University of Applied Sciences of Eastern Switzerland

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Smajic J.,ETH Zurich | Smajic J.,University of Applied Sciences of Eastern Switzerland
IEEE CEFC 2016 - 17th Biennial Conference on Electromagnetic Field Computation | Year: 2016

A semi-explicit time domain method for solving eddy-current problems is presented. The suggested method is based on the discontinuous Galerkin (DG) finite element approach and the H-Φ formulation of eddy-current problem. The DG-technique allows for explicit time stepping in electrically conducting domains without solving a large sparse ill-conditioned linear equation system. The H-Φ field formulation enables the use of scalar magnetic potential in electrically non-conducting domains that are discretized by using traditional nodal finite elements. The application of the method is illustrated by a three-dimensional example and the obtained results are verified by comparison with the corresponding frequency domain solution. © 2016 IEEE.


Tokic A.,TuzlaUniversity | Smajic J.,University of Applied Sciences of Eastern Switzerland
IEEE Transactions on Power Delivery | Year: 2015

The predictive power of transient ferroresonance simulations depends mainly on the accuracy and fidelity of the power transformer model used for simulating complete systems involving all relevant network components. This paper considers three ways of transformer iron-core modeling relevant for ferroresonance simulations that are presented in detail. The presented transformer models are suitable for the state-space form of differential equation systems that describe the ferroresonance effect. Before solving the obtained differential equation systems, their numerical eigenvalues were analyzed in detail. This eigenvalue analysis has revealed a very stiff nature of the obtained equation systems. The obtained equation systems are solved by using a A-and L-stable numerical differentiation formulas (NDF) numerical technique, with the aim of suppressing undesired numerical oscillations. The obtained numerical results are verified by comparison against the available experimental results. The presented analysis shows that the suggested transformer model based on a hysteretic core inductor provides the most accurate results in terms of voltage and current waveforms and their peak values during the steady-state and transient ferroresonance. The analyzed transformer core models can be implemented in the existing Electromagnetic Transients Program-type simulation tools by using a combination of the trapezoidal and proposed NDF2 method. © 1986-2012 IEEE.


Tokic A.,University of Tuzla | Jukan A.,University of Tuzla | Smajic J.,University of Applied Sciences of Eastern Switzerland
IEEE Transactions on Power Delivery | Year: 2016

The recent rapid concentration increase of single-phase rectifier-based loads has led to the increasingly significant problem of current and voltage distortion in low-power electrical networks. To successfully perform a prediction of the current and voltage distortion in power systems due to such nonlinear loads, it is necessary to know the structure and model parameters of those power-electronics circuits. Generally speaking, since the structure of a typical single-phase rectifier-based load is rather known, the parameters of those loads remain to be determined. Concerning this matter, an algorithm for estimating the unknown parameters of a typical single-phase rectifier based load is presented in this paper. The algorithm is based on a general approach for determining analytically the waveform of the ac load current and the dc capacitor voltage within an arbitrary number of time periods. The described nonlinear load model along with the model parameters obtained by using the suggested estimation algorithm were verified by comparison against a laboratory-designed typical rectifier-based load. Excellent agreement between the estimated and measured load parameters, as well as between the measured and simulated current and voltage waveforms was found. © 1986-2012 IEEE.


Zdun U.,University of Vienna | Capilla R.,Rey Juan Carlos University | Tran H.,University of Vienna | Zimmermann O.,University of Applied Sciences of Eastern Switzerland
IEEE Software | Year: 2013

Software architects must sustain design decisions to endure throughout software evolution. Several criteria can help them assess decisions' sustainability. In addition, industry and research projects have applied different techniques to make architectural design decisions sustainable; their examples offer solutions and lessons learned. © 2013 IEEE.


Koller R.,University of Applied Sciences of Eastern Switzerland | Schmid L.,University of Applied Sciences of Eastern Switzerland | Matsuda N.,Northwestern University | Niederberger T.,University of Applied Sciences of Eastern Switzerland | And 4 more authors.
Optics Express | Year: 2015

We present a prototype compressive video camera that encodes scene movement using a translated binary photomask in the optical path. The encoded recording can then be used to reconstruct multiple output frames from each captured image, effectively synthesizing high speed video. The use of a printed binary mask allows reconstruction at higher spatial resolutions than has been previously demonstrated. In addition, we improve upon previous work by investigating tradeoffs in mask design and reconstruction algorithm selection. We identify a mask design that consistently provides the best performance across multiple reconstruction strategies in simulation, and verify it with our prototype hardware. Finally, we compare reconstruction algorithms and identify the best choice in terms of balancing reconstruction quality and speed. © 2015 Optical Society of America.


Zimmermann O.,University of Applied Sciences of Eastern Switzerland
IEEE Software | Year: 2015

A refactoring aims to improve a certain quality while preserving others. For example, code refactoring restructures code to make it more maintainable without changing its observable behavior. Given the success of code refactoring, it's surprising that architectural refactoring (AR) hasn't taken off yet. This article examines AR from a new angle: as an evolution technique that revisits architectural decisions and identifies related design, implementation, and documentation tasks. © 2015 IEEE.


Pautasso C.,University of Lugano | Zimmermann O.,University of Applied Sciences of Eastern Switzerland
IEEE Software | Year: 2015

The column's new editors ask readers to participate, and they give guidelines for the type of articles they seek. © 2015 IEEE.


Zimmermann O.,University of Applied Sciences of Eastern Switzerland
Proceedings - 2nd International Workshop on Software Architecture and Metrics, SAM 2015 | Year: 2015

During architectural analysis and synthesis, architectural metrics are established tacitly or explicitly. In architectural evaluation, these metrics then can be consulted to assess whether architectures are fit for purpose and in line with recommended practices and published architectural knowledge. This experience report presents a personal retrospective of the author's use of architectural metrics during 20 years in IT architect roles in professional services as well as research and development. This reflection drives the identification of use cases, critical success factors and elements of risk for architectural metrics management. An initial catalog of architectural metrics is then compiled, which is organized by viewpoints and domains. The report concludes with a discussion of practical impact of architectural metrics and potential research topics in this area. © 2015 IEEE.


Zimmermann O.,University of Applied Sciences of Eastern Switzerland
Computing | Year: 2016

Unlike code refactoring of programs, architectural refactoring of systems is not commonly practiced yet. However, legacy systems typically have to be refactored when migrating them to the cloud; otherwise, these systems may run in the cloud, but cannot fully benefit from cloud properties such as elasticity. One reason for the lack of adoption of architectural refactoring is that many of the involved artefacts are intangible—architectural refactoring therefore is harder to grasp than code refactoring. To overcome this inhibitor, we take a task-centric view on the subject and introduce an architectural refactoring template that highlights the architectural decisions to be revisited when refactoring application architectures for the cloud; in this approach, architectural smells are derived from quality stories. We also present a number of common architectural refactorings and evaluate existing patterns regarding their cloud affinity. The final contribution of this paper is the identification of an initial catalog of architectural refactorings for cloud application design. This refactoring catalog was compiled from the cloud patterns literature as well as project experiences. Cloud knowledge and supporting templates have been validated via action research and implementation in cooperation with practitioners. © 2016 Springer-Verlag Wien


Behrmann G.,ABB | Smajic J.,University of Applied Sciences of Eastern Switzerland
IEEE Transactions on Dielectrics and Electrical Insulation | Year: 2016

This paper describes work done recently to characterize and better understand propagation of PD signals in the VHF and UHF bands in GIS. While carrying out a routine CIGRE TF 15/33.03.05 UHF PD Sensitivity Verification Step 1 Laboratory Test procedure, RF transmission measurements were made on the same GIS set-up employed for the CIGRE test, using an RF vector network analyzer. In addition, a comprehensive 3-D RF field simulation model of the set-up was created, based on the detailed design drawings of the GIS. The transmission measurements were simulated in the RF model and the results compared with the actual measurement data. This shows once again the extreme complexity of GIS as an RF signal propagation environment, the difficulty describing a transfer function or in extracting useful meaning from such measurements, set against the relative simplicity of the CIGRE procedure for establishing measurement sensitivity and guidelines for sensor placement. © 2016 IEEE.

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