The quasi-coherent mode (QCM), appearing in enhanced Dα high confinement mode (EDA H-mode) and quasi-continuous exhaust (QCE) plasmas has been analysed in detail at ASDEX Upgrade via thermal helium beam spectroscopy under various discharge parameters. In both scenarios the QCM appears to be localized close to the separatrix and to propagate in ion diamagnetic direction in the plasma frame. The poloidal wavenumber of the QCM is about 0.025 < kθρs < 0.075 and the radial wavenumber is kr ≈ 0 cm-1. It was found that the plasmas are generally below the ideal MHD limit at the separatrix. All the properties are consistent with ideal, resistive or kinetic ballooning modes. Simultaneous to the appearance of the QCM, higher harmonic modes can be observed in EDA H-modes, which are exclusively visible in magnetic pick-up coils and have toroidal mode numbers of up to n = 10. By performing a bicoherence analysis it was found that the higher harmonic modes and the QCM are coupling, but are disjoint phenomena. Qualitatively, the bandwidth of the QCM serves as a promising distinctive feature between QCE plasmas and EDA H-modes.
Temperature estimation plays a vital role across natural sciences. A standard approach is provided by probe thermometry, where a probe is brought into contact with the sample and examined after a certain amount of time has passed. In situations where, for example, preparation of the probe is non-trivial or total measurement time of the experiment is the main resource that must be optimised, continuously monitoring the probe may be preferred. Here, we consider a minimal model, where the probe is provided by a two-level system coupled to a thermal reservoir. Monitoring thermally activated transitions enables real-time estimation of temperature with increasing accuracy over time. Within this framework we comprehensively investigate thermometry in both bosonic and fermionic environments employing a Bayesian approach. Furthermore, we explore adaptive strategies and find a significant improvement on the precision. Additionally, we examine the impact of noise and find that adaptive strategies may suffer more than non-adaptive ones for short observation times. While our main focus is on thermometry, our results are easily extended to the estimation of other environmental parameters, such as chemical potentials and transition rates.
There exists strong experimental evidence that bainitic ferrite is formed as a supersaturated solid solution of carbon within a tetragonally-distorted body-centered iron structure (BCT), where carbon preferentially occupies the octahedral site. Despite this, the BCT structure has not yet been accounted for in the computational analysis of the thermodynamics of the bainite transformation. In the present work, we propose to calculate the onset of the bainite transformation based on the T 0 ′ concept, including the effect of Zener-ordering. This mechanism stabilizes the BCT structure, makes it energetically more favorable than BCC and leads to a significantly higher solubility of C compared Fe-BCC. The computational predictions are made based on a recent reassessment of low-T Gibbs energies and finally compared to experiments. The important role of C is emphasized, with the Fe-C system used as a showcase.
Am Institut für Tragkonstruktionen der TU Wien wurden in den letzten Jahren unterschiedliche Einsatzmöglichkeiten für Halbfertigteilelemente im Brückenbau entwickelt. Aufgrund der Wichtigkeit der Betrachtung von Materialermüdung ist ein besonderes Augenmerk auf die eingebaute heftgeschweißte Bewehrung zu legen. Nach einem kurzen Überblick über die Einsatzmöglichkeiten wie auch die allgemein gültigen Regelungen in Bezug auf Materialermüdung werden im vorliegenden Beitrag experimentelle Untersuchungen zur Bestimmung der Ermüdungseigenschaften von heftgeschweißter Bewehrung vorgestellt. Die Eigenschaften wurden einerseits mithilfe von 18 zentrischen Zugversuchen an Bewehrungsstäben mit angehefteten Querstäben, anderseits mithilfe von zwölf großformatigen, auf Biegung beanspruchten Balkenelementen untersucht. Als wesentliche Erkenntnis kann das Vorhandensein einer Restphase bei einem realitätsnahen System genannt werden, wodurch sich ein Zeitraum zwischen dem ersten Stabbruch und dem Totalkollaps des Systems ergibt. Dieses Verhalten wird für die Anwendung in der Praxis als vorteilhaft gesehen, da sich eine Reaktionszeit für die Setzung von etwaigen baulichen Maßnahmen ergibt.
The discussion of energy efficiency in the steel ladle dispatching literature is currently limited to indirectly minimizing waiting and heating times. Not considering the ladle’s thermal balance explicitly may lead to sub-optimal solutions and safety concerns regarding the condition of the refractory lining. Hence, this paper studies the energy-efficient ladle dispatching problem with refractory temperature control. A mixed integer linear problem for ladle dispatching that integrates its energy balance is presented. It enables the global solution of the problem using state-of-the-art mixed integer programming solvers. This is achieved by applying piecewise linear models with logarithmic coding to approximate the energy balance. Computational results show that the number of breakpoints employed significantly affects the approximation quality and solution time. However, we show that the error does not affect the feasibility of the problem and yields a negligible difference of 1.4% in the objective function. Hence, this viable approach enables a proper discussion on the energy efficiency of ladle dispatching decisions. For a small but representative production scenario from Tata Steel, IJmuiden, we design and execute an experiment to define a set of operational rules and discuss the potential energy savings. We conclude by presenting the existing compromise between the CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> emissions from re-heating the ladles and the reduction in the steel temperature losses from the improved thermal management of the ladles. We show that the average steel temperature losses can be reduced up to 3 °C depending on the refractory temperature requirement. This has the potential to unlock further savings for steelmakers.
Smart contracts are small programs on the blockchain that often handle valuable assets. Vulnerabilities in smart contracts can be costly, as time has shown over and over again. Countermeasures are high in demand and include best practice recommendations as well as tools supporting development, program verification, and post-deployment analysis. Many tools focus on detecting the absence or presence of a subset of the known vulnerabilities, delivering results of varying quality. Most comparative tool evaluations resort to selecting a handful of tools and testing them against each other. In the best case, the evaluation is based on a smallish ground truth. For Ethereum, there are commendable efforts by several author groups to manually classify contracts. However, a comprehensive ground truth is still lacking. In this work, we construct a ground truth based on publicly available benchmark sets for Ethereum smart contracts with manually checked ground truth data. We develop a method to unify these sets. Additionally, we devise strategies for matching entries that pertain to the same contract, such that we can determine overlaps and disagreements between the sets and consolidate the disagreements. Finally, we assess the quality of the included ground truth sets. Our work reduces inconsistencies, redundancies, and incompleteness while increasing the number of data points and their heterogeneity.
Discrete surfaces with spherical faces are interesting from a simplified manufacturing viewpoint when compared to other double curved face shapes. Furthermore, by the nature of their definition they are also appealing from the theoretical side leading to a Möbius invariant discrete surface theory. We therefore systematically describe so called sphere meshes with spherical faces and circular arcs as edges where the Möbius transformation group acts on all of its elements. Driven by aspects important for manufacturing, we provide the means to cluster spherical panels by their radii. We investigate the generation of sphere meshes which allow for a geometric support structure and characterize all such meshes with triangular combinatorics in terms of non-Euclidean geometries. We generate sphere meshes with hexagonal combinatorics by intersecting tangential spheres of a reference surface and let them evolve - guided by the surface curvature - to visually convex hexagons, even in negatively curved areas. Furthermore, we extend meshes with circular faces of all combinatorics to sphere meshes by filling its circles with suitable spherical caps and provide a remeshing scheme to obtain quadrilateral sphere meshes with support structure from given sphere congruences. By broadening polyhedral meshes to sphere meshes we exploit the additional degrees of freedom to minimize intersection angles of neighboring spheres enabling the use of spherical panels that provide a softer perception of the overall surface.
Background: High spectral power density provided by advances in external cavity quantum cascade lasers (EC-QCL) have enabled increased transmission path lengths in mid-infrared (mid-IR) spectroscopy for more sensitive measurement of proteins in aqueous solutions. These extended path lengths also facilitate flow through measurements by avoiding congestion of the flow cell by protein aggregates. Despite the advantages presented by laser-based mid-IR spectroscopy of proteins, extraction of secondary structure information from spectra, especially in the presence of complex multi-component matrices with overlapping spectral features, remains an impediment that requires fine tuning of evaluation algorithms (e.g., band fitting, interpretation of second derivative spectra etc.). Results: In this work, the use of multivariate curve resolution alternating least squares (MCR-ALS) for the analysis of a chemical de- and renaturation experiment has been demonstrated, since this technique offers the second-order advantage of extracting spectral signatures and concentration profiles even in the presence of unknown, uncalibrated constituents. Furthermore, we exhibit a partial least squares regression (PLSR) based subtraction of matrix component spectra prior to MCR-ALS as a method to obtain secondary structure information even in the absence of reference spectra. These approaches are showcased using the online reaction monitoring of the titration of β-lactoglobulin (β-LG) in water against the surfactants sodium dodecyl sulfate (SDS) and octaethylene glyol monododecyl ether (C12E8), using a commercially available laser-based IR spectrometer. Results for the automated PLSR correction plus MCR-ALS approach compare favorably to an MCR-ALS standalone approach using initial estimates as well as analysis of secondary structure using data processed with a manual baseline correction. Significance: The herein described chemometric approach suggests a way to simplify the challenge of handling complex matrices in protein structure analysis by isolating the background from the protein contributions, prior to analysis via other soft-modelling techniques. Consequently, the findings of this study indicate the suitability of online reaction monitoring through mid-IR spectroscopy combined with chemometric techniques as a potential tool in downstream quality control and process automation.
Over the past decade, Knowledge Graphs have received enormous interest both from industry and from academia. Research in this area has been driven, above all, by the Database (DB) community and the Semantic Web (SW) community. However, there still remains a certain divide between approaches coming from these two communities. For instance, while languages such as SQL or Datalog are widely used in the DB area, a different set of languages such as SPARQL and OWL is used in the SW area. Interoperability between such technologies is still a challenge. The goal of this work is to present a uniform and consistent framework meeting important requirements from both, the SW and DB field.
Thermal treatments can have detrimental effects on the photocatalytic hydrogen (H 2 ) evolution performance and impact the formation mechanism of the active state of surface‐supported co‐catalysts. In this work, a range of Ni‐based co‐catalysts is investigated immobilized on TiO 2 , evaluated their H 2 evolution rates in situ over 21 h, and analyzed the samples at various stages with a comprehensive set of spectroscopic and microscopy techniques. It is found that achieving the optimal hydrogen evolution (HER) performance requires the right Ni ⁰ :Ni ²⁺ ratio, rather than only Ni ⁰ , and that Ni needs to be weakly adsorbed on the TiO 2 surface to create a dynamic state. Under these conditions, Ni can undergo an efficient redox shuttle, involving the transformation of Ni ²⁺ to Ni ⁰ and back after releasing the accumulated electrons for H ⁺ reduction (i.e., Ni ²⁺ ↔ Ni ⁰ ). Yet, when the calcination temperature of the Ni/TiO 2 photocatalysts increases, resulting in stronger coordination/adsorption of Ni on TiO 2 , this process is gradually inhibited, which ultimately leads to decreased HER performances. This work emphasizes the significance and influence of thermal treatments on the Ni active state formation – a process that can be relevant to other HER co‐catalysts.
Robots play a vital role in modern automation, with applications in manufacturing and healthcare. Collaborative robots integrate human and robot movements. Therefore, it is essential to ensure that interactions involve qualified, and thus identified, individuals. This study delves into a new approach: identifying individuals through robot arm movements. Different from previous methods, users guide the robot, and the robot senses the movements via joint sensors. We asked 18 participants to perform six gestures, revealing the potential use as unique behavioral traits or biometrics, achieving F1-score up to 0.87, which suggests direct robot interactions as a promising avenue for implicit and explicit user identification.
One key bottleneck of employing state-of-the-art semantic segmentation networks in the real world is the availability of training labels. Conventional semantic segmentation networks require massive pixel-wise annotated labels to reach state-of-the-art prediction quality. Hence, several works focus on semantic segmentation networks trained with only image-level annotations. However, when scrutinizing the results of state-of-the-art in more detail, we notice that they are remarkably close to each other on average prediction quality, different approaches perform better in different classes while providing low quality in others. To address this problem, we propose a novel framework, ISLE, which employs an ensemble of the “pseudo-labels” for a given set of different semantic segmentation techniques on a class-wise level. Pseudo-labels are the pixel-wise predictions of the image-level semantic segmentation frameworks used to train the final segmentation model. Our pseudo-labels seamlessly combine the strong points of multiple segmentation techniques approaches to reach superior prediction quality. We reach up to 2.4% improvement over ISLE’s individual components. An exhaustive analysis was performed to demonstrate ISLE’s effectiveness over state-of-the-art frameworks for image-level semantic segmentation.
A new compact micro‐x‐ray fluorescence (μ‐XRF) spectrometer covering wide range of elements was developed and fabricated. The working capabilities of this new compact custom‐made μ‐XRF spectrometer are presented. The spectrometer uses a low power Rh target x‐ray tube for sample excitation. Polycapillary optics focuses the polychromatic beam down to 40 μm. The emitted radiation is measured by a peltier cooled silicon drift detector of 30 mm ² crystal size. It was observed that the polychromatic excitation provides sufficient photons for an efficient excitation of the sample to achieve good detection limit and area resolution. The detection limits are comparable with that one obtained by TXRF for a thin film sample. The advantage of the present setup, is the fact that it is suitable for specific applications for example, for radioactive and toxic samples requiring instrument adoption in glove boxes or fume hoods because of its good analytical features accompanied by simple and compact instrumentation.
Thiomolybdates are molecular molybdenum‐sulfide clusters formed from Mo centers and sulfur‐based ligands. For decades, they have attracted the interest of synthetic chemists due to their unique structures and their relevance in biological systems, e.g., as reactive sites in enzymes. More recently, thiomolybdates have been explored from the catalytic point of view and applied as homogeneous and molecular mimics of heterogeneous molybdenum sulfide catalysts. This review summarizes prominent examples of thiomolybdate‐based electro‐ and photocatalysis and provides a comprehensive analysis of their reactivities under homogeneous and heterogenized conditions. Active sites of thiomolybdates relevant for the hydrogen evolution reaction (HER) are examined, aiming to shed light on the link between cluster structure and performance. The shift from solution‐phase to surface‐supported thiomolybdates is discussed with a focus on applications in electrocatalysis and photocatalysis. The outlook highlights current trends and emerging areas of thiomolybdate research, ending with a summary of challenges and key takeaway messages based on the state‐of‐the‐art research. This article is protected by copyright. All rights reserved
The proposed Kirchhoff-Love shell stress resultant plasticity model extends a previously reported model for plates by complementing the constitutive law of elastoplasticity with membrane effects. This enhanced model is designed for bending dominant settings with small to moderate membrane forces. It is thus implemented in a purpose-built nonlinear mixed Eulerian–Lagrangian finite element scheme for the simulation of sheet metal roll forming. Numerical experiments by imposing artificial strain histories on a through-the-thickness element are conducted to test the model against previously reported stress resultant plasticity models and to validate it against the traditional continuum plasticity approach that features an integration of relations of elastoplasticity in a set of grid points distributed over the thickness. Results of actual roll forming simulations demonstrate the practicality in comparison to the computationally more expensive continuum plasticity approach.
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