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From Start to Finish - A Process of Using Simulation Software in Energy Research Projects
Full text linkSimulation software is crucial in energy research, serving as a key tool for analyzing complex systems and testing innovative solutions. Simulations are used in this context because real-world testing is typically expensive and time-consuming and may jeopardize the stability and safety of critical infrastructure systems. As part of NFDI4Energy, we are developing services to support researchers in effectively integrating simulation into their workflows.
To better understand the research community\u27s needs, we developed and analyzed multiple use cases that illustrate the diverse simulation-based processes in energy research. Based on these, we designed a structured process model that guides the use of simulation software, from planning and the initial setup over the execution to sharing results following the FAIR principles. Notably, the process also emphasizes the value of sharing simulation models and software, not just data, via dedicated software registries, thus enabling research data management.
Our goal within NFDI4Energy is to create new tools and services while integrating and connecting existing solutions through a shared service portfolio. This paper presents an overview of the identified requirements and the conceptual design of a Simulation-as-a-Service (SimaaS) approach tailored to the energy research domain, offering early insights into a potential future service landscape
Existence of traveling breather solutions to cubic nonlinear Maxwell equations in waveguide geometries
Full text linkWe consider the full set of Maxwell equations in a slab or cylindrical waveguide with a cubically nonlinear material law for the polarization of the electric field. The nonlinear polarization may be instantaneous or retarded, and we assume it to be confined inside the core of the waveguide. We prove existence of infinitely many spatially localized, real-valued and time-periodic solutions (breathers) propagating inside the waveguide by applying a variational minimization method to the resulting scalar quasilinear elliptic-hyperbolic equation for the profile of the breathers. The temporal period of the breathers has to be carefully chosen depending on the linear properties of the waveguide. As an example, our results apply if a two-layered linear axisymmetric waveguide is enhanced by a third core region with low refractive index where also the nonlinearity is located. In this case we can also connect our existence result with a bifurcation result. We illustrate our results with numerical simulations. Our solutions are polychromatic functions in general, but for some special models of retarded nonlinear material laws, also monochromatic solutions can exist. In this case the numerical simulations raise an interesting open question: are the breather solutions with minimal energy monochromatic or polychromatic
An Extended Krylov Subspace Method for Decoding Edge‐Based Compressed Images by Homogeneous Diffusion
Full text linkThe heat equation is often used to inpaint dropped data in inpainting-based lossy compression schemes. We propose an alternative way to numerically solve the heat equation by an extended Krylov subspace method. The method is very efficient with respect to the computation of the solution of the heat equation at large times. And this is exactly what is needed for decoding edge-compressed pictures by homogeneous diffusion
Beschleunigtes Materialdesign durch künstliche Intelligenz im Forschungsdatenmanagement
Full text linkAm Beispiel von Polyurethanschaumstrukturen entwickelt diese Arbeit einen modularen, FAIRen Workflow für datengetriebene Materialentwicklung. Über KI-basierte Segmentierung, generative 3D-Modelle und Simulationen werden mikrostrukturelle Eigenschaften automatisiert analysiert und mechanische Kennwerte zuverlässig vorhergesagt. Die generischen Workflows und eine transparente Datenverwaltung beschleunigen den Entwicklungsprozess und lassen sich flexibel auf andere Materialien übertragen
Engineering Manganese Oxide‐Decorated Carbon Stacks with Layered‐Inspired Architecture for Lithium‐Ion Capacitors
No full textEngaging Schools and Communities in Geothermal Monitoring Case Studies from the DeepStor Research Infrastructure
Full text linkSeismic Imaging and Monitoring with Distributed Acoustic Sensing on Dark Fibers at the KIT Campus
Full text linkSeismic monitoring is essential for the successful and sustainable exploration and operation of underground reservoirs and storage systems. Distributed Acoustic Sensing (DAS) has emerged as a solution for the acquisition of seismic data with high spatial density and extensive coverage, benefiting seismic monitoring efforts. Making use of unused telecommunication fibers, or dark fibers, is a particularly attractive opportunity due to the widespread availability of this infrastructure. It can help address the challenges associated with deploying and maintaining extensive seismic networks, particularly in urban areas targeted for geothermal energy development. This study uses a 3 km section of the telecommunication network at the Karlsruhe Institute of Technology (KIT) to conduct seismic monitoring near the planned DeepStor geothermal research infrastructure. The research includes a preliminary verification of the fiber\u27s location and reports observations from local seismic events, harnessing the high spatial density of sensing points for beamforming analysis. Additionally, a signal classification framework is designed to detect and categorize frequent vehicle passages. The analysis of the associated signals makes it possible to extract virtual shot gathers. These gathers facilitate the analysis of dispersion curves at relatively high frequencies, which are subsequently used to invert shear-wave velocity profiles. This complements lower-frequency analyses derived from microseism signals during periods of minimal anthropogenic activity. Continuous seismic wavefield recordings were collected over an eight-month period, providing access to a significant time series for analysis of temporal variations and signal stacking. Our results provide a basis for future seismic monitoring of the upcoming DeepStor research infrastructure on the KIT Campus North. They also demonstrate the potential of ambient seismic wavefield analysis for advanced subsurface characterization and contribute to the broader application of DAS technology in urban seismic monitoring
A Mg²⁺-Regulated Hydrated Vanadium Oxide Positive Electrode for Aqueous Mg-Ion Batteries
Full text linkAqueous Mg-ion batteries (AMIBs) have emerged as promising candidates for grid-level energy storage systems, thanks to their exceptional safety characteristics, cost-effectiveness, and abundant Mg resources. However, AMIBs confront great challenges, such as the shortage of high-performance electrodes and the sluggish Mg2+ diffusion in the electrodes. In this work, a Mg2+-regulated bilayered vanadium oxide (MgVOnH) positive electrode, holding a large interplanar spacing of ∼13.4 Å, was investigated in 0.8 m Mg(TFSI)2–85% poly(ethylene glycol) (PEG)–15% H2O and 0.8 m Mg(TFSI)2–65% PEG–20% dimethyl sulfoxide (DMSO)–15% H2O (20% DMSO-containing) electrolytes. MgVOnH delivers a first discharge capacity of 268 mAh g–1 at 50 mA g–1, obtaining 81% capacity retention after 100 cycles (against a second discharge capacity of 249 mAh g–1) in a DMSO-free electrolyte, whereas MgVOnH exhibits much better rate capability and high capacity at 500 and 1000 mA g–1 in the DMSO-containing electrolyte, respectively. Particularly, MgVOnH shows a first discharge capacity of 106 mAh g–1 at 1000 mA g–1, maintaining 80/65% of its capacity after 920/2000 cycles. Furthermore, the electrochemical reaction mechanism and reversibility of MgVOnH during Mg2+ (de)intercalation are systematically explored through ex situ techniques. This work helps us to understand the mechanisms, and this can guide us in achieving a better design for high-performance positive electrodes for AMIBs
Efficient accelerator operation with artificial intelligence based optimization methods
Full text linkPoster of IPAC´25 conference: Tuning injectors is a challenging task for the operation of accelerator facilities and synchrotron light sources, particularly during the commissioning phase. Efficient tuning of the transfer line is essential for ensuring optimal beam transport and injection efficiency. This process is further complicated by challenges such as beam misalignment in quadrupole magnets, which can degrade beam quality and disrupt operations. Traditional tuning methods are often time-consuming and insufficient for addressing the complexities of high-dimensional parameter spaces. In this work, we explore the use of advanced AI methods, including Bayesian optimization, to automate and improve the tuning process. Initial results, demonstrated on the transfer line of KARA (Karlsruhe Research Accelerator) at KIT (Karlsruhe Institute of Technology), show promising improvements in beam alignment and transport efficiency, representing first steps toward more efficient and reliable accelerator operation. This study is part of the RF2.0 project, funded by the Horizon Europe program of the European Commission, which focuses on advancing energy-efficient solutions for particle accelerators
