial sweeteners can be a challenging issue. Sucrose as a main ingredient in sweet bakery products contributes, aside from providing sweetness, to numerous processing and product characteristics. Intense sweeteners have a high sweetness compared with sucrose but lack in their contribution to the body of the product, whereas the replacement of sucrose with bulking sweeteners may result in products with a similar body but a lack in taste and flavour.     

A middleware platform for the dynamic evolution of distributed component-based systems

In this paper, we present a middleware platform that supports the dynamic evolution of distributed component-based systems. It leverages the concept of ontologies to model the context of a system and an intrinsic mechanism is integrated to causally connect the dynamic architecture specification to the running system implementation. The ontological modeling covers both the environmental and the architectural knowledge using semantic data modeling. The intrinsic mechanism can automatically derive a run-time polymorphic architecture object to coordinate the involved components. The ontology based contextual representation and the polymorphic architecture-driven dynamic evolution are the two underpinnings of the platform. A scenario application—including the two primitive evolution actions—with the performance analysis is discussed to illustrate the feasibility.     

A comparison between state-of-the-art and neural network modelling of solar collectors

The state-of-the-art modelling of solar collectors as described in the European Standard EN 12975-2 is based on equations describing the thermal behaviour of the collectors by characterising the physical phenomena, e.g. transmission of irradiance through transparent covers, absorption of irradiance by the absorber, temperature dependent heat losses and others. This approach leads to so called collector parameters that describe these phenomena, e.g. the zero-loss collector efficiency η₀ or the heat loss coefficients a₁ and a₂.Although the state-of-the-art approach in collector modelling and testing fits most of the collector types very well there are some collector designs (e.g. “Sydney” tubes using heat pipes and “water-in-glass” collectors) which cannot be modelled with the same accuracy than conventional collectors like flat plate or standard evacuated tubular collectors. The artificial neural network (ANN) approach could be an appropriate alternative to overcome this drawback.To compare the different approaches of modelling investigations for a conventional flat plate collector and an evacuated “Sydney” tubular collector have been carried out based on performance measurements according to the European Standard EN 12975-2. The investigations include the parameter identification (training), the comparisons between measured and modelled collector output and the simulated yearly collector yield for a solar domestic hot water system for both models.The obtained results show better agreement between measured and calculated collector output for the artificial neural network approach compared with the state-of-the-art modelling. The investigations also show that for the ANN approach special test sequences have to be designed and that the determination of the ANN that fits the thermal performance of the collector in the best way depends significantly on the expertise of the user.Nevertheless artificial neural networks have the potential to become an interesting alternative to the state-of-the-art collector models used today.     

DEM‐CFD modeling of particle systems with long‐range electrostatic interactions

To investigate dynamic behaviors of monocharged particle systems, a direct truncation (DT) method and a hybrid particle‐cell (HPC) method are implemented into the discrete element method coupled with computational fluid dynamics (DEM‐CFD) with defined cutoff distances. The DT method only considers electrostatic interactions between particles within the cutoff distance while the HPC method computes electrostatic interactions in the entire computational domain. The deposition process of monocharged particles in a container in air was simulated using the developed DEM‐CFD. It was found that using the DT method, the macrostructure, evolution of granular temperature, and radial distribution function of the particle system were sensitive to the specified cutoff distance. In contrast, using the HPC method, these results were independent of the specified cutoff distance, as expected. This implies that, although electrostatic interactions between particles with large separation distances are weak, they should be considered in DEM‐CFD for accurate modeling of charged particle systems. © 2015 The Authors AIChE Journal published by Wiley Periodicals, Inc. on behalf of American Institute of Chemical Engineers AIChE J, 61: 1792–1803, 2015