The rising energy production costs and the increasing reliance on volatile renewable sources have driven the need for more efficient power system redispatch strategies. In this work, we re-interpret the redispatch problem as a multi-objective combinatorial optimization task within the Quadratic Unconstrained Binary Optimization (QUBO) framework, suitable for adiabatic quantum computing. Our contributions include a novel normalized unbalanced penalty method that integrates inequality constraints via a quadratic Taylor expansion and an$\alpha$-Expansion algorithm that allows us to address largescale redispatch instances and to integrate temporal adjacent state switching constraints directly into the algorithm. Our experiments are conducted on open data of the German power system. Our results, obtained via numerical simulation and from an actual D-Wave Advantage quantum annealer, validate the viability of our formulation and demonstrate that our algorithm scales to large problem instances.

In today's globalized markets, effectivity in the way that product development information is communicated and transparently interpreted by a diversity of divisions and disciplines in an enterprise has an essential impact on the key factors time, cost and quality. Against the background of current activities in the automotive industry, we have conducted a process chain analysis at multiple OEMs and suppliers, analyzing application potentials of JT as the format of origin specifically for CAx processes, such as Digital Mock-Up, Simulation and Downstream production. In this context, a simple application to investigate and manipulate JT data in terms of structure and properties would provide the means for prototypical integration tests. Connecting containers available in the JT Open Toolkit to those provided in the OpenSceneGraph (OSG) graphics toolkit, the fundamentals of such an application were developed and are presented in this paper.

The recently introduced notion of Finite-Time Lyapunov Exponent to characterize Coherent Lagrangian Structures provides a powerful framework for the visualization and analysis of complex technical flows. Its definition is simple and intuitive, and it has a deep theoretical foundation. While the application of this approach seems straightforward in theory, the associated computational cost is essentially prohibitive. Due to the Lagrangian nature of this technique, a huge number of particle paths must be computed to fill the space-time flow domain. In this paper, we propose a novel scheme for the adaptive computation of FTLE fields in two and three dimensions that significantly reduces the number of required particle paths. Furthermore, for three-dimensional flows, we show on several examples that meaningful results can be obtained by restricting the analysis to a well-chosen plane intersecting the flow domain. Finally, we examine some of the visualization aspects of FTLE-based methods and introduce several new variations that help in the analysis of specific aspects of a flow.