Data-driven parameterization of polymer electrolyte membrane fuel cell models via simultaneous local linear structured state space identification

In order to mitigate the degradation and prolong the lifetime of polymer electrolyte membrane fuel cells, advanced, model-based control strategies are becoming indispensable. Thereby, the availability of accurate yet computationally efficient fuel cell models is of crucial importance. Associated with this is the need to efficiently parameterize a given model to a concise and cost-effective experimental data set. A challenging task due to the large number of unknown parameters and the resulting complex optimization problem. In this work, a parameterization scheme based on the simultaneous estimation of multiple structured state space models, obtained by analytic linearization of a candidate fuel cell stack model, is proposed. These local linear models have the advantage of high computational efficiency, regaining the desired flexibility required for the typically iterative task of model parameterization. Due to the analytic derivation of the local linear models, the relation to the original parameters of the non-linear model is retained. Furthermore, the local linear models enable a straight-forward parameter significance and identifiability analysis with respect to experimental data. The proposed method is demonstrated using experimental data from a 30 kW commercial polymer electrolyte membrane fuel cell stack.     

Weighted fuzzy clustering for capability-driven service aggregation

Workflow design, mashup configuration, and composite service formation are examples where the capabilities of multiple simple services combined achieve a complex functionality. In this paper, we address the problem of limiting the number of required services that fulfill the required capabilities while exploiting the functional specialization of individual services. Our approach strikes a balance between finding one service that matches all required capabilities and having one service for each required capability. Specifically, we introduce a weighted fuzzy clustering algorithm that detects implicit service capability groups. The clustering algorithm considers capability importance and service fitness to support those capabilities. Evaluation based on a real-world data set successfully demonstrates the effectiveness of and applicability for service aggregation.     

Increase in Generation of Poly-Crystalline Silicon by Atmospheric Pressure Plasma-Assisted Excimer Laser Annealing

In this work, a novel atmospheric pressure plasma-assisted excimer laser annealing method for increasing the generation efficiency of poly-crystalline silicon from amorphous silicon layers is presented. Here, both the plasma and the laser propagate coaxially in order to generate energetic synergies. The influence of different process gases and plasma discharge modes as well as the working distance were investigated. Depending on the particularly applied plasma, the crystalline area was increased by a factor of approx. 1.1 to 1.9, where the highest efficiency was observed when introducing an argon plasma beam to the annealing process.     

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.     

Morphology,structure, and chemistry of nanoclusters in a mechanically alloyed nanostructured ferritic steel

Nanostructured ferritic steels have excellent elevated temperature strengths, creep resistances, and radiation tolerances due to the presence of a high density of Ti–Y–O-enriched nanoclusters. The compositions, morphologies, and structures of the smallest of these nanoclusters with maximum dimensions of ~2–4 nm were investigated in alloy 14YWT by high-resolution scanning transmission electron microscopy and atom probe tomography. Nanoclusters are found to be coherent with truncated rhombic dodecahedron morphologies defined by the {100} and {110} planes in the Fe matrix. Particles have compositions rich in Ti, O, Y, and Cr that are inconsistent with known oxide structures. The smallest nanoclusters appear to lack an identifiable crystal structure. Both nano-diffraction and focal series imaging through the sample thickness suggest that they are amorphous.     

CFD-Simulation eines direkt befeuerten Ofens zur Vorbehandlung feuerverzinkter Stahlbänder

For the production of high-quality goods in industrial furnaces using minimal expenditure of energy, optimization of the process parameters is required. One tool for improving the processes economically is the simulation of the furnaces by using Computational Fluid Dynamics (CFD). The pre-heating process of a steel strip in a section of an annealing furnace for surface treatment in a hot-dip galvanizing process was simulated using the commercial CFD software Ansys Fluent 15.0. For combustion, the Equilibrium model is used, turbulence is modeled by the realizable-k-ε model, and radiation is taken into account by using the Discrete Ordinate Method (DOM).     

Human factors in order picking: a content analysis of the literature

Order picking (OP) is one of the most labour- and time-intensive processes in internal logistics. Over the last decades, researchers have developed various mathematical planning models that help to increase the efficiency of OP systems, for example, by optimising storage assignments or by specifying routes for the order pickers that minimise travel distance in the warehouse. Human characteristics that are often a major determinant of OP system performance have, however, widely been ignored in this stream of research. This paper systematically evaluates the literature on manual OP systems and conducts a content analysis to gain insights into how human factors (HF) have been considered and discussed in the scientific literature. The results of the analysis indicate that management-oriented efficiency criteria dominated prior research on OP, and that there is a clear lack of attention to HF in the design and management of OP systems. This poses an opportunity for research and design of manual OP systems.     

Supporting the design of data integration requirements during the development of data warehouses: a communication theory-based approach

Data warehouses (DW) form the backbone of data integration that is necessary for analytical applications, and play important roles in the information technology landscape of many industries. We introduce an approach for addressing the fundamental problem of semantic heterogeneity in the design of data integration requirements during DW development. In contrast to ontology-driven or schema-matching approaches, which propose the automatic resolution of differences ex-post, our approach addresses the core problem of data integration requirements: understanding and resolving different contextual meanings of data fields. We ground the approach firmly in communication theory and build on practices from agile software development. Besides providing relevant insights for the design of data integration requirements, our findings point to communication theory as a sound underlying foundation for a design theory of information systems development.