Effects of microreactor wall heat conduction on the reforming process of methane

In this paper, the effect of wall conduction of an autothermal tubular methane microreformer is investigated numerically. It is found that the axial wall conduction can strongly influence the performance of the microreactor and should not be neglected without a careful a priori investigation of its impact. By increasing the wall thermal conductivity, the maximum wall surface temperature is decreased. Due to the complex exothermic–endothermic nature of the chemistry of reforming, the axial variation of the wall temperature is not monotonic. Methane conversion and hydrogen yield are strongly dependent on the wall inner surface temperature, hence the heat conduction through the channel wall. The equivalence ratio and the wall thickness also significantly affect the reforming effectiveness and must be carefully considered in reactor optimization. Furthermore, it is found that exothermic oxidation reaction mechanisms, especially partial oxidation, are responsible for syngas (hydrogen and carbon monoxide) production near the inlet. Farther downstream, in the oxygen deficient region, endothermic steam reforming is the main hydrogen producing mechanism. By increasing the thermal conductivity, steam reforming becomes stronger and partial oxidation becomes weaker. For all investigated inlet conditions, the highest hydrogen yield is obtained for no or very low conductive walls.     

On the correspondence between abstract dialectical frameworks and nonmonotonic conditional logics

Annals of Mathematics and Artificial Intelligence - The exact relationship between formal argumentation and nonmonotonic logics is a research topic that keeps on eluding researchers despite recent...     

Influence of the Workpiece Stiffness on the Electromagnetic Sheet Metal Forming Process into Dies

Electromagnetic sheet metal forming is a high speed forming process using pulsed magnetic fields to form metals with high electrical conductivity such as aluminum. Thereby, workpiece velocities of more than 300 m/s are achievable, which can cause difficulties when forming into a die. The kinetic energy, which is related to the workpiece velocity, must be dissipated in a short time slot when the workpiece hits the die; otherwise undesired effects, for example rebound can occur. One possibility to handle this shortcoming is to locally increase the stiffness of the workpiece. A modal analysis is carried out in order to determine the stiffness of specific regions of the workpiece so that an estimation concerning the feasibility of the desired geometry is possible in advance without doing cost and time consuming experiments. Thereby, the desired geometry of the workpiece will be fractionized in significant sectors. This approach has to define the internal force variables acting on the cutting edge, which are required to constrain the numerical model. Finally, a method will be developed with the objective of calculating the stiffness of each sector. The numerical results will be verified by experiments. This article was presented at Materials Science & Technology 2006, Innovations in Metal Forming symposium held in Cincinnati, OH, October 15-19, 2006.     

Surface reconstruction for incremental forming

In spite of extensive efforts being made with regard to virtual process optimization technology, the production of prototype parts is still a necessity. With respect to the production of sheet metal parts in low quantities, incremental sheet metal forming (ISMF) is a highly interesting process. ISMF allows the production of complex parts with drastically reduced costs in tooling and machinery compared to conventional processes like deep drawing. However, ISMF, with it’s incremental nature, introduces the need for generating a tool path considering both final geometry and process-induced deviations or constraints. Consequently, for the generation of the tool path a (tool path) surface, with an adequate offset, is necessary. That is why, within the scope of extensive research work at the Institute of Forming Technology and Lightweight Construction (IUL), a special correction module has been developed, determining this offset e.g. depending on the workpiece geometry. This paper presents the algorithm, the application, and the effect on the produced parts. Furthermore, a concept for an extension regarding further constraints like elastic workpiece behavior is presented.     

Investigation of wetting behaviour of hardenable copper based-alloys for brazing applications

ABSTRACT

Tools for machining are exposed to high loads, wear, and elevated temperatures. Commonly, such tools consist of cemented carbides and tool steel. To combine the advantages of both materials, high-quality-joints with high strengths are desired. When brazing these materials, the main challenge is the mismatch of the Coefficient of Thermal Expansion (CTE) and the poor wettability of cemented carbides by molten filler alloys. In this regard, the feasibility of two custom-made alloys (CuNi12Si5, CuNi12Si5B0.4) was analysed. Besides being a cost-efficient alternative, these alloys offer the possibility to modify their mechanical properties by precipitation hardening to reduce stresses within the final joints. Thus, this paper shows that a temperature of 1060°C is suitable for wetting and brazing tests on different substrates.     

Insight into spontaneous recurrent calcium waves in a 3-D cardiac cell based on analysis of a 1-D deterministic model

Calcium dynamics in a cardiac cell are described by a system of 3-D non-linear stochastic partial differential equations. To obtain solutions that have biophysical properties, it is necessary to explore the model parameter space. To decrease the complexity of the parameter search, we reduce the 3-D stochastic model to a 1-D deterministic model. The reduction of the problem from 3-D to 1-D is done through an asymptotic approximation after non-dimensionalization and based on rational biophysical assumptions of the 3-D domain; the stochastic to deterministic transformation is based on the regular property of the 3-D solution. The result of the model reduction proves very effective in reducing the time required to get qualitative as well as quantitative information about parameter regions in the 3-D stochastic model including calcium dynamics (sparks, wave propagation, and recovery) observed in cardiac cells.     

Business process compliance checking – applying and evaluating a generic pattern matching approach for conceptual models in the financial sector

Given the strong increase in regulatory requirements for business processes the management of business process compliance becomes a more and more regarded field in IS research. Several methods have been developed to support compliance checking of conceptual models. However, their focus on distinct modeling languages and mostly linear (i.e., predecessor-successor related) compliance rules may hinder widespread adoption and application in practice. Furthermore, hardly any of them has been evaluated in a real-world setting. We address this issue by applying a generic pattern matching approach for conceptual models to business process compliance checking in the financial sector. It consists of a model query language, a search algorithm and a corresponding modelling tool prototype. It is (1) applicable for all graph-based conceptual modeling languages and (2) for different kinds of compliance rules. Furthermore, based on an applicability check, we (3) evaluate the approach in a financial industry project setting against its relevance for decision support of audit and compliance management tasks.     

A Python extension for the massively parallel multiphysics simulation framework waLBerla

We present a Python extension to the massively parallel HPC simulation toolkit waLBerla. waLBerla is a framework for stencil based algorithms operating on block-structured grids, with the main application field being fluid simulations in complex geometries using the lattice Boltzmann method. Careful performance engineering results in excellent node performance and good scalability to over 400,000 cores. To increase the usability and flexibility of the framework, a Python interface was developed. Python extensions are used at all stages of the simulation pipeline: they simplify and automate scenario setup, evaluation, and plotting. We show how our Python interface outperforms the existing text-file-based configuration mechanism, providing features like automatic nondimensionalization of physical quantities and handling of complex parameter dependencies. Furthermore, Python is used to process and evaluate results while the simulation is running, leading to smaller output files and the possibility to adjust parameters dependent on the current simulation state. C++ data structures are exported such that a seamless interfacing to other numerical Python libraries is possible. The expressive power of Python and the performance of C++ make development of efficient code with low time effort possible.