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The purpose of this paper is to introduce a new method to model a stranded wire efficiently in 3D finite element simulations.

In this method, the stranded wires are numerically approximated with the Cauer ladder network (CLN) model order reduction method in 2D. This approximates the eddy current effect such as the skin and proximity effect for the whole wire. This is then projected to a mesh which does not include each strand. The 3D fields are efficiently calculated with the CLN method and are projected in the 3D geometry to be used in simulations of electrical components with a current vector potential and a homogenized conductivity at each time step.

In applications where the stranded wire geometry is known and does not change, this homogenization approach is an efficient and accurate method, which can be used with any stranded wire configuration, homogenized stranded wire mesh and any input signal dependent on time steps or frequencies.

In comparison to other methods, this method has no direct frequency dependency, which makes the method usable in the time domain for an arbitrary input signal. The CLN can also be used to interconnected stranded cables arbitrarily in electrical components.

This paper aims to solve the parameter identification problem to estimate the parameters in electrochemical models of the lithium-ion battery.

The parameter estimation framework is applied to the Doyle-Fuller-Newman (DFN) model containing a total of 44 parameters. The DFN model is fit to experimental data obtained through the cycling of Li-ion cells. The parameter estimation is performed by minimizing the least-squares difference between the experimentally measured and numerically computed voltage curves. The minimization is performed using a state-of-the-art hybrid minimization algorithm.

The DFN model parameter estimation is performed within 14 h, which is a significant improvement over previous works. The mean absolute error for the converged parameters is less than 7 mV.

To the best of the authors’ knowledge, application of a hybrid optimization framework is new in the field of electrical modelling of lithium-ion cells. This approach saves much time in parameterization of models with a high number of parameters while achieving a high-quality fit.

This paper aims to present a fully coupled thermo-electrical finite-element battery model with an applied model-order reduction. The model is used to analyse the thermal design of battery modules during typical drive-cycles of electric vehicles.

A model-order reduction is applied, in which the electrical linear bus-bars are analysed in an a-priori step. For these bus-bars, special distributed basis-functions are computed, which make the solution of differential Ohm's law unnecessary during the transient simulation. Furthermore, the distributed basis-functions are used to strongly couple the non-linear battery models, which reduces the iterations needed to simulate them.

Altogether, this results in a fast simulation scheme for coupled linear and non-linear electrical components and their thermal behaviour.

The presented method delivers an innovative approach, on how to systematically minimize the computational effort in a system of linear and non-linear electrical components, while keeping the full three-dimensional information of the original problem.

The need to optimize and simulate lithium-ion cells is of high importance to their durability. It is possible to use semi-empirical models based on equivalent circuits to model the dynamic behavior. Still, parameter identification is a time consuming task if many equivalent circuits are coupled into a finite element-based simulation. The paper aims to discuss these issues.

In this paper the authors present an approach to estimate parameters in a very efficient way by using a single equivalent circuit model as a surrogate model on measurement data. The results of the surrogate model are periodically linked back to the original complex model via the so called space mapping method. The authors validate the approach and compare it to the original problem.

As a remarkable result, the authors report the achieved reduction of computational cost by approximately 87 percent, which equals a speed up factor of 8.

To the best of the authors’ knowledge, using high and low fidelity semi-empirical models combined with space mapping is new in the field of electrical modeling of lithium-ion cells. This approach saves much time in parameterization of coupled models while maintaining high quality results for geometrical and thermal optimization of lithium-ion cells.

This chapter focusses on current debates on ‘locating metal’ and on the demand for more theoretical and methodological rigor in metal studies. As an example of the usage of a non-English language in metal, the author examines the empirical case of the usage of Austrian German and Austrian dialects in metal music since around 1990. Herein, the author will be using the disciplinary methodologies of history and analyse the two Austrian bands Alkbottle and Varulv. According to the theory of ‘sonic knowledge’, the case study is interpreted as an example of ‘locating metal’ that occurred in the Austrian metal scene. The chapter shows that the seemingly contradictory coexistence of both deconstructive irony and essentialist nationalism is characteristic of the usage of Austrian German in metal. To conclude, the author proposes that this paradox is a result of the broad cultural history of Austrian nation building after 1945. The paradox of the usage of Austrian dialects in metal is the metal scene's attempt at coping with the frictions of Austria's twentieth century history.

The purpose of the present paper is to describe a web-based consensus-finding procedure, resulting in an agreement among the group of participants representing global stakeholders regarding the interdisciplinary topic in a university master's seminar on “Global Studies”. The result of the collectively elaborated solution pertains to the forward-looking and jointly agreed topic of migration policies.

The core part of the web-based negotiation game “Surfing Global Change” utilised here is a controversial group discussion. A subsequent step creates an agreement among discussants. The group of participants, in this case co-authors of this paper, developed a final agreement on possible future political adaptations and guidelines to improve current standards in the global management of refugee and migration issues.

The findings offer several political possibilities for European and African states including structural recommendations as well as cooperative development policies.

The result is a catalogue of tentative recommendations to improve international policies relating to current migration problems, here focused on migration between Africa and Europe.

Considering the creativity of the entire procedural structure combined with an ordered scientific methodology, the outcome could promise an interdisciplinary result. Effects of group dynamics, cooperation, scientific research and diplomacy are integrated into consensus building.