13 Zentrale Universitätseinrichtungen

Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/14

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2021 - 202325

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Institute: search.filters.UBSInstitut.Fakultätsübergreifend / Sonstige EinrichtungStart date: 2021End date: 2023

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Now showing 1 - 10 of 25
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    Touching data with PropellerHand
    (2022) Achberger, Alexander; Heyen, Frank; Vidackovic, Kresimir; Sedlmair, Michael
    Immersive analytics often takes place in virtual environments which promise the users immersion. To fulfill this promise, sensory feedback, such as haptics, is an important component, which is however not well supported yet. Existing haptic devices are often expensive, stationary, or occupy the user’s hand, preventing them from grasping objects or using a controller. We propose PropellerHand, an ungrounded hand-mounted haptic device with two rotatable propellers, that allows exerting forces on the hand without obstructing hand use. PropellerHand is able to simulate feedback such as weight and torque by generating thrust up to 11 N in 2-DOF and a torque of 1.87 Nm in 2-DOF. Its design builds on our experience from quantitative and qualitative experiments with different form factors and parts. We evaluated our prototype through a qualitative user study in various VR scenarios that required participants to manipulate virtual objects in different ways, while changing between torques and directional forces. Results show that PropellerHand improves users’ immersion in virtual reality. Additionally, we conducted a second user study in the field of immersive visualization to investigate the potential benefits of PropellerHand there.
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    Datamator : an authoring tool for creating datamations via data query decomposition
    (2023) Guo, Yi; Cao, Nan; Cai, Ligan; Wu, Yanqiu; Weiskopf, Daniel; Shi, Danqing; Chen, Qing
    Datamation is designed to animate an analysis pipeline step by step, serving as an intuitive and efficient method for interpreting data analysis outcomes and facilitating easy sharing with others. However, the creation of a datamation is a difficult task that demands expertise in diverse skills. To simplify this task, we introduce Datamator, a language-oriented authoring tool developed to support datamation generation. In this system, we develop a data query analyzer that enables users to generate an initial datamation effortlessly by inputting a data question in natural language. Then, the datamation is displayed in an interactive editor that affords users the ability to both edit the analysis progression and delve into the specifics of each step undertaken. Notably, the Datamator incorporates a novel calibration network that is able to optimize the outputs of the query decomposition network using a small amount of user feedback. To demonstrate the effectiveness of Datamator, we conduct a series of evaluations including performance validation, a controlled user study, and expert interviews.
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    Local bilinear computation of Jacobi sets
    (2022) Klötzl, Daniel; Krake, Tim; Zhou, Youjia; Hotz, Ingrid; Wang, Bei; Weiskopf, Daniel
    We propose a novel method for the computation of Jacobi sets in 2D domains. The Jacobi set is a topological descriptor based on Morse theory that captures gradient alignments among multiple scalar fields, which is useful for multi-field visualization. Previous Jacobi set computations use piecewise linear approximations on triangulations that result in discretization artifacts like zig-zag patterns. In this paper, we utilize a local bilinear method to obtain a more precise approximation of Jacobi sets by preserving the topology and improving the geometry. Consequently, zig-zag patterns on edges are avoided, resulting in a smoother Jacobi set representation. Our experiments show a better convergence with increasing resolution compared to the piecewise linear method. We utilize this advantage with an efficient local subdivision scheme. Finally, our approach is evaluated qualitatively and quantitatively in comparison with previous methods for different mesh resolutions and across a number of synthetic and real-world examples.
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    Visual analysis of droplet dynamics in large-scale multiphase spray simulations
    (2021) Heinemann, Moritz; Frey, Steffen; Tkachev, Gleb; Straub, Alexander; Sadlo, Filip; Ertl, Thomas
    We present a data-driven visual analysis approach for the in-depth exploration of large numbers of droplets. Understanding droplet dynamics in sprays is of interest across many scientific fields for both simulation scientists and engineers. In this paper, we analyze large-scale direct numerical simulation datasets of the two-phase flow of non-Newtonian jets. Our interactive visual analysis approach comprises various dedicated exploration modalities that are supplemented by directly linking to ParaView. This hybrid setup supports a detailed investigation of droplets, both in the spatial domain and in terms of physical quantities. Considering a large variety of extracted physical quantities for each droplet enables investigating different aspects of interest in our data. To get an overview of different types of characteristic behaviors, we cluster massive numbers of droplets to analyze different types of occurring behaviors via domain-specific pre-aggregation, as well as different methods and parameters. Extraordinary temporal patterns are of high interest, especially to investigate edge cases and detect potential simulation issues. For this, we use a neural network-based approach to predict the development of these physical quantities and identify irregularly advected droplets.
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    A novel runtime algorithm for the real-time analysis and detection of unexpected changes in a real-size SHM network with quasi-distributed FBG sensors
    (2021) Sakiyama, Felipe Isamu H.; Lehmann, Frank; Garrecht, Harald
    The ability to track the structural condition of existing structures is one of the main concerns of bridge owners and operators. In the context of bridge maintenance programs, visual inspection predominates nowadays as the primary source of information. Yet, visual inspections alone are insufficient to satisfy the current needs for safety assessment. From this perspective, extensive research on structural health monitoring has been developed in recent decades. However, the transfer rate from laboratory experiments to real-case applications is still unsatisfactory. This paper addresses the main limitations that slow the deployment and the acceptance of real-size structural health monitoring systems (SHM) and presents a novel real-time analysis algorithm based on random variable correlation for condition monitoring. The proposed algorithm was designed to respond automatically to detect unexpected events, such as local structural failure, within a multitude of random dynamic loads. The results are part of a project on SHM, where a high sensor-count monitoring system based on long-gauge fiber Bragg grating sensors (LGFBG) was installed on a prestressed concrete bridge in Neckarsulm, Germany. The authors also present the data management system developed to handle a large amount of data, and demonstrate the results from one of the implemented post-processing methods, the principal component analysis (PCA). The results showed that the deployed SHM system successfully translates the massive raw data into meaningful information. The proposed real-time analysis algorithm delivers a reliable notification system that allows bridge managers to track unexpected events as a basis for decision-making.
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    Hagrid : using Hilbert and Gosper curves to gridify scatterplots
    (2022) Cutura, Rene; Morariu, Cristina; Cheng, Zhanglin; Wang, Yunhai; Weiskopf, Daniel; Sedlmair, Michael
    A common enhancement of scatterplots represents points as small multiples, glyphs, or thumbnail images. As this encoding often results in overlaps, a general strategy is to alter the position of the data points, for instance, to a grid-like structure. Previous approaches rely on solving expensive optimization problems or on dividing the space that alter the global structure of the scatterplot. To find a good balance between efficiency and neighborhood and layout preservation, we propose Hagrid , a technique that uses space-filling curves (SFCs) to “gridify” a scatterplot without employing expensive collision detection and handling mechanisms. Using SFCs ensures that the points are plotted close to their original position, retaining approximately the same global structure. The resulting scatterplot is mapped onto a rectangular or hexagonal grid, using Hilbert and Gosper curves. We discuss and evaluate the theoretic runtime of our approach and quantitatively compare our approach to three state-of-the-art gridifying approaches, DGrid , Small multiples with gaps SMWG , and CorrelatedMultiples CMDS , in an evaluation comprising 339 scatterplots. Here, we compute several quality measures for neighborhood preservation together with an analysis of the actual runtimes. The main results show that, compared to the best other technique, Hagrid is faster by a factor of four, while achieving similar or even better quality of the gridified layout. Due to its computational efficiency, our approach also allows novel applications of gridifying approaches in interactive settings, such as removing local overlap upon hovering over a scatterplot.
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    Soya yield prediction on a within-field scale using machine learning models trained on Sentinel-2 and soil data
    (2022) Pejak, Branislav; Lugonja, Predrag; Antić, Aleksandar; Panić, Marko; Pandžić, Miloš; Alexakis, Emmanouil; Mavrepis, Philip; Zhou, Naweiluo; Marko, Oskar; Crnojević, Vladimir
    Agriculture is the backbone and the main sector of the industry for many countries in the world. Assessing crop yields is key to optimising on-field decisions and defining sustainable agricultural strategies. Remote sensing applications have greatly enhanced our ability to monitor and manage farming operation. The main objective of this research was to evaluate machine learning system for within-field soya yield prediction trained on Sentinel-2 multispectral images and soil parameters. Multispectral images used in the study came from ESA’s Sentinel-2 satellites. A total of 3 cloud-free Sentinel-2 multispectral images per year from specific periods of vegetation were used to obtain the time-series necessary for crop yield prediction. Yield monitor data were collected in three crop seasons (2018, 2019 and 2020) from a number of farms located in Upper Austria. The ground-truth database consisted of information about the location of the fields and crop yield monitor data on 411 ha of farmland. A novel method, namely the Polygon-Pixel Interpolation, for optimal fitting yield monitor data with satellite images is introduced. Several machine learning algorithms, such as Multiple Linear Regression, Support Vector Machine, eXtreme Gradient Boosting, Stochastic Gradient Descent and Random Forest, were compared for their performance in soya yield prediction. Among the tested machine learning algorithms, Stochastic Gradient Descent regression model performed better than the others, with a mean absolute error of 4.36 kg/pixel (0.436 t/ha) and a correlation coefficient of 0.83%.
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    Performance‐Prüfverfahren für den Sulfatwiderstand von Beton
    (2023) Vollpracht, Anya; Feldrappe, Volkert; Overmann, Steffen; Haufe, Johannes; Ehrenberg, Andreas; Beutel, Ralf; Matschei, Thomas
    Die aktuellen Normen für die Anwendung von Beton sehen deskriptive Regeln für den Einbau in sulfathaltigen Böden und Grundwässern vor. Diese Vorgehensweise schränkt die Anwendungsmöglichkeiten von neuen Bindemitteln und alternativen Betonrezepturen erheblich ein, da diese Baustoffe eine Zustimmung im Einzelfall oder eine allgemeine bauaufsichtliche Zulassung benötigen. Im Zulassungsbereich steht aktuell für die meisten Bindemittel nur das sehr zeitintensive modifizierte SVA‐Verfahren zur Verfügung, mit dem erst nach 2 Jahren Versuchslaufzeit eine Zulassung erfolgen kann. Es wurde daher ein Performance‐Prüfverfahren erarbeitet, das auf der Prüfung der Zugfestigkeit von in Sulfatlösung gelagerten Betonproben basiert. Das Verfahren wurde anhand von 23 verschiedenen Bindemitteln im Hinblick auf seine Aussagekraft untersucht und Abnahmekriterien vorgeschlagen. Derzeit werden Vergleichsuntersuchungen im Labor mit unterschiedlichen w/z‐Werten durchgeführt und es laufen Auslagerungsversuche in einem Anhydrit‐Bergwerk, wo die Proben einer Sulfatkonzentration von 1500 bis 2000 mg/l ausgesetzt sind. Die Proben wurden im Juli 2018 ausgelagert. Darüber hinaus ist ein Ringversuch in Bearbeitung. In diesem Beitrag wird über die Fortschritte zur Etablierung des Prüfverfahrens berichtet.
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    Compressive fatigue investigation on high-strength and ultra-high-strength concrete within the SPP 2020
    (2022) Basaldella, Marco; Jentsch, Marvin; Oneschkow, Nadja; Markert, Martin; Lohaus, Ludger
    The influence of the compressive strength of concrete on fatigue resistance has not been investigated thoroughly and contradictory results can be found in the literature. To date, the focus of concrete fatigue research has been on the determination of the numbers of cycles to failure. Concerning the fatigue behaviour of high-strength concrete (HPC) and, especially, ultra-high-strength concrete (UHPC), which is described by damage indicators such as strain and stiffness development, little knowledge is available, as well as with respect to the underlying damage mechanisms. This lack of knowledge has led to uncertainties concerning the treatment of high-strength and ultra-high-strength concretes in the fatigue design rules. This paper aims to decrease the lack of knowledge concerning the fatigue behaviour of concrete compositions characterised by a very high strength. Within the priority programme SPP 2020, one HPC and one UHPC subjected to monotonically increasing and cyclic loading were investigated comparatively in terms of their numbers of cycles to failure, as well as the damage indicators strain and stiffness. The results show that the UHPC reaches a higher stiffness and a higher ultimate strain and strength than the HPC. The fatigue investigations reveal that the UHPC can resist a higher number of cycles to failure than the HPC and the damage indicators show an improved fatigue behaviour of the UHPC compared to the HPC.
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    Anisotropy of the tribological performance of periodically oxidated laser-induced periodic surface structures
    (2023) Onufrijevs, Pavels; Grase, Liga; Padgurskas, Juozas; Rukanskis, Mindaugas; Durena, Ramona; Willer, Dieter; Iesalnieks, Mairis; Lungevics, Janis; Kaupuzs, Jevgenijs; Rukuiža, Raimundas; Kriūkienė, Rita; Hanesch, Yuliya; Speicher, Magdalena
    Laser-induced periodic surface structures (LIPSS) enable advanced surface functionalization with broad applications in various fields such as micro- and nanoelectronics, medicine, microbiology, tribology, anti-icing systems, and more. This study demonstrates the possibility of achieving anisotropy in the tribological behavior of C45-grade steel structured by nanosecond laser radiation using the LIPSS method. The lateral surface of the steel roller was irradiated with a pulsed Nd:YAG laser at an optimum intensity I = 870 MW/cm2 for the formation of LIPSS. Two sets of samples were formed with LIPSS that were perpendicular and parallel to the roller’s rotational motion direction. The Raman intensity maps revealed that the LIPSS structure consisted of periodically arranged oxides at the top of hills. At the same time, the valleys of the LIPSS structures were almost not oxidized. These results correlated well with scanning electron microscopy energy dispersive X-ray spectroscopy mapping and atomic force microscopy measurements. A comparison of Raman and X-ray photoelectron spectroscopy spectra revealed that both the magnetite phase and traces of the hematite phase were present on the surface of the samples. Tribological tests were performed in two cycles with periodic changes in the normal clamping force and sliding speed. It was found that the LIPSS structures which were formed perpendicularly to the sliding direction on the roller had a significantly greater impact on the friction processes. Structures oriented perpendicular to the direction of motion had a positive influence on reducing the energy consumption of a friction process as well as increasing the wear resistance compared to LIPSS formed parallel to the direction of motion or ones having a non-texturized surface. Laser texturing to produce LIPSS perpendicular to the direction of motion could be recommended for friction pairs operating under low-load conditions.