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Erweiterung eines modellbasierten Rekonfigurationsansatzes für hybride Systeme am Beispiel des Lebenserhaltungssystems (ECLSS) des Columbus-Moduls der ISS
No full textCyber-physische Systeme (CPS) unterliegen verschiedenen Fehlern aufgrund von versagenden Aktoren, Sensoren oder strukturellen Komponenten. Die zunehmende Größe und Komplexität moderner Systeme führen zu kostspieliger und zeitaufwändiger manueller Fehlerbehandlung. Um eine autonome Anpassung von Systemen an Fehler zu ermöglichen, ist es notwendig, eine Rekonfiguration durchzuführen, bei der eine neue gültige Konfiguration identifiziert wird, die den Betrieb wiederherstellt. Dieser Beitrag präsentiert eine Weiterentwicklung früherer Arbeiten zur Anpassung des AutoConf-Algorithmus für die Rekonfiguration von Systemen mit seriell eingeschränkten Eingängen (serially constrained systems, bzw. SCI-Systeme). Die Implementierung basiert auf einem rekursiven Durchlauf eines gerichteten azyklischen Graphen (DAG) als Systemrepräsentation und ist in aussagenlogischer Formulierung abgefasst. Der entwickelte Algorithmus DAG2SAT wird anhand eines einfachen SCI-Systems veranschaulicht und dann auf das Environmental Control and Life Support System (ECLSS) - das Lebenserhaltungssystem im COLUMBUS-Modul der ISS angewendet und gegen verschiedene synthetische Fehlerfälle getestet.Vo
Machine-learning-enabled comparative modelling of the creep behaviour of unreinforced PBT and short-fibre reinforced PBT using prony and fractional derivative models
No full textThis article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).This study presents an approach based on data-driven methods for determining the parameters needed to model time-dependent material behaviour. The time-dependent behaviour of the thermoplastic polymer polybutylene terephthalate is investigated. The material was examined under two conditions, one with and one without the inclusion of reinforcing short fibres. Two modelling approaches are proposed to represent the time-dependent response. The first approach is the generalised Maxwell model formulated through the classical exponential Prony series, and the second approach is a model based on fractional calculus. In order to quantify the comparative capabilities of both models, experimental data from tensile creep tests on fibre-reinforced polybutylene terephthalate and unreinforced polybutylene terephthalate specimens are analysed. A central contribution of this work is the implementation of a machine-learning-ready parameter identification framework that enables the automated extraction of model parameters directly from time-series data. This framework enables the robust fitting of the Prony-based model, which requires multiple characteristic times and stiffness parameters, as well as the fractional model, which achieves high accuracy with significantly fewer parameters. The fractional model benefits from a novel neural solver for fractional differential equations, which not only reduces computational complexity but also permits the interpretation of the fractional order and stiffness coefficient in terms of physical creep resistance. The methodological framework is validated through a comparative assessment of predictive performance, parameter cheapness, and interpretability of each model, thereby providing a comprehensive understanding of their applicability to long-term material behaviour modelling in polymer-based composite materials.Vo
Time-domain analysis of signal morphology and features as suitable surrogates for structural monitoring
No full textThis is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. (http://creativecommons.org/licenses/by/4.0/)Vo
Examining the structure of the Student-Educator Negotiated Critical Thinking Dispositions Scale in four countries
No full textVo
Ytterbium-laser-driven THz generation in thin lithium niobate at 1.9 kW average power in a passive enhancement cavity
No full textAll article content, except where otherwise noted, is licensed under a Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).Single-cycle, high-power, high-repetition-rate THz pulse sources are becoming the cornerstone of several scientific and industrial applications. A promising and versatile method for high-power THz generation is optical rectification in nonlinear crystals pumped by powerful near-infrared ultrafast laser systems. In this context, ytterbium-based laser sources are particularly advantageous in terms of power scalability and technology establishment. However, as the repetition rate increases toward hundreds of MHz, the conversion efficiency typically decreases, as most laser systems do not reach sufficiently high average powers to correspondingly enhance the peak power to drive the nonlinear conversion process efficiently. An alternative approach to achieving a sufficiently high average power at a high repetition rate is based on passive enhancement cavities, which boost the pulse energy of standard watt-level ytterbium lasers by orders of magnitude. We present the first demonstration of optical rectification in a passive enhancement cavity at multi-kW levels, achieved by a 240-fold power enhancement. By irradiating a 50-μm thin lithium niobate plate with 1.9-kW average power inside the enhancement cavity, we generate milliwatt-level THz pulses with 2-THz bandwidth and 93-MHz repetition rate, mostly limited by the driving pulse duration. To the best of our knowledge, this represents the highest driving average power used for optical rectification. This methodology represents a promising new step toward high-repetition-rate and high average power single-cycle THz sources using widely available multi-watt level Yb lasers.Vo
