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A python toolbox for flexibility aggregation and disaggregation: PyFlexAD
No full textThe increasing penetration of volatile renewables and growing electricity demand pose several challenges for power systems. Simultaneously, flexible devices – so called distributed energy resources (DER) – are becoming more widespread, making them attractive for providing ancillary services. The flexibility of a single device can be represented by a set of reference power profiles, and the flexibility of multiple devices by the summation of individual flexibility sets. However, set addition, also known as the Minkowski sum, is usually computationally intractable. This has led to the development of various approximation methods in the literature. The current study improves upon our previously published vertex-based inner approximation, by extending it to more general storage devices and hierarchical aggregation settings. We validate the efficacy and accuracy of the proposed method through case studies using real data and provide the source code of the algorithm as a Python package that enables the (dis-)aggregation of various flexible devices in real-world scenarios
Tracking Any Point Methods for Markerless 3D Tissue Tracking in Endoscopic Stereo Images
No full textMinimally invasive surgery presents challenges such as dynamic tissue motion and a limited field of view. Accurate tissue tracking has the potential to support surgical guidance, improve safety by helping avoid damage to sensitive structures, and enable context-aware robotic assistance during complex procedures. In this work, we propose a novel method for markerless 3D tissue tracking by leveraging 2D Tracking Any Point (TAP) networks. Our method combines two CoTracker models, one for temporal tracking and one for stereo matching, to estimate 3D motion from stereo endoscopic images. We evaluate the system using a clinical laparoscopic setup and a robotic arm simulating tissue motion, with experiments conducted on a synthetic 3D-printed phantom and a chicken tissue phantom. Tracking on the chicken tissue phantom yielded more reliable results, with Euclidean distance errors as low as 1.1 mm at a velocity of 10 mm/s. These findings highlight the potential of TAP-based models for accurate, markerless 3D tracking in challenging surgical scenarios
Berufliche/betriebliche Weiterbildung
No full textBerufliche/betriebliche Weiterbildung ist aufgrund der mit ihr verbundenen wirtschafts-, beschäftigungsfördernden und sozialintegrativen Zielsetzungen positiv konnotiert. Neben der allgemeinen, kulturellen und politischen Weiterbildung bilden die berufliche und insbesondere die betriebliche Weiterbildung hinsichtlich der Teilnehmendenzahl den größten Bereich im Weiterbildungssektor. Nach aktuellen Daten des Statischen Bundesamtes (2025) nehmen 6,2 Millionen erwerbstätige Menschen an beruflicher bzw. betrieblicher Weiterbildung teil, und 77,2 Prozent aller deutschen Unternehmen sind weiterbildungsaktiv. Zudem wird davon ausgegangen, dass die Bedeutung beruflicher Weiterbildung eher zunehmen wird. Obwohl die Relevanz von beruflicher und insbesondere betrieblicher Weiterbildung immer wieder betont wird, kann von einer Persistenz ihrer Kritikpunkte und Defizite ausgegangen werden, mit denen sich die Weiterbildungspolitik und -forschung mehr oder weniger kontinuierlich befasst, und die für uns Anlass für diese Ausgabe von bwp@ waren
A generalized dual potential for inelastic Constitutive Artificial Neural Networks: a JAX implementation at finite strains
No full textWe present a methodology for designing a generalized dual potential, or pseudo potential, for inelastic Constitutive Artificial Neural Networks (iCANNs). This potential, expressed in terms of stress invariants, inherently satisfies thermodynamic consistency for large deformations. In comparison to our previous work, the new potential captures a broader spectrum of material behaviors, including pressure-sensitive inelasticity. To this end, we revisit the underlying thermodynamic framework of iCANNs for finite strain inelasticity and derive conditions for constructing a convex, zero-valued, and non-negative dual potential. To embed these principles in a neural network, we detail the architecture's design, ensuring a priori compliance with thermodynamics. To evaluate the proposed architecture, we study its performance and limitations discovering visco-elastic material behavior, though the method is not limited to visco-elasticity. In this context, we investigate different aspects in the strategy of discovering inelastic materials. Our results indicate that the novel architecture robustly discovers interpretable models and parameters, while autonomously revealing the degree of inelasticity. The iCANN framework, implemented in JAX, is publicly accessible at https://doi.org/10.5281/zenodo.14894687
Poisson approximation for cycles in the generalised random graph
No full textThe generalised random graph contains n vertices with positive i.i.d. weights. The probability of adding an edge between two vertices is increasing in their weights. We require the weight distribution to have finite second moments, and study the point process Cn on {3,4,…}, which counts how many cycles of the respective length are present in the graph. We establish convergence of Cn to a Poisson point process. Under the stronger assumption of the weights having finite fourth moments we provide the following results. When Cn is evaluated on a bounded set A, we provide a rate of convergence. If the graph is additionally subcritical, we extend this to unbounded sets A at the cost of a slower rate of convergence. From this we deduce the limiting distribution of the length of the shortest and longest cycles when the graph is subcritical, including rates of convergence. All mentioned results also apply to the Chung–Lu model and the Norros–Reittu model
Innovative Ansätze zur Berücksichtigung der Nachhaltigkeit in der Produktentwicklung
No full textNachhaltigkeit gewinnt in Gesellschaft und Politik zunehmend an Bedeutung und stellt die Produktentwicklung vor neue Herausforderungen. Zunächst muss Nachhaltigkeit als Zielgröße charakterisiert und quantifiziert werden, um anschließend Maßnahmen zur Steigerung der Nachhaltigkeit ableiten zu können. Einerseits bietet hier Leichtbau Potential zur Reduktion des Ressourcenverbrauchs nutzungsintensiver Produkte, mittels Modularisierung und nachhaltigen Materialien lässt sich andererseits die Kreislauffähigkeit von Produkten steigern
Coelacanth-scale inspired thin-ply composites for load-bearing applications
No full textThin-ply composites are known for their superior in-situ strength and manufacturing quality, offering higher unnotched tensile and compressive strengths compared to conventional laminates. However, their damage suppression capability leads to increased notch sensitivity, where the delamination and matrix cracking mechanisms are suppressed. As a result, thin-ply laminates are limited in their use in critical load-bearing applications. To address this, bio-inspired Bouligand structures, defined by their helical fibre arrangements,
have shown promise in reducing notch sensitivity through helicoidal matrix cracking and stress redistribution. This study explores the mechanical performance of partial Bouligand layups derived from biological fibre architectures observed on coelacanth fish scales, where fibrils reorient under load. An analytical stiffness-based optimization was performed to match the mechanical properties of the conventional [0◦, ±45◦, 90◦] (50%, 40%, 10% load introduction layup used in bolted and riveted aircraft structures, while integrating the partial
Bouligand structure. The weights of the two-layer fibres (30 gsm and 60 gsm) were investigated, resulting in different pitch and stack angles. Tensile and bearing tests were conducted to evaluate the influence of the partial Bouligand structure on bearing sensitivity. The results indicate that bio-inspired fibre orientation can improve load redistribution and damage tolerance in thin-ply laminates, making them compatible for off-axis and notched applications
Wasserstein KL-divergence for Gaussian distributions
No full textWe introduce a new version of the KL-divergence for Gaussian distributions which is based on Wasserstein geometry and referred to as WKL-divergence. We show that this version is consistent with the geometry of the sample space {R}^n. In particular, we can evaluate the WKL-divergence of the Dirac measures concentrated in two points which turns out to be proportional to the squared distance between these points
Computational models of the emergence of self-exploration in 2-month-old infants
No full textInfants actively explore the relationship between actions and their associated effects (i.e., sensorimotor contingencies) before full-blown agency emerges. While there is experimental evidence for this development during the first year of life, the interplay of the associated cognitive processes is not yet well understood. This paper uses computational modeling to examine how exploratory behavior develops, based on one of the earliest experiments showing such behavior. In a seminal study of Rochat & Striano (1999), 2-month-old infants, contrary to newborns, showed differential behavioral patterns towards mouth-contingent sounds versus random sounds. This is interpreted as early evidence for action-effect exploration. We consider seven potential developmental factors as possibly explaining the emergence of active exploratory behavior in 2-month-olds: i) outcome prediction, ii) novelty preference, iii) fatigue, iv) strength, v) memory, vi) sensory noise, and vii) motor noise. These factors were implemented in both a supervised-learning model and a reinforcement learning model. Results from both models indicate that increased memory capacity with age is a key developmental factor underlying active exploration and, possibly, agency. Our code is published at: https://github.com/SpisakJ/Computational-models-of-the-emergence-of-self-exploration-in-2-month-old-infant
Electric vehicle HV-DC EMC filter loss due to variations in AC-load configuration
No full textThe motor of an electric vehicle is connected to the inverter either by cables or busbars if the inverter and motor are integrated in the same housing. Instead of a motor, an equivalent lumped load may be used during EMC pre-compliance testing. Utilizing a SPICE-based simulation model, the conducted emissions of an electric vehicle powertrain are investigated with different AC-load configurations. Shielded AC-cables lead to increased parasitic inductance and capacitance on the AC side of the powertrain. On the HV-DC side of the inverter, EMC filters are required to comply with conducted emissions limits. The filter components, especially those filtering the common mode, are exposed to power loss due to the noise currents on the powertrain. Simulation results for AC-cable lengths 0-3m show that the power loss in the EMC filter components shows a strong dependency on cable length