This publication focuses on the production of low-cost prototypes of coaxial-waveguide transitions (CWTs) that achieve the performance level of industrial WR90 and WR187 CWTs. The assembly consists of a specially designed coupling element in stripline technology that merges into an SMA connector. It is embedded into a 3D printed housing treated with a metallic surface finishing to achieve compatibility with hollow waveguides. In the first part of this study, a copper spray varnish is used to create a conductive surface on the device under test (DUT). After assembly of the prototypes, network parameters will be extracted for one pair of transitions by carrying out a set of 2-port measurements. The individual performance of a singular DUT is then deembedded by using reference measurements of commercial-grade waveguides. This analysis shows that also S-parameter extraction on connectors with a poor transition is valid. Subsequently, the procedure for the developed WR90 CWT is applied to a WR187 waveguide standard, again followed by a performance analysis. The procedure briefly addresses the modified parameters and illustrates the results as S-parameters. A comparative analysis of the measurement results for each deembedded WR90 and WR187 prototype respectively, indicates a better performance for larger waveguide standards. In consistency with this observation, larger relative tolerances in manufacturing and difficulties in controlling a uniform metallization process are identified as the limiting factors of miniaturization. In the second part of this work, an alternative concept utilizing aluminum coating and a segmented manufacturing approach is developed, targeting reduced insertion loss but keeping the mechanical tolerance level. The redesign is based on the geometry of the prior WR90 prototype, but forming a plug-in kit with each body segment being clad in multiple thin layers of aluminum foil. The measurement results of these samples reveal the effects of increased conductivity and reduced irregularities in terms of significantly improved reflection and transmission parameters. The DUTs investigated in the third part of this work again originate from the initially manufactured variants. To investigate the effects of different metallic coatings, the copper varnish is now replaced by a silver based ink, which provides high conductivity and is therefore commonly used in additive manufacturing. The network measurements are repeatedly carried out with a varying number of layers of lacquer applications on the body's surface. By deembedding a singular part from the measurements, it is shown that increasing surface conductivity leads to a significant impact on transmission parameters. In direct comparison, the silver coated CWT outperforms both preceding variants with copper varnish or aluminum clad. With more than 95 % transmitted power, it is indeed competitive compared to the industrially manufactured WR90 CWT reference. To conclude, the study focuses on a comparison of three different additive manufacturing processes for equal hollow waveguide geometries at moderate frequencies. It proves that CWT parts are producible in a simple and rapid process. The production stages with the strongest impact on performance are identified and demonstrated to be controllable. The variant presented finally is able to achieve competitive performance compared to commercial-grade parts, especially when considering the enormous cost reduction. In addition, it is proven that the RF parameter extraction method for symmetric two-port networks presented earlier by the authors is also applicable when the DUT exhibits high insertion losses. The central aim of this work is to demonstrate that additive manufacturing combined with low-cost metallization techniques can produce coaxial-waveguide transitions that approach the performance of industrial WR90 standards. This novelty highlights the feasibility of achieving near-commercial-grade quality at a fraction of the cost, thereby extending the accessibility of high-frequency components to research and prototyping applications.

High-renewables grids are planned in min but judged in milliseconds; credible studies must therefore resolve both horizons within a single model. Current adequacy tools bypass fast frequency dynamics, while detailed simulators lack multi-hour optimization, leaving investors without a unified basis for sizing storage, shifting demand, or upgrading transfers. We present a two-layer Hierarchical Model Predictive Control framework that links 15-min scheduling with 1-s corrective action and apply it to Germany’s four TSO zones under a stringent zero-exchange stress test derived from the NEP 2045 baseline. Batteries, vehicle-to-grid, pumped hydro and power-to-gas technologies are captured through aggregators; a decentralized optimizer pre-positions them, while a fast layer refines setpoints as forecasts drift; all are subject to inter-zonal transfer limits. Year-long simulations hold frequency within ±2 mHz for 99.9% of hours and below ±10 mHz during the worst multi-day renewable lull. Batteries absorb sub-second transients, electrolyzers smooth surpluses, and hydrogen turbines bridge week-long deficits — none of which violate transfer constraints. Because the algebraic core is modular, analysts can insert new asset classes or policy rules with minimal code change, enabling policy-relevant scenario studies from storage mandates to capacity-upgrade plans. The work elevates predictive control from plant-scale demonstrations to system-level planning practice. It unifies adequacy sizing and dynamic-performance evaluation in a single optimization loop, delivering an open, scalable blueprint for high-renewables assessments. The framework is readily portable to other interconnected grids, supporting analyses of storage obligations, hydrogen roll-outs and islanding strategies.

This study investigates the effects of mechanical strain on the surface roughness of copper conductors, focusing on the electrolyte-refined copper (Cu-ETP, CW004A) used in H07V-U 1.5 mm2 single-core cables. For the first time, the surface roughness evolution is characterized using the power spectral density (PSD) function, enabling a detailed roughness analysis across different spatial length scales. Conductors were subjected to mechanical stress, with measurements taken at multiple stages of service life. The study confirms the results from other studies that surface roughness increases significantly in the early stages of loading, with a plateau observed in 50 % - 75 % of cycles to failure. Micro crack formation and material extrusion are identified as key mechanisms driving roughness growth, especially at small length scales, with a shift towards larger length scales as strain intensifies. The increasing Hurst exponent suggests a transformation from a random to a more persistent and correlated surface. The results underscore the potential of power spectral density analysis in understanding surface behavior in copper conductors.

Natural fiber-reinforced polymers are gaining popularity as sustainable structural materials. However, their inherent variability can limit their reliability in load-bearing applications. To address this issue, we investigate a novel structural health monitoring method that leverages mechanoelectrical effects in flax fiber-reinforced epoxy composites. In our study, a contactless capacitive coupled measurement setup records electrical polarization during fatigue testing at four load levels. The polarization signals we observed increased with increasing load levels. Additionally, changes in polarization correlate with changes in dynamic modulus, providing early indicators of potential failure. This work lays the foundation for a new type of structural health monitoring in natural fiber-reinforced polymers.

Control rooms play a crucial role in monitoring and managing safety-critical systems, such as power grids, emergency response, and transportation networks. As these systems become increasingly complex and generate more data, the role of human operators is evolving amid growing reliance on automation and autonomous decision-making. This paper explores the balance between leveraging automation for efficiency and preserving human intuition and ethical judgment, particularly in high-stakes scenarios. Through an analysis of control room trends, operator attitudes, and models of human-computer collaboration, this paper highlights the benefits and challenges of automation, including risks of deskilling, automation bias, and accountability. The paper advocates for a hybrid approach of collaborative autonomy, where humans and systems work in partnership to ensure transparency, trust, and adaptability.